chore: publish from staged

docs/README.skills.md

@@ -204,6 +204,7 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to
 | [gtm-positioning-strategy](../skills/gtm-positioning-strategy/SKILL.md)<br />`gh skills install github/awesome-copilot gtm-positioning-strategy` | Find and own a defensible market position. Use when messaging sounds like competitors, conversion is weak despite awareness, repositioning a product, or testing positioning claims. Includes Crawl-Walk-Run rollout methodology and the word change that improved enterprise deal progression. | None |
 | [gtm-product-led-growth](../skills/gtm-product-led-growth/SKILL.md)<br />`gh skills install github/awesome-copilot gtm-product-led-growth` | Build self-serve acquisition and expansion motions. Use when deciding PLG vs sales-led, optimizing activation, driving freemium conversion, building growth equations, or recognizing when product complexity demands human touch. Includes the parallel test where sales-led won 10x on revenue. | None |
 | [gtm-technical-product-pricing](../skills/gtm-technical-product-pricing/SKILL.md)<br />`gh skills install github/awesome-copilot gtm-technical-product-pricing` | Pricing strategy for technical products. Use when choosing usage-based vs seat-based, designing freemium thresholds, structuring enterprise pricing conversations, deciding when to raise prices, or using price as a positioning signal. | None |
+| [harness-engineering](../skills/harness-engineering/SKILL.md)<br />`gh skills install github/awesome-copilot 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. | None |
 | [image-annotations](../skills/image-annotations/SKILL.md)<br />`gh skills install github/awesome-copilot image-annotations` | Annotate screenshots, diagrams, and images with callout rectangles, arrows, labels, and color-coded highlights using PIL. Includes rules for animated GIF annotations with timing and pacing. | None |
 | [image-manipulation-image-magick](../skills/image-manipulation-image-magick/SKILL.md)<br />`gh skills install github/awesome-copilot image-manipulation-image-magick` | Process and manipulate images using ImageMagick. Supports resizing, format conversion, batch processing, and retrieving image metadata. Use when working with images, creating thumbnails, resizing wallpapers, or performing batch image operations. | None |
 | [impediment-prioritization](../skills/impediment-prioritization/SKILL.md)<br />`gh skills install github/awesome-copilot impediment-prioritization` | Ranks any list of impediments and their countermeasures using a value-stream scoring model (ROI, Cost to Implement, Ease of Deployment, Risk Factor) and a fixed prioritization formula. Use when someone asks to prioritize, rank, sequence, or triage impediments, countermeasures, remediation items, risks, findings, gaps, action items, or backlog entries; or mentions value-stream prioritization, A3 / lean countermeasure ranking, ROI vs. effort scoring, or building a remediation / improvement backlog. Works with GHQR findings, audit results, retrospective action items, risk registers, architecture review gaps, or any free-form `{impediment, countermeasure}` list. | `references/scoring-rubric.md` |

skills/harness-engineering/SKILL.md

@@ -0,0 +1,227 @@
+---
+name: harness-engineering
+description: '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.'
+---
+
+# 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 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:
+
+| Need | Preferred artifact |
+| --- | --- |
+| Always-on agent behavior | `AGENTS.md` or `.github/copilot-instructions.md` |
+| File-scoped guidance | `.github/instructions/*.instructions.md` |
+| Recurring project checks | `scripts/check_*.py`, shell scripts, or package scripts |
+| CI enforcement | existing workflow files or a small new workflow |
+| Known failures | `docs/failures/*.md` |
+| Architecture or process decisions | `docs/decisions/*.md` |
+| Adoption evidence | `docs/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:
+
+```text
+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:
+
+```markdown
+# 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.