Agent skill · AI & Agents

harness-engineering

Adopt repository-level harness engineering for coding agents. Use when a user wants to prevent repeated AI coding-agent mistakes by turning failures into durable instructions, drift checks, regression tests, failure memory, and adoption reports tailored to the target repository.

GitHub68,948★ · +463/wk · 2 repos on radarProfile →
copilotMIT
Install
npx skills add github/awesome-copilot --skill harness-engineering --agent copilot

Same command for any agent — swap --agent for claude-code, codex, cursor.

Facts
Files in the skill folder: 1
SKILL.md size: 8 KB
Bundled scripts: none
Path: skills/harness-engineering/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 37,432 · +281 this week
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Harness Engineering Harness engineering turns repeated coding-agent mistakes into durable repository artifacts: ```text Harness = Instructions + Constraints + Feedback + Memory + Evaluation + Governance ``` Use this skill when the user asks to: - make a repository more reliable for GitHub Copilot or other coding agents - add durable agent instructions, repository rules, or guardrails - prevent repeated AI coding-agent mistakes - record known failure paths and the checks that prevent recurrence - add lightweight drift checks for project rules - review, refresh, or update an existing agent harness Do not use this skill for ordinary feature implementation unless the user asks to improve the repository's agent operating environment. ## Core Principles - Treat the target repository as the source of truth. - Inspect before editing. Preserve the existing stack, package manager, CI, docs, naming, and architecture. - Add the smallest useful harness. Prefer updating existing files over adding duplicate guidance. - Make important rules enforceable where practical through tests, linters, type checks, CI, pre-commit hooks, or drift scripts. - Use manual review points only when automation woul

What's inside
Steps it walks through
  1. Core Principles
  2. Discovery
  3. Adoption Workflow
  4. 1. Choose the Harness Surface
  5. 2. Write Agent Instructions
  6. 3. Add Enforceable Checks
  7. 4. Record Failure Memory
  8. 5. Add Drift Checks
  9. 6. Report the Adoption
  10. Review Workflow
  11. Output Contract
  12. Optional Reference
More from awesome-copilot
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About this skill
What does the harness-engineering skill do?

Adopt repository-level harness engineering for coding agents. Use when a user wants to prevent repeated AI coding-agent mistakes by turning failures into durable instructions, drift checks, regression tests, failure memory, and adoption reports tailored to the target repository.

How do I install it?

Run `npx skills add github/awesome-copilot --skill harness-engineering --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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