harness-setup

name	harness-setup
version	1.1.0
description	[Quality] Use when setting up an agent quality harness with feedforward guides and feedback sensors.

[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set in_progress when step starts, set completed when step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.

Quick Summary

Goal: Wire every feedforward guide and feedback sensor into the greenfield project so all later AI coding agents operate with maximum guidance and self-correct against quality gates BEFORE human review — raising first-attempt quality and catching defects at the earliest, cheapest stage.

Summary:

• BLOCK on the /linter-setup prerequisite first — computational sensors (linters, hooks, CI gates) MUST exist before any phase runs; this skill never installs them itself.
• Walk phases A→F as a hard barrier sequence: detect stack → author feedforward guides (CLAUDE.md conventions, anti-patterns, pattern catalog) → confirm computational sensors → wire inferential review skills to lifecycle gates → define behaviour/test strategy → emit inventory.
• Treat every feedforward-guide and sensor choice as AskUserQuestion-gated — never auto-decide content, because harness conventions bind every future agent and silent choices propagate.
• Write .ai/workspace/harness/harness-inventory.md incrementally (append per phase, not held in memory), keeping it a living document updated as new sensors are added.

Produces:

• Feedforward guides: CLAUDE.md/AGENTS.md conventions, architecture docs, pattern catalogs, skill activation rules
• Computational feedback sensors: configured via /linter-setup (linters, formatters, pre-commit hooks, CI gates)
• Inferential feedback sensors: AI review skills wired to lifecycle stages
• Harness inventory: .ai/workspace/harness/harness-inventory.md

When invoked: After /scaffold + /linter-setup in greenfield workflow. Assumes scaffolding complete.

Does NOT do: Install linters or configure formatters — that is /linter-setup's responsibility.

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Activation Guards

Check 1 — Linter-setup prerequisite (BLOCK if missing): Before running any phases, verify /linter-setup completed by checking for:

• Linter config file at project root (e.g., .eslintrc, pyproject.toml, .editorconfig)
• Pre-commit hook config (e.g., .husky/, .pre-commit-config.yaml)
• CI quality gate definition

If any missing → AskUserQuestion: "/linter-setup appears incomplete. Computational feedback sensors must be in place before harness setup. Run /linter-setup first, then return here?" BLOCK Phase A/B/C/D/E until linter-setup verification passes.

Check 2 — Existing harness inventory: Check for .ai/workspace/harness/harness-inventory.md

• If found → AskUserQuestion: "Harness inventory already exists — re-run to enhance existing harness, or skip?"
• Proceed even when CLAUDE.md/AGENTS.md present — those are feedforward guides this skill may enhance, NEVER signals to skip

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Phase A — Stack Detection

Read from: plan.md frontmatter → architecture-design report → tech-stack-comparison report.

Extract:

• Primary language(s) and framework(s)
• Test framework and test runner
• CI provider/tooling
• Package manager and monorepo structure (if any)
• Module system and build tooling

Write detection result to .ai/workspace/harness/stack-profile.md.

If any field undetectable → AskUserQuestion to confirm before proceeding.

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Phase B — Feedforward Guide Setup (Inferential)

For each guide type, check if it exists; if not, create or enhance:

1. CLAUDE.md / AGENTS.md — Architecture conventions

• Add section: "Architecture Patterns" — document the patterns chosen in /architecture-design (e.g., Clean Architecture, CQRS, Repository)
• Add section: "Anti-Patterns" — explicit list of patterns to avoid for this stack
• Add section: "Naming Conventions" — language-idiomatic conventions for this repository
• Add section: "Module Boundaries" — which layers may import which; dependency direction rules

2. Skill activation rules

• Document in CLAUDE.md which skills auto-activate for common task types in this stack
• Example: "When modifying domain entities → activate /review-domain-entities"
• Example: "Before any commit → run /code-review"

3. Architecture notes

• Create docs/architecture/ with:
  • bounded-contexts.md — domain boundaries and ownership
  • dependency-rules.md — allowed import directions between layers
  • naming-conventions.md — project-specific naming for files, classes, functions

4. Pattern catalog

• Create docs/architecture/pattern-catalog.md
• Document each pattern chosen in /architecture-design with DO/DON'T examples
• Anchor to actual project files once scaffolding produces them

Present list of guides created/updated via AskUserQuestion: "Feedforward guides above will be created/enhanced. Confirm or adjust?"

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Phase C — Computational Feedback Sensors

Confirm /linter-setup has completed:

• Check for linter config file at project root (e.g., .eslintrc, pyproject.toml, .editorconfig)
• Check for pre-commit hook config (e.g., .husky/, .pre-commit-config.yaml)
• Check for CI quality gate definition

If any missing → invoke /linter-setup before continuing.

Output: confirmation that computational sensors are in place, with file paths listed.

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Phase D — Inferential Feedback Sensors

Configure which AI review skills fire at each lifecycle stage. Present to user via AskUserQuestion: "Which inferential sensors should be mandatory vs optional for this repository?"

Pre-implementation (planning gate):

• /why-review — validate design rationale before committing to implementation approach

Pre-commit (lightweight review):

• Document in CLAUDE.md: run /code-review before committing significant changes

Post-implementation (domain model changes):

• /review-domain-entities — when domain entity files are in the changeset

Pre-release (mandatory gates):

• /production-readiness-review — reliability and operational readiness
• /security-review — security review before production release

Recurring drift detection:

• /scan-codebase-health — schedule quarterly (or on CI schedule) to detect drift

Add the agreed sensor configuration to CLAUDE.md under "## Review Gates".

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Phase E — Behaviour Harness (Spec + Test Strategy)

Define the project's behaviour harness plan:

Functional spec format:

• AskUserQuestion: "Feature documentation format?" Options: feature-spec (8-section tech-free), TDD specs only, lightweight ADRs
• Establish docs/specs/ or equivalent spec home

Test strategy pyramid:

• Unit: pure functions, domain entities, business logic (no I/O)
• Integration: subcutaneous CQRS tests, repository tests with real DB
• E2E: critical user journeys only (not full coverage — too slow)

Approved fixtures pattern:

• Pre-seed reference/lookup data as approved snapshots
• Integration tests are additive (never delete/reset data)

Test-strength sensors (NOT a line-coverage gate):

• Line coverage is a diagnostic only — NEVER gate a build on it. Low coverage is a useful NEGATIVE signal (an area is untested → investigate); high coverage is NOT evidence of quality (lines can execute with no meaningful assertion). Report it as a diagnostic; do not fail CI on a coverage %.
• Mutation score is the real test-strength metric — gate on this. AskUserQuestion: "Configure a mutation-testing tool (e.g. Stryker / PITest / mutmut, per stack) as the CI test-quality gate?" A surviving mutant = a fault your tests did not catch = a missing/weak assertion. Add a minimum mutation-score threshold to CI as the computational test-strength sensor.
• Property coverage (optional second sensor): each named business invariant guarded by ≥1 property/metamorphic test. Track which invariants have a property test; an unguarded invariant is a gap to fill.
• Keep behavior/change-coverage (meaningful, not a %): every behavior-changing file must have a test that asserts the changed outcome — see /integration-test-review Gate 7. This is the right notion of "coverage"; the line-% is not.

Document agreed test strategy to docs/architecture/test-strategy.md.

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Phase F — Harness Inventory Report

Write .ai/workspace/harness/harness-inventory.md:

# Harness Inventory

Generated: {date}
Stack: {detected stack from Phase A}

## Feedforward Guides

| Type          | File/Skill                           | Purpose                         |
| ------------- | ------------------------------------ | ------------------------------- |
| Inferential   | CLAUDE.md §Architecture Patterns     | Shapes AI architectural choices |
| Inferential   | CLAUDE.md §Anti-Patterns             | Prevents known bad patterns     |
| Inferential   | docs/architecture/pattern-catalog.md | DO/DON'T examples per pattern   |
| Computational | .editorconfig                        | Cross-IDE consistency           |

## Feedback Sensors — Computational

| Stage      | Tool/Hook         | What it catches                                |
| ---------- | ----------------- | ---------------------------------------------- |
| Pre-commit | {linter}          | Style violations, common errors                |
| Pre-commit | {formatter}       | Code formatting drift                          |
| CI         | {type-checker}    | Type errors                                    |
| CI         | {static-analyzer} | Security, complexity, dead code                |
| CI         | {mutation-tool}   | Weak/missing assertions (test-strength GATE)   |
| CI         | {coverage-tool}   | Untested areas (DIAGNOSTIC only — never gated) |

## Feedback Sensors — Inferential

| Stage               | Skill/Agent                  | What it catches                |
| ------------------- | ---------------------------- | ------------------------------ |
| Pre-implementation  | /why-review                  | Design rationale gaps          |
| Pre-commit          | /code-review                 | Convention drift, logic errors |
| Post-implementation | /review-domain-entities      | Domain model quality           |
| Pre-release         | /production-readiness-review | Operational readiness          |
| Pre-release         | /security-review             | Security vulnerabilities       |

## Open Gaps

| Area                     | Reason   | Risk           |
| ------------------------ | -------- | -------------- |
| {area not yet harnessed} | {reason} | {LOW/MED/HIGH} |

Present inventory to user for review via AskUserQuestion.

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Next Steps

AskUserQuestion:

• "/feature-implement (Recommended)" — Begin implementing the project plan with full harness in place
• "/why-review" — Review harness design rationale before proceeding
• "Skip" — Proceed manually without workflow guidance

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[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

AI Mistake Prevention — Failure modes to avoid on every task:

Re-read files after context changes. Context compaction, resume, or long-running work can make memory stale; verify current files before acting. Verify generated content against source evidence. AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. Check downstream references before deleting or renaming. Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. Trace the full impact chain after edits. Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done. Verify ALL affected outputs, not just the first. One green check is not all green checks; validate every output surface the change can affect. Assume existing values are intentional — ask WHY before changing. Before changing a constant, limit, flag, wording, or pattern, read nearby context and history. Surface ambiguity before acting — don't pick silently. Multiple valid interpretations require an explicit question or stated assumption with risk. Keep shared guidance role-relevant. Universal guidance must help every receiving skill or agent; code-specific obligations belong only in code-specific protocols.

Harness Engineering — An outer agent harness has two jobs: raise first-attempt quality + provide self-correction feedback loops before human review.

Controls split:

Axis	Type	Examples	Frequency
Feedforward	Computational	.editorconfig, strict compiler flags, enforced module boundaries	Always-on
Feedforward	Inferential	CLAUDE.md conventions, skill prompts, architecture notes, pattern catalogs	Always-on
Feedback	Computational	Linters, type checks, pre-commit hooks, ArchUnit/arch-fitness tests, mutation-score gate, CI gates	Pre-commit → CI
Feedback	Inferential	/code-review skill, /production-readiness-review, /security-review, LLM-as-judge passes	Post-commit → CI

Test-strength sensor — gate on mutation score, NOT line coverage. Line coverage is a DIAGNOSTIC only: low coverage is a useful NEGATIVE signal (something is untested); high coverage is NOT evidence of quality (tests can execute lines without asserting intent) — NEVER fail a build on a line-coverage %. The real test-strength metric is mutation score (inject faults into changed code; surviving mutant = a missing/weak assertion = write the killing test); gate the build on it where a mutation tool exists. Add property coverage as a second sensor — each [HARD] §4 rule / §5 invariant guarded by ≥1 property/metamorphic test. The property tests themselves are REQUIRED for invariant-owning behaviors (spec [mode=tests] + integration-test force them, not opt-in); what is optional is only wiring property coverage as an automated CI sensor on top. Keep behavior/change-coverage (does each behavior-changing file have a test that asserts the changed outcome) — that notion is meaningful and stays.

Three harness types:

1. Maintainability — Complexity, duplication, line-coverage (diagnostic only — never a gate), style. Easiest: rich deterministic tooling.
2. Architecture fitness — Module boundaries, dependency direction, performance budgets, observability conventions.
3. Behaviour — Functional correctness. Hardest: gate on mutation score + property coverage; line coverage stays a diagnostic.

Prompt-Enhance Closing Anchors

IMPORTANT MUST ATTENTION follow declared step order for this skill; NEVER skip, reorder, or merge steps without explicit user approval IMPORTANT MUST ATTENTION for every step/sub-skill call: set in_progress before execution, set completed after execution IMPORTANT MUST ATTENTION every skipped step MUST include explicit reason; every completed step MUST include concise evidence IMPORTANT MUST ATTENTION if Task tools unavailable, maintain an equivalent step-by-step plan tracker with synchronized statuses

Closing Reminders

IMPORTANT MUST ATTENTION Goal: Wire every feedforward guide and feedback sensor into the project so all later AI agents self-correct against quality gates BEFORE human review — raising first-attempt quality and catching defects at the earliest, cheapest stage.

IMPORTANT MUST ATTENTION Protocols in force (concise digest of the SYNC/shared blocks this skill carries):

• Critical Thinking: critical + sequential thinking; every claim traced, confidence >80% to act.
• AI Mistake Prevention: verify generated content against evidence, trace downstream references, verify all affected outputs, re-read after context loss, surface ambiguity.
• Harness Engineering: feedforward + feedback loops; gate on mutation score, never line-coverage %, keep quality left.

IMPORTANT MUST ATTENTION BLOCK on the /linter-setup prerequisite first — ALWAYS verify computational sensors (linter config, pre-commit hook, CI gate) exist before any phase runs — why: keep quality left; cheapest gates must precede inferential ones, and this skill never installs them itself IMPORTANT MUST ATTENTION NEVER auto-decide feedforward-guide or sensor content — present the draft and confirm via AskUserQuestion — why: harness conventions bind every future agent; silent choices propagate to all later sessions IMPORTANT MUST ATTENTION write .ai/workspace/harness/harness-inventory.md incrementally (append after each phase) — NEVER hold findings in memory — why: long context drifts and silently drops findings IMPORTANT MUST ATTENTION walk phases A→F as a hard barrier sequence — NEVER skip or reorder; each phase BLOCKS the next until its guard passes — why: a later phase consumes the prior phase's verified output IMPORTANT MUST ATTENTION gate the behaviour harness on mutation score + property coverage — NEVER fail a build on a line-coverage % — why: lines execute without asserting intent, so coverage % is a diagnostic only, never a quality gate IMPORTANT MUST ATTENTION research tool choices per detected stack — NEVER hardcode a linter/formatter/mutation tool — present top 2-3 options, enforce strictest defaults, loosen only with explicit approval — why: harnessability depends on the actual stack, not a default IMPORTANT MUST ATTENTION harness inventory is a LIVING document — update it when new sensors are added later — why: a stale inventory misrepresents the active feedback loop IMPORTANT MUST ATTENTION grep 3+ existing guides/sensors before authoring a new one; verify fit (same stack, gate stage, lifecycle) before copying a nearby pattern — why: closest example ≠ matching preconditions IMPORTANT MUST ATTENTION cite file:line / config-path evidence for every detected sensor and stack fact (confidence >80% to act, <60% DO NOT recommend) — NEVER speculate a tool exists; grep the config to confirm — why: a hallucinated sensor leaves a real gap unguarded IMPORTANT MUST ATTENTION bootstrap task tracking before phases — TaskCreate one todo per phase, mark in_progress/completed as you go; on context loss TaskList first — why: resume work, never duplicate phases

Anti-Rationalization:

Evasion	Rebuttal
"Linter probably set up — skip the prereq check"	Grep for the config files. No file:line proof = BLOCK Phase A/B/C/D/E until verified.
"I'll pick the obvious linter myself"	NEVER auto-decide — present top 2-3 via AskUserQuestion; the user owns binding conventions.
"High line coverage means tests are strong"	Coverage is a diagnostic, not a gate. Gate on mutation score; lines run without asserting.
"Inventory's small, I'll hold it in memory"	Append per phase to the inventory file — context loss silently drops findings.
"CLAUDE.md exists, harness already done"	CLAUDE.md is a feedforward guide to ENHANCE, never a signal to skip phases.

IMPORTANT MUST ATTENTION BLOCK on /linter-setup before any phase · NEVER auto-decide harness content (AskUserQuestion-gate) · gate behaviour on mutation score, NEVER on line-coverage %.