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jubscodesjubscodes/harness-doctor/SKILL.md

harness-doctor

Skill9 starsChanged 5 months agoMITView on GitHub

Use when evaluating a repository's Claude Code harness setup — CLAUDE.md, skills, guides/sensors, hooks, memory — to surface good practices, gaps, and prioritized fixes. Triggers when the user asks to audit their agent setup, "is my harness any good", "review my CLAUDE.md / skills", grade a repo's Claude Code config, or onboard a project to agents well.

5 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions5 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 5

    1. PromptPartner/agentsmith★ 173same name
    2. oeftimie/vv-claude-harness★ 20same name
    3. Mark-Life/agent-skills★ 4same name
    4. MrBogomips/agentic-harness★ 1same name
    5. thefiredev-cloud/meshvault-harness★ 0same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 0 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Sensors: test setup, linter/formatter config, type-checker, CI (.github/workflows/).

    line 23
  2. Very specific:

    Read references/checklist.md (the criteria) and references/principles.md (the *why* + sources) now, and score each dimension against them.

    line 30

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Harness Doctor

Audit a repository's agent harness — everything wrapped around the model (the contract, skills, guides, sensors, hooks, memory) — and report what's good, what's missing, and what to fix first.

Framing: Agent = Model + Harness. Guides steer before the agent acts (feedforward); sensors check after (feedback). You need both. (Böckeler, Harness Engineering, martinfowler.com.)

Process

1. Scan (read, don't guess)

Run scripts/scan.sh [repo-dir] first — a fast, deterministic inventory (contract · skills · sensors · hooks · memory). Then read what it can't judge — skill descriptions, CLAUDE.md content. Look for:

  • CLAUDE.md (also AGENTS.md, .cursor/rules) — the always-on contract
  • .claude/skills/*/SKILL.md — expertise
  • .claude/commands/, .claude/agents/, .claude/hooks/, .claude/settings*.json, .mcp.json, rules/
  • Sensors: test setup, linter/formatter config, type-checker, CI (.github/workflows/); is it computational (cheap/deterministic) or only inferential?
  • Memory & state: MEMORY.md, decision/progress logs, ADRs, a STATE.md/plan for long tasks
  • Improvement loop: skill evals, a learnings log, drift scans — does the harness get better when it fails?

For a large repo, spawn an Explore subagent to map it so you don't bloat your context.

2. Evaluate

Read references/checklist.md (the criteria) and references/principles.md (the why + sources) now, and score each dimension against them. Mark every finding ✓ good · ⚠ weak · ✗ missing, and tag each fix [cheap] (deterministic, do first) or [deeper].

3. Report (scannable, in the terminal)

  • Scorecard — one line per dimension: Contract · Skills · Guides · Sensors · Enforcement · Memory & State · Improvement loop
  • ✓ Strengths — what's already good (keep doing)
  • ⚠ / ✗ Gaps — each with a one-line concrete fix, ordered cheapest-deterministic first ("start cheap")
  • Top 3 next moves

4. Offer to fix

After the report, ask which fixes to apply — don't edit unprompted. When approved, make the change and show a diff. Typical fixes: scaffold a CLAUDE.md contract, rewrite a skill description to WHEN-not-WHAT, split a bloated CLAUDE.md into .claude/rules/, add a pre-commit secret/lint hook, wire a test/lint command in. Never weaken a check to make something pass.

Principles to judge against

  • Guides + sensors, before + after — flag feedforward-only (rules, never verified) and feedback-only (checks, no guidance).
  • A rule is only hard if a hook blocks it — prose is a request, a PreToolUse hook is enforcement.
  • Keep CLAUDE.md lean (< ~200 lines) — how-to belongs in skills/rules, not the contract.
  • Right tool for the job — flag misplacements (the skill/command/subagent/hook/MCP map is in references/checklist.md).
  • Start cheap — prefer fast deterministic controls (lint, tests, type-check) before slow/inferential ones (LLM-as-judge).

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free