agent-launcher-orchestrator

# agent-launcher — Domain Orchestrator Every session starts with a **goal** — one sentence for one CMA. This orchestrator reads that goal, routes to the right phase, and compiles the goal into a **loop or a workflow**. Heavy intake stays in the forked context; the parent gets a digest. Inspired by Anthropic's `launch-your-agent` reference skill (Apache-2.0). This is an independent re-implementation; CMA semantics come from [`../../references/cma-primitives.md`](../../references/cma-primitives.md). ## The through-line: the session goal State lives at `./my-agent/goal.json` (the user's folder). Manage it with `goal_state.py` (init / set / status / advance) — it also backs the `/cs:goal` command and the opt-in `SessionStart` hook. The goal's `phase` selects the lane; the phase + recurrence selects the loop shape. ## Routing (deterministic) Run the router, then act on its exit code: ```bash python3 scripts/goal_router.py --out-dir ./my-agent # exit 0 ROUTE -> fork to the named phase sub-skill # exit 3 ASK -> ask the one printed forcing question, then re-route # exit 4 REFUSE -> goal too vague; get one sentence, then re-route ``` | Lane (phase) | Sub-skill | Loop/workflow | |---|---|---| | interview | `interview` | single-pass workflow | | stage-launch | `stage-launch` | single-pass workflow | | grade-iterate | `grade-iterate` | **bounded grade→iterate loop** | | run-without-you | `run-without-you` | **recurring cron deployment loop** | | wrap-up | `wrap-up` | — | ## Compile the loop ```bash python3 scripts/loop_compiler.py \ --out-dir ./my-agent --max-iterations 5 --cron "0 9 * * *" --timezone Europe/Berlin --nest-outcome ``` `loop_compiler.py` emits `plan.v1`: `single-pass`, `grade-iterate` (always with a `max_iterations` cap 1..20), or `cron-loop` (optionally nesting a self-grading outcome per firing). See [`../../references/loops-and-workflows.md`](../../references/loops-and-workflows.md). ## Pre-flight gates (hard refusals) 1. **No goal set.** If `goal.json` is missing, run `goal_state.py init --goal "..."` first. The orchestrator does not guess a goal. 2. **Goal too vague.** Router exit 4 — get one sentence naming the one job before routing. Never route on under-3-word goals. 3. **Never make API calls.** Emit BYOK curl; the user runs it with their own `$ANTHROPIC_API_KEY`. No script in this plugin touches the network. 4. **Never print the key.** Launch scripts read the key from the environment. ## Hand-off contract After routing, fork to the sub-skill with: the goal string, `agent_name`, `out_dir` (`./my-agent`), and the compiled `plan.v1`. When the sub-skill returns, `goal_state.py advance` moves the phase and the parent gets a ≤100-word digest (phase done, artifact paths, loop shape, one next step). ## Forcing-question library (walk one at a time; recommend + cite) 1. **"What one job should this agent do end-to-end?"** — *Recommend:* the single most repeated task. *Cite:* interview-to-config.md (six intake slots). Refuse to route a two-job goal; split into two `./my-agent-*/` folders. 2. **"What kicks it off — you ask it, an event, or a schedule?"** — *Recommend:* on-demand for v0, schedule as the Phase-4 upgrade. *Cite:* loops-and-workflows.md. 3. **"How would you grade a good run?"** — *Recommend:* 3–5 rubric lines grounded in the output. *Cite:* cma-primitives.md (outcomes; rubric required). 4. **"Is a real integration ready, or do we mock it in v0?"** — *Recommend:* mock with a schema-true custom tool; wire the MCP server as v1. *Cite:* interview-to-config.md. 5. **"Should run #10 be smarter than run #1?"** — *Recommend:* attach a memory store only if yes; else skip it. *Cite:* cma-primitives.md (memory limits + injection risk). ## Tools - `scripts/goal_state.py` — own `goal.json` (init/set/status/advance). - `scripts/goal_router.py` — goal → lane (exit 0 route / 3 ask / 4 refuse). - `scripts/loop_compiler.py` — goal+phase → `plan.v1` execution shape.