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claude-skills/docs/commands/cs-harness.md
Claude abd9c9d8de
docs(site): generate agent-launcher pages (18th domain) + nav 
generate-docs.py learns the agent-launcher domain (5 hardcoded maps extended);
regenerated docs tree: 343 skill pages / 96 agent pages / 122 command pages
(561 total). mkdocs.yml nav gains the Agent Launcher skill section (7 pages),
4 cs-agent-* agent entries, and 8 /cs:* command entries; all nav targets verified
to exist.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012FwXG6TqCXKZQvF4iD69cv
2026-08-24 17:26:12 +00:00

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title description
/cs-harness — Slash Command for AI Coding Agents Compile a goal into a verified agent-harness loop for a domain and drive it to close — /cs:harness <domain> <goal>. Slash command for Claude Code, Codex CLI, Gemini CLI.

/cs-harness

:material-console: Slash Command :material-github: Source

Parse $ARGUMENTS: the first token is the domain (one of the 18 manifest names under engineering/agent-harness/skills/agent-harness/assets/harnesses/); the rest is the goal. If the domain token doesn't match a manifest file, list the available manifests and ask.

Sequence (gates are blocking — never skip forward)

  1. Compile — python3 engineering/agent-harness/skills/agent-harness/scripts/goal_compiler.py --goal "<goal>" --manifest engineering/agent-harness/skills/agent-harness/assets/harnesses/<domain>.json --out .agent-harness/plan.json
    • Exit 3: relay the forcing questions to the user one at a time (recommended answer first), then recompile with the enriched goal. Do not proceed on a vague goal.
    • Exit 4: show nearest_candidates, ask whether to switch domain or refine the goal.
  2. Review the plan with the user — show tasks, verifications, and caps. Confirm before initializing: this is the only approval gate in the loop.
  3. Init — python3 .../scripts/loop_controller.py init --plan .agent-harness/plan.json --state .agent-harness/state.json
  4. Drive — repeat: next → execute the task per its skill's SKILL.md → record → verify. For long goals, spawn the harness-runner agent per task instead of executing inline, one at a time (writes stay serialized).
  5. On exit 2 or 5 — stop, show status and the failing evidence; the user decides: fix and continue, waive with a reason, or abandon.
  6. Close — close --state .agent-harness/state.json; paste the handoff block (tasks, statuses, evidence, waivers) as the deliverable summary.

Rules

  • Never edit checks, manifests, or the plan mid-loop to make verification pass.
  • Never report an exhausted budget as success.
  • .agent-harness/ is git-ignorable working state; the handoff block is the record.