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  1. steipete revised this gist Oct 7, 2025. 1 changed file with 1 addition and 1 deletion.
    2 changes: 1 addition & 1 deletion swagent-spec.md
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    build swagent swift cli and test it yourself until it works.
    use this development key for testing with openai API: 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
    use this development key for testing with openai API: <enter key>

    ---

  2. steipete revised this gist Oct 7, 2025. 1 changed file with 2 additions and 1 deletion.
    3 changes: 2 additions & 1 deletion swagent-spec.md
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    Below is a clean, workshop‑ready guide for **swagent**, split into three parts as requested.
    build swagent swift cli and test it yourself until it works.
    use this development key for testing with openai API: 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

    ---

  3. steipete revised this gist Sep 30, 2025. No changes.
  4. steipete revised this gist Sep 30, 2025. 1 changed file with 267 additions and 261 deletions.
    528 changes: 267 additions & 261 deletions swagent-spec.md
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    Nice—this feedback is gold. I baked **every missing specificity** into your stage prompts and the **one‑go build** so the agent has zero room to guess.
    Below is a clean, workshop‑ready guide for **swagent**, split into three parts as requested.

    Below you’ll find:

    * a **Responses API “contract”** (exact payloads, shapes, key casing)
    * a tighter **system prompt** (macOS 26, self‑testing, behavior when unsure)
    * **stage acceptance checks** that force the model to actually **call `run_bash`** and verify
    * an updated **one‑go build brief** with the full system prompt + a copy‑paste **crib sheet**
    ---

    All references point to the official docs so agents don’t revert to legacy Chat Completions. ([OpenAI Platform][1])
    ## 1) Docs — the exact contract (Responses API, tools, streaming, chaining)

    ---
    **Endpoints**

    ## 🔒 Hardened API contract (copy/paste into your spec)
    * Create/continue a response: `POST https://api.openai.com/v1/responses`
    Headers: `Authorization: Bearer $OPENAI_API_KEY`, `Content-Type: application/json`. ([OpenAI Platform][1])

    **Endpoint**
    **Core request fields**

    ```http
    POST https://api.openai.com/v1/responses
    Authorization: Bearer $OPENAI_API_KEY
    Content-Type: application/json
    ```
    * `model`: `"gpt-5-codex"`.
    * `instructions`: your system rules (string). Re‑send them on **every** turn.
    * `input`: string **or** an array of **items** (e.g., user message, function call outputs).
    * `store: true` if you’ll chain turns later with `previous_response_id`. ([OpenAI Platform][1])

    **Required fields & casing**
    **Tools (function calling)**

    * `model` (e.g., `"gpt-5-codex"`)
    * `instructions` (system‑like rules, string)
    * `input` (the user turn, string or array of items—string is fine here)
    * `store: true` if you plan to chain with `previous_response_id`
    * **Tools (function calling)** go in `tools` as **top‑level** objects:
    * Send tools as **top‑level** objects in `tools` with this shape:

    ```json
    {
    @@ -38,328 +29,343 @@ Content-Type: application/json
    "type": "object",
    "properties": {
    "command": { "type": "string" },
    "cwd": { "type": "string" }
    "cwd": { "type": "string" }
    },
    "required": ["command"]
    }
    }
    ```
    * You can let the model choose with `"tool_choice": "auto"`. ([OpenAI Platform][2])

    > **Do not** use the old nested `function: { name, ... }` shape from Assistants. Responses uses **top‑level** `name/description/parameters`. ([OpenAI Platform][2])
    **Conversation state**

    * To continue a conversation **without** resending the whole transcript, pass `previous_response_id` on the next call.
    * **Important:** `instructions` are **not carried over** with `previous_response_id`; **re‑send** your system prompt each turn. ([OpenAI Platform][3])
    **Function‑call loop (no `tool_outputs` param)**

    **Usage metrics (footer numbers)**
    1. First call: model may return **items** of `type: "function_call"` in `output` with `call_id`, `name`, and `arguments` (JSON string).
    2. Run the tool locally.
    3. Continue the run by calling `POST /v1/responses` **again** with:

    * Current casing: `usage.input_tokens`, `usage.output_tokens`, `usage.total_tokens` (snake_case). Use these for the per‑turn stats footer. ([OpenAI Platform][4])
    * `previous_response_id`: the prior response `id`
    * `instructions`: the same system rules
    * `input`: an **array of items**, each

    **Output structure (what you’ll parse)**
    ```json
    {
    "type": "function_call_output",
    "call_id": "<same id>",
    "output": "<stringified JSON like { stdout, stderr, exitCode }>"
    }
    ```

    * `output` is an **array of items**. Expect **assistant messages** and possible **function calls**:
    This is how you return tool results. Don’t send a top‑level `tool_outputs` field. ([OpenAI Platform][3])

    * Assistant text lives in a message item’s `content` as `{ "type": "output_text", "text": "..." }`. ([OpenAI Platform][3])
    * Function calls appear as items of type **`function_call`** with:
    **Streaming (SSE)**

    ```json
    { "type": "function_call", "call_id": "call_…", "name": "run_bash", "arguments": "{\"command\":\"swift build\"}" }
    ```
    * Set `"stream": true` to get **Server‑Sent Events** while the model is thinking. You’ll receive events such as:

    `arguments` is a **JSON string**. ([OpenAI Platform][5])
    * To **return tool results**, create a follow‑up `responses.create` with:
    * `response.created` (start)
    * `response.output_text.delta` (text chunks)
    * `response.function_call.delta` (incremental function args)
    * `response.completed` (final object, includes `usage`)
    Handle errors via `response.error`. ([OpenAI Platform][4])

    * the same `model`
    * `previous_response_id: "<id from the prior response>"`
    * `tool_outputs: [ { "call_id": "<call id>", "output": "<stringified JSON like { stdout, stderr, exitCode }>" } ]`
    * This yields a new response; continue until the model produces a final message or asks for more info. ([OpenAI Platform][6])
    **Usage & token counters**

    **Minimal end‑to‑end example**
    * Use `usage.input_tokens`, `usage.output_tokens`, `usage.total_tokens` (snake_case) to print per‑turn stats. These arrive on the final response (or `response.completed` in streaming). ([OpenAI Platform][5])

    *Request (turn 1):*

    ```json
    {
    "model": "gpt-5-codex",
    "instructions": "…swagent system rules…",
    "input": "Init a Swift package and build it.",
    "tools": [
    { "type":"function", "name":"run_bash",
    "description":"Run bash", "parameters":{
    "type":"object","properties":{
    "command":{"type":"string"}, "cwd":{"type":"string"}
    },"required":["command"]
    }},
    { "type":"function","name":"request_more_info",
    "parameters":{"type":"object","properties":{"question":{"type":"string"}},"required":["question"]}},
    { "type":"function","name":"finish",
    "parameters":{"type":"object","properties":{"summary":{"type":"string"}},"required":["summary"]}}
    ],
    "tool_choice": "auto",
    "store": true
    }
    ```
    **Conversation state**

    *Response (turn 1 → includes a function call):*
    * To continue a chat **without** resending past text, set `previous_response_id` and re‑send your `instructions`. You may also pass prior output items explicitly if you need. ([OpenAI Platform][6])

    ```json
    {
    "id": "resp_123",
    "output": [
    {
    "type": "message",
    "role": "assistant",
    "content": [ { "type": "output_text", "text": "Creating the package, then building…" } ]
    },
    {
    "type": "function_call",
    "call_id": "call_abc",
    "name": "run_bash",
    "arguments": "{\"command\":\"swift package init --type executable\"}"
    }
    ],
    "usage": { "input_tokens": 395, "output_tokens": 57, "total_tokens": 452 }
    }
    ```
    **Progress signal taxonomy (what to show in the CLI)**

    *Request (turn 2 → return the tool output):*
    * Before the first output token: **“🧠 thinking…”** (spinner) once you receive `response.created`.
    * While streaming text: live print each `response.output_text.delta`.
    * When the model starts a tool: **“🔧 run_bash …”** as soon as you see `response.function_call.delta` / the final `function_call` item.
    * While executing the tool: **“⏳ running command…”** until you post the `function_call_output` and the model resumes.
    * On finalization: **“✅ done”** once `response.completed` arrives, then print the footer with `usage`. ([OpenAI Platform][4])

    ```json
    {
    "model": "gpt-5-codex",
    "instructions": "…swagent system rules…",
    "previous_response_id": "resp_123",
    "tool_outputs": [
    {
    "call_id": "call_abc",
    "output": "{\"stdout\":\"initialized…\",\"stderr\":\"\",\"exitCode\":0}"
    }
    ]
    }
    ```
    ---

    *Response (turn 2 → may include another function call or final text):*
    ## 2) Full instructions — build the whole CLI in one pass

    ```json
    {
    "id": "resp_124",
    "output": [
    { "type":"function_call", "call_id":"call_def", "name":"run_bash",
    "arguments":"{\"command\":\"swift build\"}" }
    ],
    "usage": { "input_tokens": 117, "output_tokens": 12, "total_tokens": 129 }
    }
    ```
    **Project:** `swagent`
    **Language/Tooling:** Swift 6.2 with `SwiftSetting.defaultIsolation(MainActor.self)` enabled via SPM; dependencies: `swift-argument-parser`, `apple/swift-configuration`; built‑in **Swift Testing** (Xcode 26); add **swift-format** and **SwiftLint**.
    **Model/API:** OpenAI **Responses API**, `model: gpt-5-codex`, streaming **on**. ([OpenAI Platform][1])

    …and so on until the model emits a message (with `output_text`) or calls `finish`. ([OpenAI Platform][1])
    **Startup UX**

    **Key deltas vs Chat Completions (so agents don’t regress)**
    * Print **2–3 cheeky lines** (random) and the **masked API key** (first 3 + last 4).
    * Examples:

    * `input` + `instructions` instead of `messages`
    * tool calls are **items** (type `function_call`) with `call_id` + `arguments` string
    * tool **results** are sent via `tool_outputs` (not “tool messages”)
    * conversation uses `previous_response_id` (not an array of past messages)
    Docs walk through each difference. ([OpenAI Platform][5])
    * “🎩 I code therefore I am.”
    * “⚡ One prompt. One shot. Make it count.”
    * “🔧 Small diffs, big wins.”
    * “🧪 If it compiles, we ship. Mostly.”
    * “🐚 Bashful? I’m not.”

    ---
    **Flags**

    ## 🧠 Behavior policy (no guesswork)
    * `-v, --verbose` — extra logs (HTTP status, timings).
    * `--version` — print version.
    * `-p <prompt>` — one‑shot user interaction; **internally** the agent may loop via tools until `finish` or it needs info.
    * `--yolo` — auto‑approve all shell commands (no interactive Y/n).
    * `--session <uuid>` — load a persisted session.

    * **Default stance:** if confident, **answer & act**; if not, call `request_more_info(question)` with one precise question.
    * **Self‑testing is mandatory:** after proposing any command, **call `run_bash`** (post‑approval / `--yolo`) and verify results. If a step fails, iterate until fixed or ask for info.
    * **Live calls please:** run the **real** API end‑to‑end (we’ll provide an `OPENAI_API_KEY`). No stubs during the workshop.
    Function‑calling & tool loop details: see Function Calling + Responses guides. ([OpenAI Platform][7])
    **Commands**

    ---
    * `/new` or `/clear` — reset conversation state.
    * `/status` — show masked key, token totals this session, **estimated** remaining context.
    * `/exit` — quit; print:
    *“To resume this session, call `swagent --session <uuid>`.”*

    ## 🧾 System prompt (final, paste verbatim)
    **System prompt (embed verbatim in `instructions` every turn)**

    > **You are swagent**, a coding agent for terminal workflows.
    > **Runtime:** **macOS 26 or later**.
    > **Mission:** Build, run, and refine code + shell workflows; verify your work.
    > **Behavior:**
    >
    > * Think step‑by‑step; prefer small diffs and working patches.
    > * When you propose commands, you **must** call `run_bash` to execute them (after user approval) and confirm results.
    > * If blocked, call `request_more_info(question)` with one precise, answerable question.
    > * When you propose commands, **call `run_bash`** to execute them; **never** ask the user to confirm (the CLI handles approvals).
    > * If the runtime says **yolo=true**, treat commands as pre‑approved and run immediately.
    > * If **yolo=false** and a command is destructive/ambiguous, call `request_more_info(question)` once; otherwise, just `run_bash`.
    > * When done, call `finish(summary)` with a concise summary + next steps.
    > * Don’t exfiltrate secrets; avoid destructive commands unless asked.
    > * Output stays terminal‑friendly and concise.
    > * Keep output terminal‑friendly and concise; never print secrets.
    > **Tools:**
    >
    > 1. `run_bash(command: string, cwd?: string)` → return `{stdout, stderr, exitCode}`.
    > 1. `run_bash(command: string, cwd?: string)` → returns `{stdout, stderr, exitCode}`.
    > 2. `request_more_info(question: string)`
    > 3. `finish(summary: string)`
    > **API rules (Responses API):**
    > **Responses API rules:**
    >
    > * Use `model: gpt-5-codex`.
    > * Re‑send these instructions every turn.
    > * Chain turns with `previous_response_id`.
    > * Tools are defined with top‑level `name/description/parameters` (JSON Schema).
    > * Tool calls arrive as `function_call` items with a `call_id`; return results using `tool_outputs` with the **same** `call_id`.
    > * Read `usage.input_tokens`, `usage.output_tokens`, `usage.total_tokens` for stats. ([OpenAI Platform][1])
    ---

    ## 🧪 Stage plan (only the deltas that changed, with **self‑test** baked in)
    > * Chain with `previous_response_id`.
    > * Tools are top‑level `{ type:'function', name, description, parameters }`.
    > * Tool calls arrive as `output` items of `type:'function_call'` with a `call_id`. **Return results** by continuing with `previous_response_id` and sending `input: [{ "type":"function_call_output", "call_id":"<same>", "output":"<stringified JSON>" }]`.
    > * Read `usage.input_tokens`, `usage.output_tokens`, `usage.total_tokens` for per‑turn stats.
    > **[swagent runtime]**
    > `yolo=true|false` • `verbose=true|false` • `session=<uuid>` • `cwd=<path>` ([OpenAI Platform][2])

    ### Stage 1 — minimal one‑shot
    **Runtime header**
    Append the `[swagent runtime]` block above to `instructions` every turn (so the agent knows about `yolo`, etc.). ([OpenAI Platform][6])

    * Startup: print **2–3 cheeky lines** + masked key (`sk‑abc…wxyz`).
    * One call to Responses; print reply + footer `(in/out/total, time)`.
    * **Checks (must pass)**
    **Tooling & policies**

    * `swagent -v "ping"` → shows cheeky lines, masked key, HTTP 200 log, model text, usage footer.
    * Missing key → single‑line error.
    * **Usage footer uses snake_case fields** from `usage`. ([OpenAI Platform][4])
    * **Bash tool**: Implement `run_bash(command, cwd?)` via `bash -lc`. By default, prompt `Run? [Y/n]` (Enter=Yes). With `--yolo`, auto‑approve. Return `{stdout, stderr, exitCode}` (JSON), but **stringify** it before sending as `function_call_output`.
    * **Ask‑for‑info tool**: `request_more_info(question)` prints the question and waits for a one‑line user reply; forward that as the next turn’s user message (you can co‑send alongside tool outputs in `input`).
    * **Finish tool**: `finish(summary)` prints the summary and ends the current action (stay in REPL unless in `-p` mode).
    * **Self‑testing**: After code changes, the agent **must** call `run_bash` to run `swift build` (and `swift test` if tests exist), and also self‑invoke the CLI (`swift run swagent …`) to verify flags.

    ### Stage 2 — sticky chat (`-p` still one‑shot)
    **Streaming & progress**

    * Re‑send system prompt every turn; chain with `previous_response_id`.
    * **Checks**
    * Always set `"stream": true` when calling `/v1/responses`. Show:

    * REPL: second turn uses the first turn’s `previous_response_id`.
    * `/new` clears chain; next call has **no** `previous_response_id`. ([OpenAI Platform][8])
    * **Thinking spinner** after `response.created` until first `response.output_text.delta`.
    * **Live text streaming** by writing each `delta` chunk immediately.
    * **Tool call progress** when you see a `function_call` (or its deltas): print the command preview; switch to **“⏳ running…”** while executing; resume streaming once you send `function_call_output`.
    * **Footer** on `response.completed` using `usage.*` and a monotonic timer.
    Event names and flow: see Responses streaming & Realtime guides. ([OpenAI Platform][4])

    ### Stage 3 — agent signals
    **Sessions**

    * Add `finish(summary)` and `request_more_info(question)`; implement tool loop.
    * **Checks**
    * Persist under `~/.swagent/<uuid>.json` via an `actor`.
    * Save: `previous_response_id`, chain of response ids, per‑session token totals, timestamps.
    * `--session <uuid>` loads and continues from file.

    * Prompt: “Ask me one clarifying question, then summarize and finish.”
    → Model calls `request_more_info` → you answer → model calls `finish` → summary printed + stats.
    * Verify: each function call got a **matching** `tool_outputs` entry with the same `call_id`. ([OpenAI Platform][5])
    **Config**

    ### Stage 4 — bash tool + guardrails
    * Use `swift-configuration` to read `OPENAI_API_KEY` from the environment; mask it as `sk‑abc…wxyz` on startup. ([OpenAI Platform][2])

    * Tool: `run_bash(command, cwd?)`; Y/n prompt (Enter = Yes); `--yolo` auto‑approves.
    * Inherit env so the agent can run `swift build` and `swift run` with your real key available.
    * **Checks (self‑test required)**
    **Testing, format, lint**

    * `swagent -p "Create hello.sh, chmod +x, run it"` → agent actually **calls `run_bash`** and shows `stdout: hello`.
    * `swagent --yolo -p "swift --version"` → auto‑runs, returns output, then `finish`.
    * Each tool call returned a **tool output** with the same `call_id`. ([OpenAI Platform][7])
    * Use **Swift Testing** (built‑in with Xcode 26) for unit tests.
    * Add `swift-format` + `SwiftLint` targets/scripts.

    ### Stage 5 — sessions + `/status` + tests
    **Security**

    * Persist `~/.swagent/<uuid>.json` (actor, async file I/O).
    * `/status`: masked key; `usage` totals; **estimated** remaining context.
    * `--session <uuid>` resumes; on exit: “To resume this session, call `swagent --session <uuid>`.”
    * Tests with **Swift Testing** (assume built‑in in your Xcode 26 setup).
    * **Checks**

    * Two turns → `/status` shows snake_case usage fields; `/exit` writes JSON with `previous_response_id`.
    * `--session <uuid>` resumes and chains from file’s `previous_response_id`. ([OpenAI Platform][3])

    ---
    * Never echo secrets.
    * Treat dangerous commands conservatively when `yolo=false` (use `request_more_info`).

    ## 🚀 One‑go build brief (give this to the model)

    > **Project:** `swagent`
    > **Env:** Swift 6.2 (SPM `.defaultIsolation(MainActor.self)`), macOS host
    > **Deps:** `swift-argument-parser`, `apple/swift-configuration`, built‑in **Swift Testing**, plus **swift-format** and **SwiftLint**
    > **System prompt:** *(paste the “System prompt (final)” above verbatim)*
    > **Startup UX:** print 2–3 cheeky lines (random) + masked API key (first 3 + last 4).
    > **Flags:** `-v/--verbose`, `--version`, `-p <prompt>` (one‑shot UI; internal tool loop), `--yolo`, `--session <uuid>`.
    > **Chat & sessions:** interactive REPL with `/new` `/clear` `/status` `/exit`; chain with `previous_response_id` + `store:true`; **always include** the system prompt each turn; persist under `~/.swagent/<uuid>.json`.
    > **Tools (function calling):**
    >
    > * `run_bash(command, cwd?)` → prompt Y/n unless `--yolo`; execute with `bash -lc`; return `{stdout, stderr, exitCode}` (stringified JSON) via `tool_outputs` bound to the **same `call_id`**.
    > * `request_more_info(question)` → ask the user, then continue.
    > * `finish(summary)` → end and print summary.
    > **Per‑turn stats:** print `(in: N, out: M, total: T tokens, 0m 00s)` from `usage`.
    > **Self‑test (mandatory):**
    >
    > 1. After generating code, **call `run_bash`** to run `swift build`.
    > 2. If tests exist, **call `run_bash`** to run `swift test`.
    > 3. **Call `run_bash`** to run:
    >
    > * `swift run swagent --version`
    > * `swift run swagent -p "Echo hello"`
    > * `swift run swagent --yolo -p "Create hello.sh and run it"`
    > 4. On any failure, inspect `stderr`, fix, and retry.
    > **Responses API (use exactly this shape):** tools are **top‑level** (`type/name/description/parameters`); tool calls arrive as `function_call` items with `call_id` + `arguments` (JSON string); tool results go in `tool_outputs`; usage fields are `input_tokens`, `output_tokens`, `total_tokens`. Use `previous_response_id` for chaining and **re‑send** the system prompt each turn.
    > **Docs:** API Reference (Responses), Function Calling, Conversation State / previous_response_id, streaming/output_text, migration notes. ([OpenAI Platform][1])
    ---
    **Minimal JSON crib sheet (copy/paste)**

    ## 📎 Responses API crib sheet (drop right into your repo/readme)

    **Request (with tools):**
    *Create (turn 1, with tools & streaming):*

    ```json
    {
    "model": "gpt-5-codex",
    "instructions": "<SYSTEM PROMPT HERE>",
    "input": "<USER INPUT HERE>",
    "tools": [
    { "type":"function","name":"run_bash","description":"Run bash","parameters":{
    "type":"object","properties":{"command":{"type":"string"},"cwd":{"type":"string"}},
    "required":["command"]
    }},
    { "type":"function","name":"request_more_info","parameters":{
    "type":"object","properties":{"question":{"type":"string"}},"required":["question"]
    }},
    { "type":"function","name":"finish","parameters":{
    "type":"object","properties":{"summary":{"type":"string"}},"required":["summary"]
    }}
    ],
    "instructions": "<SYSTEM PROMPT + [swagent runtime]>",
    "input": "Create a Swift package and build it.",
    "tools": [ { "type":"function","name":"run_bash","description":"Run bash","parameters":{
    "type":"object","properties":{"command":{"type":"string"},"cwd":{"type":"string"}},
    "required":["command"]
    }}, { "type":"function","name":"request_more_info","parameters":{
    "type":"object","properties":{"question":{"type":"string"}},"required":["question"]
    }}, { "type":"function","name":"finish","parameters":{
    "type":"object","properties":{"summary":{"type":"string"}},"required":["summary"]
    }} ],
    "tool_choice": "auto",
    "store": true
    "store": true,
    "stream": true
    }
    ```

    **Response (snippet):**
    *Continue (turn 2, return tool result):*

    ```json
    {
    "id": "resp_abc",
    "output": [
    { "type":"message", "role":"assistant",
    "content":[{ "type":"output_text", "text":"…" }] },
    { "type":"function_call", "call_id":"call_123",
    "name":"run_bash", "arguments":"{\"command\":\"swift build\"}" }
    "model": "gpt-5-codex",
    "instructions": "<SYSTEM PROMPT + [swagent runtime]>",
    "previous_response_id": "resp_123",
    "input": [
    {
    "type": "function_call_output",
    "call_id": "call_abc",
    "output": "{\"stdout\":\"initialized…\",\"stderr\":\"\",\"exitCode\":0}"
    }
    ],
    "usage": { "input_tokens": 123, "output_tokens": 45, "total_tokens": 168 }
    "stream": true
    }
    ```

    **Continue with tool output:**
    Docs: Responses create, streaming events, migration guide (function_call_output), usage counters, conversation state. ([OpenAI Platform][1])

    ```json
    {
    "model": "gpt-5-codex",
    "instructions": "<SYSTEM PROMPT HERE>",
    "previous_response_id": "resp_abc",
    "tool_outputs": [
    { "call_id":"call_123",
    "output":"{\"stdout\":\"…\",\"stderr\":\"\",\"exitCode\":0}" }
    ]
    }
    ```
    ---

    ## 3) Step‑by‑step — 5 tiny stages (each 7–12 minutes), with streaming & checks

    ### Stage 1 — Minimal one‑shot + streaming

    **Build**

    * SPM executable target; enable `SwiftSetting.defaultIsolation(MainActor.self)` in `swiftSettings`.
    * Deps: `swift-argument-parser`, `swift-configuration`.
    * Implement a single **Responses** call with `"stream": true`; stream `response.output_text.delta` to stdout.
    * Startup prints **2–3 cheeky lines** + masked key.
    * Flags: `--version`, `-v`.

    **Checks**

    * `swagent --version` → prints version only.
    * `swagent -v "Ping"` → shows cheeky lines, masked key, streams text live, then footer `(in: X, out: Y, total: Z, 0m 00s)` from `usage`.
    Streaming/usage: see docs. ([OpenAI Platform][4])
    * No key → clear single‑line error.

    ---

    ### Stage 2 — Sticky chat (REPL), `-p` one‑shot, runtime header

    **Build**

    * Interactive REPL; keep `-p` for one‑shot.
    * Maintain state via `previous_response_id` + `store:true`.
    * Always re‑send `instructions` and attach a `[swagent runtime]` header with `yolo`, `verbose`, `session`, `cwd`.

    **Checks**

    * Second user turn uses the first turn’s `previous_response_id` (verify in logs if `-v`).
    * `/new` clears state (next call has no `previous_response_id`).
    * Streaming remains active in both REPL and `-p`.
    Chaining: see conversation state docs. ([OpenAI Platform][6])

    Refs for each bit: Responses API reference, `previous_response_id`, function‑calling loop, `output_text`, `usage` fields. ([OpenAI Platform][1])
    ---

    ### Stage 3 — Agent signals (finish / request_more_info), loop via `function_call_output`

    **Build**

    * Add two tools:

    * `finish(summary: string)`
    * `request_more_info(question: string)`
    * Implement the function‑call loop:

    * Parse any `function_call` items.
    * For `request_more_info`, print the question and wait for input; continue by sending a user message item in `input` (you can send it alongside any `function_call_output` items).
    * For `finish`, print the summary and stop the action.

    **Checks**

    * Prompt: “Ask me one clarifying question, then summarize and finish.”
    → Model calls `request_more_info` → collects answer → model calls `finish` → summary printed + footer.
    * Confirm there’s **no** top‑level `tool_outputs`; only `input` items with `type:"function_call_output"` on continuations. ([OpenAI Platform][3])

    ---

    ## 💬 Startup cheeky lines (pool)
    ### Stage 4 — Bash tool (guardrails), self‑testing, yolo awareness

    **Build**

    * Add `run_bash(command, cwd?)`:

    * Default approval: `Run? [Y/n]` (Enter=Yes).
    * `--yolo`: auto‑approve.
    * Execute via `bash -lc`; capture `{stdout, stderr, exitCode}`; **stringify** as the `output` field in `function_call_output`.
    * **System prompt** and runtime header explicitly say: agent **never** asks for permission; `yolo=true` means pre‑approved.
    * After code changes, agent **must** self‑test: `swift build`, optional `swift test`, then `swift run swagent …`.

    * “🎩 I code therefore I am.”
    * “⚡ One prompt. One shot. Make it count.”
    * “🧪 If it compiles, we ship. Mostly.”
    * “🐚 Bashful? I’m not.”
    * “🔧 Small diffs, big wins.”
    **Checks**

    * `swagent --yolo -p "Echo hello"` → model calls `run_bash("echo hello")` immediately (no extra prompt), CLI runs, continuation sends `function_call_output`, finalizes with a reply + footer.
    * `swagent -p "Echo hello"` (non‑yolo) → agent still **does not** ask; CLI prompts Y/n; run completes.
    * Tool loop uses `previous_response_id` + `input` items, streaming on. ([OpenAI Platform][4])

    ---

    Want me to fold these exact blocks into your Stage 1–5 “paste‑to‑build” prompts so you can run the workshop straight from slides?
    ### Stage 5 — Sessions, `/status`, tests, format/lint

    **Build**

    * Persist sessions under `~/.swagent/<uuid>.json` using an `actor`.
    * `/status` prints: masked key; per‑session token totals; **estimated** context left (model limit minus running total).
    * On exit: *“To resume this session, call `swagent --session <uuid>`.”*
    * Tests with **Swift Testing** for:

    * Arg parsing (`-v`, `--version`, `-p`, `--yolo`, `--session`).
    * Session store save/load roundtrip (concurrent writes protected by actor).
    * Tool approval logic (Y/n default vs `--yolo`).
    * Add `swift-format` and `SwiftLint` targets (`make fmt`, `make lint`, `make check`).

    **Checks**

    * Two turns, then `/status` shows totals; `/exit` persists a JSON containing the latest `previous_response_id`, cumulative `usage`, timestamps.
    * `--session <uuid>` resumes and continues chaining.
    * `make check` runs format, lint, and tests cleanly.

    ---

    ### Minimal streaming cURL (for the slides)

    ```bash
    curl https://api.openai.com/v1/responses \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -H "Content-Type: application/json" \
    -N \
    -d '{
    "model": "gpt-5-codex",
    "instructions": "…system prompt…",
    "input": "Say hello, slowly.",
    "stream": true
    }'
    # Expect SSE events like: response.created, response.output_text.delta, response.completed
    ```

    SSE event names and flow: Responses streaming docs (plus Realtime guide for event taxonomy). ([OpenAI Platform][4])

    ---

    **References**

    * Responses API — create & tools. ([OpenAI Platform][1])
    * Streaming — SSE events for Responses. ([OpenAI Platform][4])
    * Conversation state — `previous_response_id`. ([OpenAI Platform][6])
    * Migration guide — `function_call_output` items. ([OpenAI Platform][3])
    * Usage counters (snake_case). ([OpenAI Platform][5])

    Want a tiny Swift snippet that shows parsing SSE lines and switching the UI between “🧠 thinking…”, streaming text, and tool execution?

    [1]: https://platform.openai.com/docs/api-reference/responses "OpenAI Platform"
    [2]: https://platform.openai.com/docs/quickstart?utm_source=chatgpt.com "Developer quickstart - OpenAI API"
    [3]: https://platform.openai.com/docs/api-reference/responses?utm_source=chatgpt.com "API Reference"
    [4]: https://platform.openai.com/docs/guides/structured-outputs?utm_source=chatgpt.com "Structured model outputs - OpenAI API"
    [5]: https://platform.openai.com/docs/guides/migrate-to-responses?utm_source=chatgpt.com "Migrate to the Responses API"
    [6]: https://platform.openai.com/docs/guides/function-calling?utm_source=chatgpt.com "Function calling - OpenAI API"
    [7]: https://platform.openai.com/docs/guides/tools?utm_source=chatgpt.com "Using tools - OpenAI API"
    [8]: https://platform.openai.com/docs/guides/text?utm_source=chatgpt.com "Text generation - OpenAI API"
    [1]: https://platform.openai.com/docs/api-reference/responses/create?utm_cta=website-homepage-industry-card-media&utm_source=chatgpt.com "API Reference"
    [2]: https://platform.openai.com/docs/api-reference/responses "OpenAI Platform"
    [3]: https://platform.openai.com/docs/guides/migrate-to-responses "OpenAI Platform"
    [4]: https://platform.openai.com/docs/api-reference/responses-streaming "OpenAI Platform"
    [5]: https://platform.openai.com/docs/api-reference/usage "OpenAI Platform"
    [6]: https://platform.openai.com/docs/guides/conversation-state "OpenAI Platform"
  5. steipete revised this gist Sep 30, 2025. 1 changed file with 269 additions and 224 deletions.
    493 changes: 269 additions & 224 deletions swagent-spec.md
    View file
    Original file line number Diff line number Diff line change
    @@ -1,320 +1,365 @@
    Perfect—let’s tune the plan so it’s workshop‑friendly, shows **a few cheeky lines** on startup, **doesn’t print compiler flags**, keeps **macOS 26** only in the **system prompt**, and **expands** the checks so the model + humans both have more to chew on.
    Nice—this feedback is gold. I baked **every missing specificity** into your stage prompts and the **one‑go build** so the agent has zero room to guess.

    ---

    ## What changed (quick)
    Below you’ll find:

    * Startup prints **multiple cheeky lines** + masked API key; **no mention of Swift 6.2 or MainActor** in the output.
    * **System prompt** now explicitly contains **“Runtime: macOS 26 or later”** and is more detailed (pasted in full below).
    * **Stage acceptance checks** beefed up with explicit I/O, example transcripts, and file expectations.
    * **All‑in‑one (one‑go) build prompt** now embeds the **full system prompt**.
    * a **Responses API “contract”** (exact payloads, shapes, key casing)
    * a tighter **system prompt** (macOS 26, self‑testing, behavior when unsure)
    * **stage acceptance checks** that force the model to actually **call `run_bash`** and verify
    * an updated **one‑go build brief** with the full system prompt + a copy‑paste **crib sheet**

    > Build knobs you still apply in code: **Swift 6.2** + **default MainActor isolation** via SPM `SwiftSetting.defaultIsolation(MainActor.self)`; conversation chaining via **Responses API** with `previous_response_id`; **function tools** for finish/ask‑for‑info; and a **bash tool** with Y/n gating or `--yolo`. ([Swift.org][1])
    All references point to the official docs so agents don’t revert to legacy Chat Completions. ([OpenAI Platform][1])

    ---

    ## Stage plan (5 steps, updated + expanded checks)

    ### 1) “Hello, swagent” — minimal one‑shot

    **Build scope**

    * Swift 6.2; set default isolation at module level in **SPM**:

    ```swift
    // swift-tools-version: 6.2
    // ...
    .executableTarget(
    name: "swagent",
    // ...
    swiftSettings: [
    .defaultIsolation(MainActor.self) // SwiftPM 6.2
    ]
    )
    ```

    *Docs:* Swift 6.2 main‑actor default option; SPM `defaultIsolation`. ([Swift.org][1])
    * Deps: `swift-argument-parser` (CLI), `swift-configuration` (reads `OPENAI_API_KEY` from env). ([Apple GitHub][2])
    * Call **OpenAI Responses API** (`model: gpt-5-codex`) once; print the reply. Show token usage from `usage` + elapsed time. ([OpenAI Platform][3])

    **Runtime UX**
    ## 🔒 Hardened API contract (copy/paste into your spec)

    * On launch, print **2–3 cheeky lines** (randomly sampled) + masked API key (`sk‑abc…def0`).
    * Flags: `--version`, `-v` (verbose HTTP codes + timings).
    **Endpoint**

    **Cheeky lines pool (example)**

    ```
    • 🎩 “I code therefore I am. Hit me.”
    • 🧰 “Tabs, spaces, or chaos? Your call.”
    • ⚡ “One prompt. One shot. Make it count.”
    • 🧪 “If it compiles, we ship. Kidding. Mostly.”
    • 🐚 “Bashful? I’m not.”
    ```http
    POST https://api.openai.com/v1/responses
    Authorization: Bearer $OPENAI_API_KEY
    Content-Type: application/json
    ```

    **Expanded checks**
    **Required fields & casing**

    * `model` (e.g., `"gpt-5-codex"`)
    * `instructions` (system‑like rules, string)
    * `input` (the user turn, string or array of items—string is fine here)
    * `store: true` if you plan to chain with `previous_response_id`
    * **Tools (function calling)** go in `tools` as **top‑level** objects:

    ```json
    {
    "type": "function",
    "name": "run_bash",
    "description": "Run a bash command and return stdout, stderr, exitCode.",
    "parameters": {
    "type": "object",
    "properties": {
    "command": { "type": "string" },
    "cwd": { "type": "string" }
    },
    "required": ["command"]
    }
    }
    ```

    * **Env**: with key → shows masked key; without → prints clear error about missing `OPENAI_API_KEY` (no stacktrace).
    * **CLI**:
    > **Do not** use the old nested `function: { name, ... }` shape from Assistants. Responses uses **top‑level** `name/description/parameters`. ([OpenAI Platform][2])
    * `swagent --version` → semantic version line only.
    * `swagent -v "What’s 2+2?"` → prints cheeky intro (2–3 lines), masked key, HTTP 200 in verbose log, model text, and a footer `(in: X, out: Y, total: Z tokens, 0m 01s)`.
    * **Failure paths**: network error surfaces as a single‑line diagnostic in `-v` mode; non‑`-v` shows brief “request failed (HTTP NNN)”.
    **Conversation state**

    References for API, tokens, and arg parsing. ([OpenAI Platform][3])
    * To continue a conversation **without** resending the whole transcript, pass `previous_response_id` on the next call.
    * **Important:** `instructions` are **not carried over** with `previous_response_id`; **re‑send** your system prompt each turn. ([OpenAI Platform][3])

    ---
    **Usage metrics (footer numbers)**

    ### 2) “Sticky chat” — interactive REPL + one‑shot `-p`
    * Current casing: `usage.input_tokens`, `usage.output_tokens`, `usage.total_tokens` (snake_case). Use these for the per‑turn stats footer. ([OpenAI Platform][4])

    **Build scope**
    **Output structure (what you’ll parse)**

    * Add REPL (loop until `/exit`).
    * Keep one‑shot via `-p "…"`.
    * Maintain conversation by passing **`previous_response_id`** each turn. **Always resend your system prompt** each request (instructions aren’t auto‑carried). ([OpenAI Platform][4])
    * `output` is an **array of items**. Expect **assistant messages** and possible **function calls**:

    **Expanded checks**
    * Assistant text lives in a message item’s `content` as `{ "type": "output_text", "text": "..." }`. ([OpenAI Platform][3])
    * Function calls appear as items of type **`function_call`** with:

    * **REPL basics**:
    ```json
    { "type": "function_call", "call_id": "call_…", "name": "run_bash", "arguments": "{\"command\":\"swift build\"}" }
    ```

    * Start `swagent` → cheeky lines + masked key → prompt `›`.
    * Type `Hello` → model replies; prints per‑turn `(tokens, time)`.
    * **Commands**:
    `arguments` is a **JSON string**. ([OpenAI Platform][5])
    * To **return tool results**, create a follow‑up `responses.create` with:

    * `/new` (alias `/clear`) → response chain reset; next call has **no** `previous_response_id`.
    * `/exit` → exits the process.
    * `/status` (preview, wired in Stage 5) → prints “not persisted yet” message in Stage 2.
    * **One‑shot**: `swagent -p "Summarize rust vs swift"` → one response, stats footer, exit.
    * **State**: verify the second turn includes **`previous_response_id`** of the first. (You’ll see longer `in:` tokens owing to chaining.) ([OpenAI Platform][4])
    * the same `model`
    * `previous_response_id: "<id from the prior response>"`
    * `tool_outputs: [ { "call_id": "<call id>", "output": "<stringified JSON like { stdout, stderr, exitCode }>" } ]`
    * This yields a new response; continue until the model produces a final message or asks for more info. ([OpenAI Platform][6])

    ---
    **Minimal end‑to‑end example**

    ### 3) “Agent signals” — finish / ask‑for‑info tools
    *Request (turn 1):*

    **Build scope**
    ```json
    {
    "model": "gpt-5-codex",
    "instructions": "…swagent system rules…",
    "input": "Init a Swift package and build it.",
    "tools": [
    { "type":"function", "name":"run_bash",
    "description":"Run bash", "parameters":{
    "type":"object","properties":{
    "command":{"type":"string"}, "cwd":{"type":"string"}
    },"required":["command"]
    }},
    { "type":"function","name":"request_more_info",
    "parameters":{"type":"object","properties":{"question":{"type":"string"}},"required":["question"]}},
    { "type":"function","name":"finish",
    "parameters":{"type":"object","properties":{"summary":{"type":"string"}},"required":["summary"]}}
    ],
    "tool_choice": "auto",
    "store": true
    }
    ```

    * Add **two function tools** (Responses API `tools`):
    *Response (turn 1 → includes a function call):*

    * `finish(summary: string)`
    * `request_more_info(question: string)`
    * Implement tool‑call loop: when a tool is called, send its **tool output** back (bound to the exact `tool_call_id`), then continue. ([OpenAI Platform][5])
    ```json
    {
    "id": "resp_123",
    "output": [
    {
    "type": "message",
    "role": "assistant",
    "content": [ { "type": "output_text", "text": "Creating the package, then building…" } ]
    },
    {
    "type": "function_call",
    "call_id": "call_abc",
    "name": "run_bash",
    "arguments": "{\"command\":\"swift package init --type executable\"}"
    }
    ],
    "usage": { "input_tokens": 395, "output_tokens": 57, "total_tokens": 452 }
    }
    ```

    **Tool JSON schemas (sketch)**
    *Request (turn 2 → return the tool output):*

    ```json
    {
    "type": "function",
    "name": "finish",
    "description": "Signal task completion with a short summary and next steps.",
    "parameters": { "type": "object", "properties": { "summary": { "type": "string" } }, "required": ["summary"] }
    "model": "gpt-5-codex",
    "instructions": "…swagent system rules…",
    "previous_response_id": "resp_123",
    "tool_outputs": [
    {
    "call_id": "call_abc",
    "output": "{\"stdout\":\"initialized…\",\"stderr\":\"\",\"exitCode\":0}"
    }
    ]
    }
    ```

    *Response (turn 2 → may include another function call or final text):*

    ```json
    {
    "type": "function",
    "name": "request_more_info",
    "description": "Ask the user for missing information to proceed.",
    "parameters": { "type": "object", "properties": { "question": { "type": "string" } }, "required": ["question"] }
    "id": "resp_124",
    "output": [
    { "type":"function_call", "call_id":"call_def", "name":"run_bash",
    "arguments":"{\"command\":\"swift build\"}" }
    ],
    "usage": { "input_tokens": 117, "output_tokens": 12, "total_tokens": 129 }
    }
    ```

    **Expanded checks**
    …and so on until the model emits a message (with `output_text`) or calls `finish`. ([OpenAI Platform][1])

    * Prompt: “Draft a minimal README, ask me one clarifying question, then finish.”
    **Key deltas vs Chat Completions (so agents don’t regress)**

    * Model calls `request_more_info` → CLI prints the question and waits for user input → you answer → model continues → model calls `finish` with a summary → CLI prints summary + stats and returns to prompt (REPL) or exits (`-p`).
    * **Verify**: every assistant tool call is followed by a matching **tool output** before continuing (this is required by function‑calling semantics). If you skip it, you’ll hit tool‑output errors. ([OpenAI Platform][5])
    * `input` + `instructions` instead of `messages`
    * tool calls are **items** (type `function_call`) with `call_id` + `arguments` string
    * tool **results** are sent via `tool_outputs` (not “tool messages”)
    * conversation uses `previous_response_id` (not an array of past messages)
    Docs walk through each difference. ([OpenAI Platform][5])

    ---

    ### 4) “Run commands” — bash tool with guardrails
    ## 🧠 Behavior policy (no guesswork)

    **Build scope**
    * **Default stance:** if confident, **answer & act**; if not, call `request_more_info(question)` with one precise question.
    * **Self‑testing is mandatory:** after proposing any command, **call `run_bash`** (post‑approval / `--yolo`) and verify results. If a step fails, iterate until fixed or ask for info.
    * **Live calls please:** run the **real** API end‑to‑end (we’ll provide an `OPENAI_API_KEY`). No stubs during the workshop.
    Function‑calling & tool loop details: see Function Calling + Responses guides. ([OpenAI Platform][7])

    * Add `run_bash(command: string, cwd?: string)` tool:
    ---

    * On invocation, print the proposed command and ask **`Run? [Y/n]`** (Enter = Yes).
    * `--yolo` auto‑approves.
    * Execute with `bash -lc "<command>"`; capture `stdout`, `stderr`, `exitCode`; return as tool output.
    * `-p` mode: still **one‑shot to the user**, but the **agent may loop internally** across tools until it calls `finish` or `request_more_info`.
    ## 🧾 System prompt (final, paste verbatim)

    **Expanded checks**
    > **You are swagent**, a coding agent for terminal workflows.
    > **Runtime:** **macOS 26 or later**.
    > **Mission:** Build, run, and refine code + shell workflows; verify your work.
    > **Behavior:**
    >
    > * Think step‑by‑step; prefer small diffs and working patches.
    > * When you propose commands, you **must** call `run_bash` to execute them (after user approval) and confirm results.
    > * If blocked, call `request_more_info(question)` with one precise, answerable question.
    > * When done, call `finish(summary)` with a concise summary + next steps.
    > * Don’t exfiltrate secrets; avoid destructive commands unless asked.
    > * Output stays terminal‑friendly and concise.
    > **Tools:**
    >
    > 1. `run_bash(command: string, cwd?: string)` → return `{stdout, stderr, exitCode}`.
    > 2. `request_more_info(question: string)`
    > 3. `finish(summary: string)`
    > **API rules (Responses API):**
    >
    > * Use `model: gpt-5-codex`.
    > * Re‑send these instructions every turn.
    > * Chain turns with `previous_response_id`.
    > * Tools are defined with top‑level `name/description/parameters` (JSON Schema).
    > * Tool calls arrive as `function_call` items with a `call_id`; return results using `tool_outputs` with the **same** `call_id`.
    > * Read `usage.input_tokens`, `usage.output_tokens`, `usage.total_tokens` for stats. ([OpenAI Platform][1])
    * `swagent -p "Create hello.sh that prints hello, make it executable, run it"`
    ---

    * Shows planned commands, asks Y/n, runs, shows `stdout: hello`.
    * On failure (non‑zero exit), model sees `exitCode!=0` + `stderr` and retries.
    * `swagent --yolo -p "swift --version"` → executes without prompt; output returned to model; prints final message + stats.
    * **Audit**: ensure each tool call’s **tool output** uses the **same `tool_call_id`** field the model provided (Responses API requirement). ([OpenAI Platform][5])
    ## 🧪 Stage plan (only the deltas that changed, with **self‑test** baked in)

    ---
    ### Stage 1 — minimal one‑shot

    ### 5) “Sessions, polish, tests” — persistence + status + lint/format
    * Startup: print **2–3 cheeky lines** + masked key (`sk‑abc…wxyz`).
    * One call to Responses; print reply + footer `(in/out/total, time)`.
    * **Checks (must pass)**

    **Build scope**
    * `swagent -v "ping"` → shows cheeky lines, masked key, HTTP 200 log, model text, usage footer.
    * Missing key → single‑line error.
    * **Usage footer uses snake_case fields** from `usage`. ([OpenAI Platform][4])

    * Persist sessions under `~/.swagent/<uuid>.json` via an **actor** (async file I/O).
    * `/status` prints:
    ### Stage 2 — sticky chat (`-p` still one‑shot)

    * masked API key,
    * totals for **input/output/total tokens** this session,
    * **estimated context remaining** (based on model context limit and running total).
    * `--session <uuid>` resumes a saved chain.
    * On exit: print *“To resume this session, call `swagent --session <uuid>`.”*
    * Tests with **Swift Testing** (Xcode 26 includes it). ([GitHub][6])
    * Formatting/linting: **swift-format** + **SwiftLint** targets or scripts. ([GitHub][7])
    * Re‑send system prompt every turn; chain with `previous_response_id`.
    * **Checks**

    **Expanded checks**
    * REPL: second turn uses the first turn’s `previous_response_id`.
    * `/new` clears chain; next call has **no** `previous_response_id`. ([OpenAI Platform][8])

    * **Persistence**:
    ### Stage 3 — agent signals

    * Start chat, send two turns → exit → check `~/.swagent/<uuid>.json` exists and includes: latest `response_id`, cumulative `usage`, timestamps.
    * `swagent --session <uuid>` → prints greeting + “session loaded” note, then the REPL prompt. Next turn continues with `previous_response_id` from file. ([OpenAI Platform][4])
    * **/status** shows something like:
    * Add `finish(summary)` and `request_more_info(question)`; implement tool loop.
    * **Checks**

    ```
    Session: 3B83C2A2-…-8F
    API key: sk-abc…f789
    Tokens used: in=1,820 out=980 total=2,800
    Context headroom (est.): ~170k tokens left
    ```
    * Prompt: “Ask me one clarifying question, then summarize and finish.”
    → Model calls `request_more_info` → you answer → model calls `finish` → summary printed + stats.
    * Verify: each function call got a **matching** `tool_outputs` entry with the same `call_id`. ([OpenAI Platform][5])

    (Token counts from **Responses API `usage`**, context estimate uses model limit minus running input/output tokens; show it as an estimate.) ([OpenAI Platform][8])
    * **Tests**:
    ### Stage 4 — bash tool + guardrails

    * `CLITests`: `--version`, `-p`, `--yolo`, `--session`.
    * `SessionStoreTests`: save/load round‑trip; concurrent reads/writes guarded by the actor.
    * `ToolApprovalTests`: Y/n prompt default acceptance; `--yolo` bypass.
    * **Lint/format**: `make fmt lint` passes (no warnings on default rules).
    * Tool: `run_bash(command, cwd?)`; Y/n prompt (Enter = Yes); `--yolo` auto‑approves.
    * Inherit env so the agent can run `swift build` and `swift run` with your real key available.
    * **Checks (self‑test required)**

    ---
    * `swagent -p "Create hello.sh, chmod +x, run it"` → agent actually **calls `run_bash`** and shows `stdout: hello`.
    * `swagent --yolo -p "swift --version"` → auto‑runs, returns output, then `finish`.
    * Each tool call returned a **tool output** with the same `call_id`. ([OpenAI Platform][7])

    ## System prompt (paste verbatim)
    ### Stage 5 — sessions + `/status` + tests

    > **You are swagent**, a focused coding agent optimized for terminal workflows.
    > **Runtime:** **macOS 26 or later**.
    > **Mission:** Help the user build, run, and refine code and shell workflows efficiently.
    > **Behavior rules:**
    >
    > * Think step‑by‑step; propose small diffs; prefer minimal, working patches.
    > * Only run shell commands via the `run_bash` tool after clearly proposing what will run.
    > * If missing info, call `request_more_info(question)`.
    > * When done, call `finish(summary)` with a concise summary + next steps.
    > * Never print or exfiltrate secrets; avoid destructive commands unless explicitly asked.
    > * Keep answers **terminal‑friendly** and concise.
    > **Tools available:**
    >
    > 1. `run_bash(command: string, cwd?: string)` — execute a shell command and read its output.
    > 2. `request_more_info(question: string)` — ask the user for specifics and wait.
    > 3. `finish(summary: string)` — signal completion and stop.
    > **Conversation:** You are part of a chat. Treat each turn as a continuation. When the user uses one‑shot `-p`, you may internally loop tool calls until you either `finish` or you must `request_more_info`.
    * Persist `~/.swagent/<uuid>.json` (actor, async file I/O).
    * `/status`: masked key; `usage` totals; **estimated** remaining context.
    * `--session <uuid>` resumes; on exit: “To resume this session, call `swagent --session <uuid>`.”
    * Tests with **Swift Testing** (assume built‑in in your Xcode 26 setup).
    * **Checks**

    *(Note: we keep OS here; we intentionally don’t print compiler flags or isolation mode at runtime.)*
    * Two turns → `/status` shows snake_case usage fields; `/exit` writes JSON with `previous_response_id`.
    * `--session <uuid>` resumes and chains from file’s `previous_response_id`. ([OpenAI Platform][3])

    ---

    ## One‑go build prompt (full brief, **now includes the system prompt**)
    ## 🚀 One‑go build brief (give this to the model)

    > **Project name:** `swagent`
    > **Environment:** Swift 6.2 with **default MainActor isolation** (via `.defaultIsolation(MainActor.self)` in SPM), **macOS host**.
    > **Dependencies:** `swift-argument-parser`, `apple/swift-configuration`; built‑in **Swift Testing**; plus **swift-format** and **SwiftLint**.
    > **System prompt to embed (verbatim):**
    > *[insert the “System prompt (paste verbatim)” block above]*
    > **Build & UX requirements:**
    > **Project:** `swagent`
    > **Env:** Swift 6.2 (SPM `.defaultIsolation(MainActor.self)`), macOS host
    > **Deps:** `swift-argument-parser`, `apple/swift-configuration`, built‑in **Swift Testing**, plus **swift-format** and **SwiftLint**
    > **System prompt:** *(paste the “System prompt (final)” above verbatim)*
    > **Startup UX:** print 2–3 cheeky lines (random) + masked API key (first 3 + last 4).
    > **Flags:** `-v/--verbose`, `--version`, `-p <prompt>` (one‑shot UI; internal tool loop), `--yolo`, `--session <uuid>`.
    > **Chat & sessions:** interactive REPL with `/new` `/clear` `/status` `/exit`; chain with `previous_response_id` + `store:true`; **always include** the system prompt each turn; persist under `~/.swagent/<uuid>.json`.
    > **Tools (function calling):**
    >
    > * `run_bash(command, cwd?)` → prompt Y/n unless `--yolo`; execute with `bash -lc`; return `{stdout, stderr, exitCode}` (stringified JSON) via `tool_outputs` bound to the **same `call_id`**.
    > * `request_more_info(question)` → ask the user, then continue.
    > * `finish(summary)` → end and print summary.
    > **Per‑turn stats:** print `(in: N, out: M, total: T tokens, 0m 00s)` from `usage`.
    > **Self‑test (mandatory):**
    >
    > * **Startup:** print 2–3 cheeky lines (random), then the masked API key (first 3 + last 4). No mention of compiler flags or isolation modes.
    > * **Flags:** `-v/--verbose` (extra logs + HTTP status), `--version`, `-p <prompt>` (one‑shot to the user; internal tool loop), `--yolo` (auto‑approve tools), `--session <uuid>`.
    > * **Chat:** interactive REPL with `/new` `/clear` `/status` `/exit`. Maintain state via **`previous_response_id`** and **`store:true`**; **always** include the **system prompt** each turn.
    > * **Tools (function calling):**
    > 1. After generating code, **call `run_bash`** to run `swift build`.
    > 2. If tests exist, **call `run_bash`** to run `swift test`.
    > 3. **Call `run_bash`** to run:
    >
    > * `run_bash(command, cwd?)` → ask **Y/n** per call (Enter=Yes) unless `--yolo`. Run via `bash -lc`. Return `{stdout, stderr, exitCode}` bound to the same `tool_call_id`.
    > * `request_more_info(question)` → print question; wait for user input.
    > * `finish(summary)` → end; print summary.
    > * **Per‑turn stats:** print `(in: N, out: M, total: T tokens, 0m 00s)` using the **Responses API `usage`** and a monotonic timer.
    > * **Sessions:** persist under `~/.swagent/<uuid>.json`; `/status` shows masked key, token totals, and an **estimated** remaining context; on exit: *“To resume this session, call `swagent --session <uuid>`.”*
    > * **Engineering:** idiomatic Swift 6.2; strict concurrency (MainActor by default); state in `actor`s; DTOs `Sendable`; clean terminal text output; `swift test` with **Swift Testing**; `swift-format`/`SwiftLint` wired via scripts or SPM plugins.
    > * **Responses API details to follow precisely:** function tools + tool outputs, chaining via `previous_response_id`, `usage` tokens. ([OpenAI Platform][3])
    > * `swift run swagent --version`
    > * `swift run swagent -p "Echo hello"`
    > * `swift run swagent --yolo -p "Create hello.sh and run it"`
    > 4. On any failure, inspect `stderr`, fix, and retry.
    > **Responses API (use exactly this shape):** tools are **top‑level** (`type/name/description/parameters`); tool calls arrive as `function_call` items with `call_id` + `arguments` (JSON string); tool results go in `tool_outputs`; usage fields are `input_tokens`, `output_tokens`, `total_tokens`. Use `previous_response_id` for chaining and **re‑send** the system prompt each turn.
    > **Docs:** API Reference (Responses), Function Calling, Conversation State / previous_response_id, streaming/output_text, migration notes. ([OpenAI Platform][1])
    ---

    ## Snippets you can drop in
    ## 📎 Responses API crib sheet (drop right into your repo/readme)

    **Cheeky greetings helper**
    **Request (with tools):**

    ```swift
    enum Greetings {
    static let pool: [[String]] = [
    ["🎩 I code therefore I am.", "⚡ One prompt. One shot.", "🧰 Tabs, spaces, or chaos?"],
    ["🧪 If it compiles, we ship.", "🐚 Bashful? I’m not.", "📦 Got packages? I do."],
    ["🤖 Ship it?", "🔧 Small diffs, big wins.", "🧭 Point me at a repo."]
    ]
    static func random() -> [String] { pool.randomElement() ?? ["👋 Hey"] }
    ```json
    {
    "model": "gpt-5-codex",
    "instructions": "<SYSTEM PROMPT HERE>",
    "input": "<USER INPUT HERE>",
    "tools": [
    { "type":"function","name":"run_bash","description":"Run bash","parameters":{
    "type":"object","properties":{"command":{"type":"string"},"cwd":{"type":"string"}},
    "required":["command"]
    }},
    { "type":"function","name":"request_more_info","parameters":{
    "type":"object","properties":{"question":{"type":"string"}},"required":["question"]
    }},
    { "type":"function","name":"finish","parameters":{
    "type":"object","properties":{"summary":{"type":"string"}},"required":["summary"]
    }}
    ],
    "tool_choice": "auto",
    "store": true
    }
    ```

    **Tool schemas (Swift types → JSON)**

    ```swift
    struct RunBashArgs: Codable { let command: String; let cwd: String? }
    struct MoreInfoArgs: Codable { let question: String }
    struct FinishArgs: Codable { let summary: String }
    ```

    Use these to build `tools: [...]` for the Responses API request. ([OpenAI Platform][3])

    **Session file shape (`~/.swagent/<uuid>.json`)**
    **Response (snippet):**

    ```json
    {
    "id": "3B83C2A2-...-8F",
    "createdAt": "2025-09-30T19:12:03Z",
    "previous_response_id": "resp_abc123",
    "usage": { "input_tokens": 1820, "output_tokens": 980, "total_tokens": 2800 },
    "history": ["resp_abc123", "resp_def456"]
    "id": "resp_abc",
    "output": [
    { "type":"message", "role":"assistant",
    "content":[{ "type":"output_text", "text":"…" }] },
    { "type":"function_call", "call_id":"call_123",
    "name":"run_bash", "arguments":"{\"command\":\"swift build\"}" }
    ],
    "usage": { "input_tokens": 123, "output_tokens": 45, "total_tokens": 168 }
    }
    ```

    **Makefile mini**
    **Continue with tool output:**

    ```makefile
    fmt: ; swift-format --in-place --recursive Sources Tests
    lint: ; swiftlint
    test: ; swift test -v
    check: fmt lint test
    ```json
    {
    "model": "gpt-5-codex",
    "instructions": "<SYSTEM PROMPT HERE>",
    "previous_response_id": "resp_abc",
    "tool_outputs": [
    { "call_id":"call_123",
    "output":"{\"stdout\":\"…\",\"stderr\":\"\",\"exitCode\":0}" }
    ]
    }
    ```

    Formatter / linter docs. ([GitHub][7])
    Refs for each bit: Responses API reference, `previous_response_id`, function‑calling loop, `output_text`, `usage` fields. ([OpenAI Platform][1])

    ---

    ## Why the model will behave better with this setup
    ## 💬 Startup cheeky lines (pool)

    * **Richer acceptance checks** = clearer affordances for tool loops, approval prompts, and session continuity (what to do next is unambiguous).
    * **System prompt now encodes runtime (macOS 26)** and strict tool etiquette, so the assistant knows how to “play by the rules” in every turn.
    * **SPM‑level default isolation** handles the concurrency foot‑guns without cluttering runtime output. ([Swift.org][1])
    * “🎩 I code therefore I am.”
    * “⚡ One prompt. One shot. Make it count.”
    * “🧪 If it compiles, we ship. Mostly.”
    * “🐚 Bashful? I’m not.”
    * “🔧 Small diffs, big wins.”

    ---

    ## Sources

    * Swift 6.2 (default MainActor isolation & single‑threaded option). ([Swift.org][1])
    * SPM `SwiftSetting.defaultIsolation` docs (PackageDescription 6.2). ([Swift Documentation][9])
    * Swift Testing (toolchain framework). ([GitHub][6])
    * swift-configuration (env provider). ([GitHub][10])
    * ArgumentParser docs. ([Apple GitHub][2])
    * Responses API reference; function calling; conversation state & `previous_response_id`; usage tokens. ([OpenAI Platform][3])
    * swift-format; SwiftLint. ([GitHub][7])

    Want me to also push a tiny repo skeleton with the `Package.swift`, `CLI.swift`, `SessionStore` actor, and a `Swift Testing` smoke test so you can kick off Stage 1 instantly?
    Want me to fold these exact blocks into your Stage 1–5 “paste‑to‑build” prompts so you can run the workshop straight from slides?

    [1]: https://swift.org/blog/swift-6.2-released/?utm_source=chatgpt.com "Swift 6.2 Released"
    [2]: https://apple.github.io/swift-argument-parser/documentation/argumentparser/?utm_source=chatgpt.com "ArgumentParser | Documentation - Apple"
    [1]: https://platform.openai.com/docs/api-reference/responses "OpenAI Platform"
    [2]: https://platform.openai.com/docs/quickstart?utm_source=chatgpt.com "Developer quickstart - OpenAI API"
    [3]: https://platform.openai.com/docs/api-reference/responses?utm_source=chatgpt.com "API Reference"
    [4]: https://platform.openai.com/docs/guides/conversation-state?utm_source=chatgpt.com "Conversation state - OpenAI API"
    [5]: https://platform.openai.com/docs/guides/function-calling?utm_source=chatgpt.com "Function calling - OpenAI API"
    [6]: https://github.com/swiftlang/swift-testing?utm_source=chatgpt.com "swiftlang/swift-testing: A modern, expressive ..."
    [7]: https://github.com/swiftlang/swift-format?utm_source=chatgpt.com "Formatting technology for Swift source code"
    [8]: https://platform.openai.com/docs/api-reference/usage?utm_source=chatgpt.com "API Reference"
    [9]: https://docs.swift.org/swiftpm/documentation/packagedescription/swiftsetting/defaultisolation%28_%3A_%3A%29/?utm_source=chatgpt.com "defaultIsolation(_:_:)"
    [10]: https://github.com/apple/swift-configuration?utm_source=chatgpt.com "apple/swift-configuration: API package for reading ..."
    [4]: https://platform.openai.com/docs/guides/structured-outputs?utm_source=chatgpt.com "Structured model outputs - OpenAI API"
    [5]: https://platform.openai.com/docs/guides/migrate-to-responses?utm_source=chatgpt.com "Migrate to the Responses API"
    [6]: https://platform.openai.com/docs/guides/function-calling?utm_source=chatgpt.com "Function calling - OpenAI API"
    [7]: https://platform.openai.com/docs/guides/tools?utm_source=chatgpt.com "Using tools - OpenAI API"
    [8]: https://platform.openai.com/docs/guides/text?utm_source=chatgpt.com "Text generation - OpenAI API"
  6. steipete created this gist Sep 30, 2025.
    320 changes: 320 additions & 0 deletions swagent-spec.md
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    Perfect—let’s tune the plan so it’s workshop‑friendly, shows **a few cheeky lines** on startup, **doesn’t print compiler flags**, keeps **macOS 26** only in the **system prompt**, and **expands** the checks so the model + humans both have more to chew on.

    ---

    ## What changed (quick)

    * Startup prints **multiple cheeky lines** + masked API key; **no mention of Swift 6.2 or MainActor** in the output.
    * **System prompt** now explicitly contains **“Runtime: macOS 26 or later”** and is more detailed (pasted in full below).
    * **Stage acceptance checks** beefed up with explicit I/O, example transcripts, and file expectations.
    * **All‑in‑one (one‑go) build prompt** now embeds the **full system prompt**.

    > Build knobs you still apply in code: **Swift 6.2** + **default MainActor isolation** via SPM `SwiftSetting.defaultIsolation(MainActor.self)`; conversation chaining via **Responses API** with `previous_response_id`; **function tools** for finish/ask‑for‑info; and a **bash tool** with Y/n gating or `--yolo`. ([Swift.org][1])
    ---

    ## Stage plan (5 steps, updated + expanded checks)

    ### 1) “Hello, swagent” — minimal one‑shot

    **Build scope**

    * Swift 6.2; set default isolation at module level in **SPM**:

    ```swift
    // swift-tools-version: 6.2
    // ...
    .executableTarget(
    name: "swagent",
    // ...
    swiftSettings: [
    .defaultIsolation(MainActor.self) // SwiftPM 6.2
    ]
    )
    ```

    *Docs:* Swift 6.2 main‑actor default option; SPM `defaultIsolation`. ([Swift.org][1])
    * Deps: `swift-argument-parser` (CLI), `swift-configuration` (reads `OPENAI_API_KEY` from env). ([Apple GitHub][2])
    * Call **OpenAI Responses API** (`model: gpt-5-codex`) once; print the reply. Show token usage from `usage` + elapsed time. ([OpenAI Platform][3])

    **Runtime UX**

    * On launch, print **2–3 cheeky lines** (randomly sampled) + masked API key (`sk‑abc…def0`).
    * Flags: `--version`, `-v` (verbose HTTP codes + timings).

    **Cheeky lines pool (example)**

    ```
    • 🎩 “I code therefore I am. Hit me.”
    • 🧰 “Tabs, spaces, or chaos? Your call.”
    • ⚡ “One prompt. One shot. Make it count.”
    • 🧪 “If it compiles, we ship. Kidding. Mostly.”
    • 🐚 “Bashful? I’m not.”
    ```

    **Expanded checks**

    * **Env**: with key → shows masked key; without → prints clear error about missing `OPENAI_API_KEY` (no stacktrace).
    * **CLI**:

    * `swagent --version` → semantic version line only.
    * `swagent -v "What’s 2+2?"` → prints cheeky intro (2–3 lines), masked key, HTTP 200 in verbose log, model text, and a footer `(in: X, out: Y, total: Z tokens, 0m 01s)`.
    * **Failure paths**: network error surfaces as a single‑line diagnostic in `-v` mode; non‑`-v` shows brief “request failed (HTTP NNN)”.

    References for API, tokens, and arg parsing. ([OpenAI Platform][3])

    ---

    ### 2) “Sticky chat” — interactive REPL + one‑shot `-p`

    **Build scope**

    * Add REPL (loop until `/exit`).
    * Keep one‑shot via `-p "…"`.
    * Maintain conversation by passing **`previous_response_id`** each turn. **Always resend your system prompt** each request (instructions aren’t auto‑carried). ([OpenAI Platform][4])

    **Expanded checks**

    * **REPL basics**:

    * Start `swagent` → cheeky lines + masked key → prompt `›`.
    * Type `Hello` → model replies; prints per‑turn `(tokens, time)`.
    * **Commands**:

    * `/new` (alias `/clear`) → response chain reset; next call has **no** `previous_response_id`.
    * `/exit` → exits the process.
    * `/status` (preview, wired in Stage 5) → prints “not persisted yet” message in Stage 2.
    * **One‑shot**: `swagent -p "Summarize rust vs swift"` → one response, stats footer, exit.
    * **State**: verify the second turn includes **`previous_response_id`** of the first. (You’ll see longer `in:` tokens owing to chaining.) ([OpenAI Platform][4])

    ---

    ### 3) “Agent signals” — finish / ask‑for‑info tools

    **Build scope**

    * Add **two function tools** (Responses API `tools`):

    * `finish(summary: string)`
    * `request_more_info(question: string)`
    * Implement tool‑call loop: when a tool is called, send its **tool output** back (bound to the exact `tool_call_id`), then continue. ([OpenAI Platform][5])

    **Tool JSON schemas (sketch)**

    ```json
    {
    "type": "function",
    "name": "finish",
    "description": "Signal task completion with a short summary and next steps.",
    "parameters": { "type": "object", "properties": { "summary": { "type": "string" } }, "required": ["summary"] }
    }
    ```

    ```json
    {
    "type": "function",
    "name": "request_more_info",
    "description": "Ask the user for missing information to proceed.",
    "parameters": { "type": "object", "properties": { "question": { "type": "string" } }, "required": ["question"] }
    }
    ```

    **Expanded checks**

    * Prompt: “Draft a minimal README, ask me one clarifying question, then finish.”

    * Model calls `request_more_info` → CLI prints the question and waits for user input → you answer → model continues → model calls `finish` with a summary → CLI prints summary + stats and returns to prompt (REPL) or exits (`-p`).
    * **Verify**: every assistant tool call is followed by a matching **tool output** before continuing (this is required by function‑calling semantics). If you skip it, you’ll hit tool‑output errors. ([OpenAI Platform][5])

    ---

    ### 4) “Run commands” — bash tool with guardrails

    **Build scope**

    * Add `run_bash(command: string, cwd?: string)` tool:

    * On invocation, print the proposed command and ask **`Run? [Y/n]`** (Enter = Yes).
    * `--yolo` auto‑approves.
    * Execute with `bash -lc "<command>"`; capture `stdout`, `stderr`, `exitCode`; return as tool output.
    * `-p` mode: still **one‑shot to the user**, but the **agent may loop internally** across tools until it calls `finish` or `request_more_info`.

    **Expanded checks**

    * `swagent -p "Create hello.sh that prints hello, make it executable, run it"`

    * Shows planned commands, asks Y/n, runs, shows `stdout: hello`.
    * On failure (non‑zero exit), model sees `exitCode!=0` + `stderr` and retries.
    * `swagent --yolo -p "swift --version"` → executes without prompt; output returned to model; prints final message + stats.
    * **Audit**: ensure each tool call’s **tool output** uses the **same `tool_call_id`** field the model provided (Responses API requirement). ([OpenAI Platform][5])

    ---

    ### 5) “Sessions, polish, tests” — persistence + status + lint/format

    **Build scope**

    * Persist sessions under `~/.swagent/<uuid>.json` via an **actor** (async file I/O).
    * `/status` prints:

    * masked API key,
    * totals for **input/output/total tokens** this session,
    * **estimated context remaining** (based on model context limit and running total).
    * `--session <uuid>` resumes a saved chain.
    * On exit: print *“To resume this session, call `swagent --session <uuid>`.”*
    * Tests with **Swift Testing** (Xcode 26 includes it). ([GitHub][6])
    * Formatting/linting: **swift-format** + **SwiftLint** targets or scripts. ([GitHub][7])

    **Expanded checks**

    * **Persistence**:

    * Start chat, send two turns → exit → check `~/.swagent/<uuid>.json` exists and includes: latest `response_id`, cumulative `usage`, timestamps.
    * `swagent --session <uuid>` → prints greeting + “session loaded” note, then the REPL prompt. Next turn continues with `previous_response_id` from file. ([OpenAI Platform][4])
    * **/status** shows something like:

    ```
    Session: 3B83C2A2-…-8F
    API key: sk-abc…f789
    Tokens used: in=1,820 out=980 total=2,800
    Context headroom (est.): ~170k tokens left
    ```

    (Token counts from **Responses API `usage`**, context estimate uses model limit minus running input/output tokens; show it as an estimate.) ([OpenAI Platform][8])
    * **Tests**:

    * `CLITests`: `--version`, `-p`, `--yolo`, `--session`.
    * `SessionStoreTests`: save/load round‑trip; concurrent reads/writes guarded by the actor.
    * `ToolApprovalTests`: Y/n prompt default acceptance; `--yolo` bypass.
    * **Lint/format**: `make fmt lint` passes (no warnings on default rules).

    ---

    ## System prompt (paste verbatim)

    > **You are swagent**, a focused coding agent optimized for terminal workflows.
    > **Runtime:** **macOS 26 or later**.
    > **Mission:** Help the user build, run, and refine code and shell workflows efficiently.
    > **Behavior rules:**
    >
    > * Think step‑by‑step; propose small diffs; prefer minimal, working patches.
    > * Only run shell commands via the `run_bash` tool after clearly proposing what will run.
    > * If missing info, call `request_more_info(question)`.
    > * When done, call `finish(summary)` with a concise summary + next steps.
    > * Never print or exfiltrate secrets; avoid destructive commands unless explicitly asked.
    > * Keep answers **terminal‑friendly** and concise.
    > **Tools available:**
    >
    > 1. `run_bash(command: string, cwd?: string)` — execute a shell command and read its output.
    > 2. `request_more_info(question: string)` — ask the user for specifics and wait.
    > 3. `finish(summary: string)` — signal completion and stop.
    > **Conversation:** You are part of a chat. Treat each turn as a continuation. When the user uses one‑shot `-p`, you may internally loop tool calls until you either `finish` or you must `request_more_info`.
    *(Note: we keep OS here; we intentionally don’t print compiler flags or isolation mode at runtime.)*

    ---

    ## One‑go build prompt (full brief, **now includes the system prompt**)

    > **Project name:** `swagent`
    > **Environment:** Swift 6.2 with **default MainActor isolation** (via `.defaultIsolation(MainActor.self)` in SPM), **macOS host**.
    > **Dependencies:** `swift-argument-parser`, `apple/swift-configuration`; built‑in **Swift Testing**; plus **swift-format** and **SwiftLint**.
    > **System prompt to embed (verbatim):**
    > *[insert the “System prompt (paste verbatim)” block above]*
    > **Build & UX requirements:**
    >
    > * **Startup:** print 2–3 cheeky lines (random), then the masked API key (first 3 + last 4). No mention of compiler flags or isolation modes.
    > * **Flags:** `-v/--verbose` (extra logs + HTTP status), `--version`, `-p <prompt>` (one‑shot to the user; internal tool loop), `--yolo` (auto‑approve tools), `--session <uuid>`.
    > * **Chat:** interactive REPL with `/new` `/clear` `/status` `/exit`. Maintain state via **`previous_response_id`** and **`store:true`**; **always** include the **system prompt** each turn.
    > * **Tools (function calling):**
    >
    > * `run_bash(command, cwd?)` → ask **Y/n** per call (Enter=Yes) unless `--yolo`. Run via `bash -lc`. Return `{stdout, stderr, exitCode}` bound to the same `tool_call_id`.
    > * `request_more_info(question)` → print question; wait for user input.
    > * `finish(summary)` → end; print summary.
    > * **Per‑turn stats:** print `(in: N, out: M, total: T tokens, 0m 00s)` using the **Responses API `usage`** and a monotonic timer.
    > * **Sessions:** persist under `~/.swagent/<uuid>.json`; `/status` shows masked key, token totals, and an **estimated** remaining context; on exit: *“To resume this session, call `swagent --session <uuid>`.”*
    > * **Engineering:** idiomatic Swift 6.2; strict concurrency (MainActor by default); state in `actor`s; DTOs `Sendable`; clean terminal text output; `swift test` with **Swift Testing**; `swift-format`/`SwiftLint` wired via scripts or SPM plugins.
    > * **Responses API details to follow precisely:** function tools + tool outputs, chaining via `previous_response_id`, `usage` tokens. ([OpenAI Platform][3])
    ---

    ## Snippets you can drop in

    **Cheeky greetings helper**

    ```swift
    enum Greetings {
    static let pool: [[String]] = [
    ["🎩 I code therefore I am.", "⚡ One prompt. One shot.", "🧰 Tabs, spaces, or chaos?"],
    ["🧪 If it compiles, we ship.", "🐚 Bashful? I’m not.", "📦 Got packages? I do."],
    ["🤖 Ship it?", "🔧 Small diffs, big wins.", "🧭 Point me at a repo."]
    ]
    static func random() -> [String] { pool.randomElement() ?? ["👋 Hey"] }
    }
    ```

    **Tool schemas (Swift types → JSON)**

    ```swift
    struct RunBashArgs: Codable { let command: String; let cwd: String? }
    struct MoreInfoArgs: Codable { let question: String }
    struct FinishArgs: Codable { let summary: String }
    ```

    Use these to build `tools: [...]` for the Responses API request. ([OpenAI Platform][3])

    **Session file shape (`~/.swagent/<uuid>.json`)**

    ```json
    {
    "id": "3B83C2A2-...-8F",
    "createdAt": "2025-09-30T19:12:03Z",
    "previous_response_id": "resp_abc123",
    "usage": { "input_tokens": 1820, "output_tokens": 980, "total_tokens": 2800 },
    "history": ["resp_abc123", "resp_def456"]
    }
    ```

    **Makefile mini**

    ```makefile
    fmt: ; swift-format --in-place --recursive Sources Tests
    lint: ; swiftlint
    test: ; swift test -v
    check: fmt lint test
    ```

    Formatter / linter docs. ([GitHub][7])

    ---

    ## Why the model will behave better with this setup

    * **Richer acceptance checks** = clearer affordances for tool loops, approval prompts, and session continuity (what to do next is unambiguous).
    * **System prompt now encodes runtime (macOS 26)** and strict tool etiquette, so the assistant knows how to “play by the rules” in every turn.
    * **SPM‑level default isolation** handles the concurrency foot‑guns without cluttering runtime output. ([Swift.org][1])

    ---

    ## Sources

    * Swift 6.2 (default MainActor isolation & single‑threaded option). ([Swift.org][1])
    * SPM `SwiftSetting.defaultIsolation` docs (PackageDescription 6.2). ([Swift Documentation][9])
    * Swift Testing (toolchain framework). ([GitHub][6])
    * swift-configuration (env provider). ([GitHub][10])
    * ArgumentParser docs. ([Apple GitHub][2])
    * Responses API reference; function calling; conversation state & `previous_response_id`; usage tokens. ([OpenAI Platform][3])
    * swift-format; SwiftLint. ([GitHub][7])

    Want me to also push a tiny repo skeleton with the `Package.swift`, `CLI.swift`, `SessionStore` actor, and a `Swift Testing` smoke test so you can kick off Stage 1 instantly?

    [1]: https://swift.org/blog/swift-6.2-released/?utm_source=chatgpt.com "Swift 6.2 Released"
    [2]: https://apple.github.io/swift-argument-parser/documentation/argumentparser/?utm_source=chatgpt.com "ArgumentParser | Documentation - Apple"
    [3]: https://platform.openai.com/docs/api-reference/responses?utm_source=chatgpt.com "API Reference"
    [4]: https://platform.openai.com/docs/guides/conversation-state?utm_source=chatgpt.com "Conversation state - OpenAI API"
    [5]: https://platform.openai.com/docs/guides/function-calling?utm_source=chatgpt.com "Function calling - OpenAI API"
    [6]: https://github.com/swiftlang/swift-testing?utm_source=chatgpt.com "swiftlang/swift-testing: A modern, expressive ..."
    [7]: https://github.com/swiftlang/swift-format?utm_source=chatgpt.com "Formatting technology for Swift source code"
    [8]: https://platform.openai.com/docs/api-reference/usage?utm_source=chatgpt.com "API Reference"
    [9]: https://docs.swift.org/swiftpm/documentation/packagedescription/swiftsetting/defaultisolation%28_%3A_%3A%29/?utm_source=chatgpt.com "defaultIsolation(_:_:)"
    [10]: https://github.com/apple/swift-configuration?utm_source=chatgpt.com "apple/swift-configuration: API package for reading ..."