Harness Setup

[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 — why: harness conventions bind every future agent and silent choices propagate.
• Write .ai/workspace/harness/harness-inventory.md incrementally (append per phase, never held in memory) — keep it a LIVING document updated as new sensors are added.

Main steps (run in order — each BLOCKS the next):

1. Guards — BLOCK until /linter-setup verified (linter config + pre-commit hook + CI gate present); detect existing inventory (enhance, never skip).
2. Phase A — Stack Detection — read plan / architecture-design / tech-stack reports; write stack-profile.md; AskUserQuestion on any undetectable field.
3. Phase B — Feedforward Guides — author/enhance CLAUDE.md/AGENTS.md (architecture patterns, anti-patterns, naming, module boundaries) + skill-activation rules + docs/architecture/* notes + pattern catalog; confirm via AskUserQuestion.
4. Phase C — Computational Sensors — confirm /linter-setup outputs; list config paths (invoke /linter-setup if any missing).
5. Phase D — Inferential Sensors — wire review skills to lifecycle gates (/why-review pre-impl · /code-review pre-commit · /domain-entities-review post-impl · /production-readiness-review + /security-review pre-release · /scan-codebase-health recurring · /integration-test-review feature-area TC audit BOTH pre-release AND recurring — closes the diff-scoped blind spot); record under "## Review Gates".
6. Phase E — Behaviour Harness — pick spec format, define test pyramid + approved fixtures, gate on mutation score (NEVER line %), add property/behavior coverage; write test-strategy.md.
7. Phase F — Inventory Report — append harness-inventory.md (feedforward + computational/inferential sensors + open gaps); present via AskUserQuestion.
8. Next Steps — AskUserQuestion: /feature-implement (recommended) · /why-review · skip.

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.

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

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.

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 /domain-entities-review"
• 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?"

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.

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):

• /domain-entities-review — 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
• /integration-test-review — Missing Integration Test / Spec-Coverage Gate: feature-area-wide TC audit (Phase 3 addendum in that skill) catches orphaned Section-8 TCs and uncovered changed behavior. Wire BOTH pre-release (mandatory gate, alongside /production-readiness-review and /security-review) AND same recurring cadence as /scan-codebase-health — a diff-scoped run alone cannot see a TC whose covering test regressed outside the current change set; only a periodic feature-area sweep does.

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

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.

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     | /domain-entities-review                          | Domain model quality                               |
| Pre-release             | /production-readiness-review                     | Operational readiness                              |
| Pre-release             | /security-review                                 | Security vulnerabilities                           |
| Pre-release + Recurring | /integration-test-review (feature-area TC audit) | Orphaned Section-8 TCs, uncovered changed behavior |

## Open Gaps

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

Present inventory to user for review via AskUserQuestion.

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

[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 OR flagging one as a defect. Before changing or reporting a constant, limit, flag, cutoff, wording, or pattern, read nearby context and history, the CALLER's ordering, and 2+ sibling call sites of the same convention. A doc stating WHAT without WHY is missing rationale, not proof of a missing guard. Surface ambiguity before acting — don't pick silently. Multiple valid interpretations require an explicit question or stated assumption with risk. Assert the outcome your system owns, not the intermediate state your infrastructure owns. When verifying async work, assert the final business state — never the delivery/retry bookkeeping held in shared infrastructure that any co-running process can write. Such a check passes when run alone and flakes the moment anything else shares that infrastructure. 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.

Keep quality left: pre-commit sensors fire first (cheap), CI sensors fire second, post-review last (expensive).

Research-driven: Never hardcode tool choices. Detect tech stack → research ecosystem → present top 2-3 options → user decides. Enforce strictest defaults; loosen only with explicit approval.

Harnessability signals: Strong typing, explicit module boundaries, opinionated frameworks = easier to harness. Treat these as greenfield architectural choices, not just style preferences.

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

Project Protocol Overlay — Before executing this skill, resolve any PROJECT overlay rules layered onto it: match this skill's name against the Target column of the project's skill-protocol index (docs/project-reference/skill-protocols-reference.md by default; a referenceDocs entry in docs/project-config.json overrides the path), taking the most specific matching tier ONLY — exact name > glob > *. That precedence orders overlays against EACH OTHER, never against this skill. Read ONLY the matched bodies, resolved as <protocols-dir>/<Name>.md; a row's Body link is display text, never a read path. A matched body that is missing or malformed is REPORTED and skipped — never reconstructed from the index Description. No index, or no match -> proceed with no overlay, silently. Full contract: .claude/skills/project-skill-protocol/references/registry.md.

Overlays are ADDITIVE ONLY: they ADD rules on top of this skill's own protocol and NEVER replace, override, disable, or reinterpret a rule it already states — removing every overlay must return this skill to exactly its documented behavior. An overlay is a BRIEF, not an authority escalation: it can NEVER waive a workflow gate, git discipline, a review gate, or a user-confirmation gate. A genuine overlay-vs-skill conflict, or two equally-specific overlays that directly contradict -> surface both to the user; NEVER resolve silently.

MUST ATTENTION resolve project protocol overlays for this skill BEFORE executing — most specific matching tier only (exact > glob > *, which ranks overlays against each other, NEVER against this skill), read only matched bodies at <protocols-dir>/<Name>.md; a missing or malformed body is reported, never reconstructed. Overlays are ADDITIVE ONLY (they never replace this skill's own rules) and are a brief, NEVER an authority escalation; an equal-specificity contradiction goes to the user.

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 Main steps (in order — each BLOCKS the next): Guards (verify /linter-setup) → A Stack Detection (stack-profile.md) → B Feedforward Guides (CLAUDE.md patterns/anti-patterns/naming/boundaries + skill-activation rules + pattern catalog) → C Computational Sensors (confirm linter/hook/CI) → D Inferential Sensors (wire /why-review, /code-review, /domain-entities-review, /production-readiness-review, /security-review, /scan-codebase-health, /integration-test-review missing-test/spec-coverage gate to gates) → E Behaviour Harness (spec format + test pyramid + mutation-score gate + test-strategy.md) → F Inventory Report (harness-inventory.md) → Next Steps. NEVER skip or reorder — why: each phase consumes the prior phase's verified output.

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 wire /integration-test-review's feature-area-wide TC audit as a Phase D sensor BOTH pre-release AND on the SAME recurring cadence as /scan-codebase-health — never pre-release only — why: a diff-scoped-only run cannot see a §8 TC whose covering test regressed outside the current change set; only a periodic feature-area sweep catches it 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:

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 %.