mirror of
https://github.com/alirezarezvani/claude-skills.git
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- check_paths.py: fix two unresolvable shutdown_checklist.md references in cs-deep-work agent/command (correct ../skills/ prefix) - meetings SKILL.md: add genuine intake/iteration/close-out discipline (clarify-the-decision intake, re-run-until-fit stop condition, owner+date completion check) -> manifest signals now 5/5, checklist still PASS at 97 lines - productivity harness manifest regenerated Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TQLKzYb1bR2LYqwYUupm5f |
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| .. | ||
| .claude-plugin | ||
| agents | ||
| commands | ||
| skills/agent-harness | ||
| README.md | ||
agent-harness
Turn any domain folder of this repo into a bounded agentic loop: pick up a goal, compile it into tasks with machine-run verification, execute, verify, retry with caps, escalate to a human when budgets exhaust, and close only when everything is verified.
GOAL → goal_compiler → PLAN → loop_controller: [execute → verify]* → CLOSE
↑ retry ≤ caps, changed approach
└ ESCALATE — never fake success
What ships
| Piece | Purpose |
|---|---|
scripts/harness_manifest_builder.py |
Scan a domain folder → manifest.v1 JSON (skills, tools, checks, agentic signals) |
scripts/goal_compiler.py |
Goal + manifest → plan.v1 task plan; refuses vague goals (exit 3, forcing questions) |
scripts/loop_controller.py |
init/next/record/verify/close/status state machine; controller runs checks itself |
assets/harnesses/*.json |
18 committed per-domain manifests (regenerable, diff-stable) |
assets/harness_manifest.schema.json |
Manifest schema |
references/ |
Agentic-loop canon, verification discipline, domain-harness design (cited) |
agents/harness-runner.md |
Stateless one-task-per-invocation executor |
commands/cs-harness.md |
/cs:harness <domain> <goal> end-to-end driver |
All tools are stdlib-only, pass --help and --sample, and emit JSON.
Design lineage
Anthropic's long-running-agents harness (feature-list + stateless shifts), verifier's law,
SWE-agent's environment-feedback lesson, Ralph-loop fresh-context iteration, Cognition's
serialize-writers rule, and this repo's own tc-tracker / autoresearch locked-evaluator /
loop-library stop-state primitives. See skills/agent-harness/references/.