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github/awesome-copilot/skills/harness-engineering/SKILL.md

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.

Source repository stars
37,126
Declared platforms
0
Static risk flags
1
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

Harness engineering turns repeated coding-agent mistakes into durable repository artifacts:

Best for

  • 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.

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/github/awesome-copilot --skill "skills/harness-engineering"
Safe inspection promptEditorial

Inspect the Agent Skill "harness-engineering" from https://github.com/github/awesome-copilot/blob/9933dcad5be5caeb288cebcd370eeeb2fc2f1685/skills/harness-engineering/SKILL.md at commit 9933dcad5be5caeb288cebcd370eeeb2fc2f1685. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Adoption Workflow

    1. Choose the harness surface that fits the target repository. 2. Write target-specific agent instructions. 3. Add enforceable checks for high-value rules. 4. Record failure memory for high-risk or recurring failures. 5. Add drift checks for guidance that can silently become sta…

    Choose the harness surface that fits the target repository.Write target-specific agent instructions.Add enforceable checks for high-value rules.
  2. 02

    2. Write Agent Instructions

    Agent instructions should be concrete and operational. Include:

    project purpose and major ownership boundariessetup, test, lint, build, and verification commandspackage manager and dependency rules
  3. 03

    Review Workflow

    When asked to review a harness change, take an opposing perspective. Look for:

    generic rules copied without evidence from the target repositoryduplicate or conflicting instruction filesbroad checks that are likely to fail on valid changes
  4. 04

    Core Principles

    Treat the target repository as the source of truth.

    Treat the target repository as the source of truth.Inspect before editing. Preserve the existing stack, package manager, CI,Add the smallest useful harness. Prefer updating existing files over adding
  5. 05

    Discovery

    Before proposing or making harness changes, inspect the repository for existing rules and evidence.

    README.mdAGENTS.md.github/copilot-instructions.md

Permission review

Static risk signals and limitations

Reads files

low · line 39

The documentation asks the agent to read local files, directories, or repositories.

Before proposing or making harness changes, inspect the repository for existing

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score81/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars37,126SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
github/awesome-copilot
Skill path
skills/harness-engineering/SKILL.md
Commit
9933dcad5be5caeb288cebcd370eeeb2fc2f1685
License
MIT
Collected
2026-07-28
Default branch
main
View the original SKILL.md

Harness Engineering

Harness engineering turns repeated coding-agent mistakes into durable repository artifacts:

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 would be brittle or misleading.
  • Record high-risk failures that should not recur, and name the check or review point that catches recurrence.
  • Do not copy generic templates blindly. Adapt every artifact to real evidence in the target repository.

Discovery

Before proposing or making harness changes, inspect the repository for existing rules and evidence.

Read these files and folders when they exist:

  • README.md
  • AGENTS.md
  • .github/copilot-instructions.md
  • .github/instructions/
  • .github/workflows/
  • CONTRIBUTING.md
  • package manifests such as package.json, pyproject.toml, go.mod, Cargo.toml, pom.xml, or build.gradle
  • existing docs under docs/
  • existing scripts under scripts/
  • existing tests and CI checks

Then summarize:

  • stack, package manager, and entry points
  • existing development and verification commands
  • current agent instructions or repository conventions
  • known failures, incidents, flaky paths, or repeated review comments
  • gaps where project rules are not enforced

Adoption Workflow

Follow this sequence:

  1. Choose the harness surface that fits the target repository.
  2. Write target-specific agent instructions.
  3. Add enforceable checks for high-value rules.
  4. Record failure memory for high-risk or recurring failures.
  5. Add drift checks for guidance that can silently become stale.
  6. Report the adoption with evidence, assumptions, and follow-up.

1. Choose the Harness Surface

Pick only the surfaces that fit the target repository:

NeedPreferred artifact
Always-on agent behaviorAGENTS.md or .github/copilot-instructions.md
File-scoped guidance.github/instructions/*.instructions.md
Recurring project checksscripts/check_*.py, shell scripts, or package scripts
CI enforcementexisting workflow files or a small new workflow
Known failuresdocs/failures/*.md
Architecture or process decisionsdocs/decisions/*.md
Adoption evidencedocs/harness/adoption-report.md or similar

If the repository already has an equivalent location, update it instead of creating a parallel system.

2. Write Agent Instructions

Agent instructions should be concrete and operational. Include:

  • project purpose and major ownership boundaries
  • setup, test, lint, build, and verification commands
  • package manager and dependency rules
  • safe editing rules, generated file rules, and forbidden paths
  • testing expectations for changed code
  • PR and commit conventions if the repo has them
  • how to record new failures or decisions

Avoid broad personality guidance, generic best practices, and rules that cannot be checked or reviewed.

3. Add Enforceable Checks

Convert high-value rules into checks. Good harness checks are:

  • narrow enough to avoid false positives
  • fast enough to run locally and in CI
  • named clearly so agents can run them before finishing
  • documented with the rule they protect

Examples:

Rule: Do not edit generated API clients.
Check: script scans diffs for generated paths and fails with a clear message.

Rule: Every failure memory note names a regression check.
Check: script validates docs/failures/*.md for a "Detection" section.

Rule: Profile docs and templates must stay aligned.
Check: test compares profile README files to expected template files.

4. Record Failure Memory

Record failures when they are user-visible, high-risk, or likely to recur. Use a new file under docs/failures/ unless an existing note already covers the same root cause.

Recommended structure:

# Short Failure Title

## Summary

What failed, who saw it, and why it matters.

## Root Cause

The technical or process cause. Avoid blame.

## Prevention

Instruction, test, drift check, CI gate, fixture, or manual review point that
prevents or detects recurrence.

## Evidence

Links to issue, PR, test, log, command output, or file paths.

If no automated check is practical, record the manual review point and why automation would be unsafe or misleading.

5. Add Drift Checks

Use drift checks for guidance that can silently become stale. Common examples:

  • docs mention commands that no longer exist
  • profile snippets and generated examples diverge
  • failure notes omit regression checks
  • decision records are missing for structural changes
  • CI references stale scripts or package commands

Prefer small scripts using the repository's existing language. If the repo has no scripting convention, Python with only the standard library is a portable default.

6. Report the Adoption

Finish substantial harness work with an adoption report that includes:

  • files changed
  • rules added or updated
  • checks added or reused
  • commands run and results
  • assumptions and manual follow-up
  • failure memory created or intentionally skipped
  • how effectiveness will be measured

Review Workflow

When asked to review a harness change, take an opposing perspective. Look for:

  • generic rules copied without evidence from the target repository
  • duplicate or conflicting instruction files
  • broad checks that are likely to fail on valid changes
  • unenforced high-risk rules
  • missing failure memory for repeated mistakes or runtime failures
  • generated docs not refreshed after source changes
  • CI gates that do not run the relevant checks
  • target repository conventions being overwritten by harness defaults

Report findings first, ordered by severity, with file and line references when available. Do not modify files during a review unless the user explicitly asks for fixes.

Output Contract

Before finishing harness adoption work, verify:

  • the target repository was inspected before edits
  • new guidance is specific to the target repository
  • changed checks can be run locally or have a documented manual substitute
  • failure memory was recorded when required, or the final response explains why it was skipped
  • generated docs or indexes are refreshed
  • the final report names every command run and its result

Optional Reference

The prompt-first workflow in https://github.com/baskduf/harness-starter-kit is a reference implementation of these ideas. Use it as reference material only when the user asks for it or when the repository already includes it. The target repository remains the source of truth.

Alternatives

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