Individual skill

harness-audit

Score a project's agent harness across 5 subsystems (Instructions / State / Verification / Scope / Lifecycle), identify the bottleneck, and produce a prioritized improvement plan. Use when assessing if a project is ready to graduate to [LONG-RUN] status, when an agent keeps failing despite good models, or when adopting our stack on a new codebase. Do NOT use to design or build a new harness from scratch — this only scores an existing one; for greenfield harness/agent architecture use harness-design (or agent-harness-design).

skills/operational/harness-audit/SKILL.md

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Last checked: Nov 7, 2026

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Repository stars (not skill ratings): 214
Repository last updated: Nov 5, 2026
License: MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

ai-agents Repository topic
claude Repository topic
claude-code Repository topic
llm Repository topic
machine-learning Repository topic
prompt-engineering Repository topic
skills Repository topic
mcp Repository topic
agent-harness Repository topic
harness Repository topic
engineering Derived category
design Derived category
security Derived category

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references/scoring-rubric.mddoc · 7,882 bytes

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# Harness Audit

Trigger on phrases like: "audit my harness", "evaluate my agent setup", "score my CLAUDE.md", "is my project ready for long-run", "5-subsystem assessment", "what's missing from my project setup", "/harness-audit". Run proactively when joining an unfamiliar codebase that has agent artifacts (CLAUDE.md, .claude/, AGENTS.md) but obvious gaps. Skip for single-file scripts and pure exploration.

Score a project's agent harness across five subsystems and tell the user which evidenced bottleneck to address first. Distinguish an artifact's presence from demonstrated behavior; never present metadata alone as runtime proof.

**Source**: Five-subsystem framework adapted from [Learn Harness Engineering](https://walkinglabs.github.io/learn-harness-engineering/) (walkinglabs, MIT). Adapted to our concrete stack: CLAUDE.md, `.claude/rules/`, PROBLEMS.md, `feature_list.json`, `init.sh`, hooks, handoffs, chronicles.

## What This Skill Does

Given a project directory, produces a scorecard like this. This example assumes
`project-xyz` delivers features across sessions and uses pull requests:

```