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claude-skills/docs/commands/cs-grade.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-grade — Slash Command for AI Coding Agents Phase 3 — the bounded grade→iterate loop. Define a CMA outcome (required rubric, max_iterations 1..20), read each grader verdict, decide the next. Slash command for Claude Code, Codex CLI, Gemini CLI.

/cs-grade

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

Run the grade-iterate skill.

$ARGUMENTS

Steps

  1. python3 agent-launcher/skills/grade-iterate/scripts/outcome_builder.py --sheet ./my-agent/build-sheet.json --max-iterations 5 --out ./my-agent/payloads/outcome.json — rubric required; send as a user.define_outcome event.
  2. On each verdict: python3 agent-launcher/skills/grade-iterate/scripts/verdict_reader.py --result ./my-agent/last-verdict.json → SHIP / SHARPEN / ESCALATE / RESUME. Each iteration must move ≥1 rubric line fail→pass.
  3. Once a version passes: python3 agent-launcher/skills/grade-iterate/scripts/eval_scaffold.py --sheet ./my-agent/build-sheet.json --out ./my-agent/eval.json — held-back cases in parallel (≤25 threads).
  4. Decide: ship v0, or goal_state.py set --phase run-without-you.

Bounded loops only. Read the verdict before acting. Held-back cases stay held back.