# Harness Doctor

> 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.

- **Type:** Skill
- **Install:** `agentstack add skill-jubscodes-harness-doctor-harness-doctor`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [jubscodes](https://agentstack.voostack.com/s/jubscodes)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [jubscodes](https://github.com/jubscodes)
- **Source:** https://github.com/jubscodes/harness-doctor

## Install

```sh
agentstack add skill-jubscodes-harness-doctor-harness-doctor
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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).

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [jubscodes](https://github.com/jubscodes)
- **Source:** [jubscodes/harness-doctor](https://github.com/jubscodes/harness-doctor)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-jubscodes-harness-doctor-harness-doctor
- Seller: https://agentstack.voostack.com/s/jubscodes
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.