linter-setup

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[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.

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Quick Summary

Goal: Ensure every code change is caught by an automated quality sensor — both locally (fast feedback) AND in CI (enforcement gate) — before it reaches main, with zero divergence between the two, by installing the full computational feedback sensor layer for the tech stack (linters, formatters, type checkers, static analyzers, pre-commit hooks, and CI quality gates).

Summary:

• Purpose — install the full computational feedback sensor layer for the detected stack so no code change reaches main unguarded: strict-by-default, research-driven (NEVER hardcode tools), local-and-CI with zero divergence, proven to block.
• Main steps, in order: (1) Detect stack — read plan.md → architecture report → tech-stack report, write stack-profile.md; AskUserQuestion if a critical field is undetectable. (2) Research each tool category — linter, formatter, type checker, static analyzer, dependency scanner, architecture fitness — via QUERY TEMPLATES; score top 3; present top 2-3 per category via AskUserQuestion, user picks. (3) Install & configure — STRICTEST reasonable defaults (loosen ONLY with explicit user approval), document what each rule catches, add cache dirs to .gitignore, ALWAYS emit a stack-agnostic .editorconfig. (4) Wire the pre-commit hook — formatter→linter→type-check, staged-files-only, <30s; document setup in README.md. (5) Configure the CI quality gate to MIRROR the hook (format→lint→type→static→dep-scan), coverage diagnostic-only. (6) Verify — fire the hook with an INTENTIONAL violation, confirm it blocks before declaring complete. (7) Next steps — AskUserQuestion to continue to /harness-setup.
• Non-negotiables — research-driven tool choice (NEVER hardcode), strict-by-default, local↔CI zero divergence, prove the gate blocks before done.

Output: Config files at project root + pre-commit hook config + CI quality gate step + .editorconfig.

When invoked: After /scaffold in the greenfield workflow, before /harness-setup.

Design principles:

• Generic — No hardcoded tool names in the research protocol. AI researches the stack's ecosystem.
• Research-driven — Per-stack research → present top 2-3 options → user picks → configure.
• Strict-by-default — Propose strictest reasonable settings; loosen only with explicit user approval.
• Purpose-first — Every category has a WHY; understanding purpose prevents cargo-culting.
• Integration-ready — Every tool must work both locally (fast feedback) AND in CI (enforcement gate).

Stack Detection Protocol

Read from (in priority order):

1. plan.md YAML frontmatter — look for tech_stack, language, framework fields
2. Architecture-design report — look for tech stack comparison table
3. Tech-stack-comparison report — look for chosen stack

Extract: primary language(s), framework(s), CI provider/tooling, test framework, package manager.

Write detected profile to .ai/workspace/linter-setup/stack-profile.md:

# Stack Profile

Language: {language}
Framework: {framework}
Package Manager: {npm/pip/dotnet/go/cargo/etc}
CI Provider/Tooling: {github-actions/gitlab-ci/azure-pipelines/etc}
Test Framework: {framework}

If any critical field undetectable → AskUserQuestion to confirm before research.

Tool Research Protocol

MANDATORY IMPORTANT MUST ATTENTION — This section uses QUERY TEMPLATES, not tool names. DO NOT hardcode specific tool recommendations. Research current ecosystem for the detected stack and present options.

For each tech stack layer detected, research these TOOL CATEGORIES using the query templates below:

Research process per category:

1. Search with query template (WebSearch if available, otherwise apply knowledge with explicit confidence %)
2. Score top 3 candidates: community adoption, last release date, CI integration ease, config complexity
3. Present via AskUserQuestion: "For {category} in {language}, which tool?" — top 2-3 as options + brief pros/cons

IMPORTANT: Confidence in current ecosystem <80% (fast-moving ecosystem, unfamiliar stack) → use WebSearch to verify before presenting options. — why: tool ecosystems churn fast; stale recommendations cargo-cult dead tools.

Dependency-Boundary Enforcement (Architecture Fitness detail — options, not defaults)

The Architecture Fitness category above is where dependency-direction / module-boundary enforcement is chosen. It consumes the architecture-design "Arch rules / fitness" scaffold handoff. Treat the following only as example candidates to research and evaluate for stack fit — never mandatory installs. Research the current ecosystem, then present the top 2-3 via AskUserQuestion and let the user confirm:

Only add a boundary tool when the architecture actually declares dependency directions to enforce. If no cross-module rules are declared, record N/A — no cross-module dependency rules declared rather than installing a tool speculatively. Chosen rules MUST encode the architecture's dependency directions and fail CI on a violation, mirroring the pre-commit posture (local↔CI zero divergence). Init/audit grading of whether boundaries exist at all is owned by architecture-scalability-review; per-change boundary drift is owned by architecture-review. — why: a boundary tool with no declared rules is ceremony; enforcement without CI teeth is documentation.

Installation & Configuration Protocol

After user selects tools per category:

1. Generate install command for detected package manager
2. Generate config file with STRICTEST reasonable defaults

- Rationale: starting strict is easier to loosen than starting loose is to tighten - Loosen ONLY with explicit user approval via AskUserQuestion

1. Document what each enabled rule catches and why (one line per rule group)
2. Generate sample config file: .{tool}rc, {tool}.config.{ext}, pyproject.toml section, etc.
3. Add tool cache directories to .gitignore

.editorconfig (ALWAYS generate — stack-agnostic):

root = true

[*]
indent_style = space
indent_size = 2
end_of_line = lf
charset = utf-8
trim_trailing_whitespace = true
insert_final_newline = true

Adjust indentsize and endof_line for the detected stack's conventions.

Pre-Commit Hook Setup

Note on framework names: Pre-commit hook frameworks are ecosystem infrastructure standards, not research choices. Naming them here is correct — they are the glue layer, not the quality tools invoked through them. The quality tools (linter, formatter) invoked inside hooks are the research-driven selections from the Tool Research Protocol above.

Detect pre-commit framework for the stack:

• Node.js / JavaScript / TypeScript → Husky + lint-staged OR lefthook (research current community preference)
• Python → pre-commit framework (pre-commit package)
• Configured backend/runtime stack → restore/install analyzer tools + custom .git/hooks/pre-commit shell script
• Go → pre-commit framework or custom Makefile target
• Rust → cargo-husky OR pre-commit framework
• Java / Kotlin → pre-commit framework or Maven/Gradle Git hooks plugin
• Ruby → overcommit OR pre-commit framework

Configure hooks to run in this order (fastest first to fail fast):

1. Formatter (check only — do not auto-fix in hook)
2. Linter (fail on any error)
3. Type-check (fail on any error)

Performance constraint: Hooks MUST run in <30 seconds total for good DX. If slower:

• Configure to run only on staged files (not full codebase)
• Defer slow checks (static analysis, full type-check) to CI only

Generate:

• Hook config file (.husky/pre-commit, .lefthook.yml, .pre-commit-config.yaml, etc.)
• README.md section: "## Code Quality — Pre-commit Hooks" with setup instructions for new team members

CI Quality Gate Configuration

Detect CI provider/tooling from repository files:

• .github/workflows/ → GitHub Actions
• .gitlab-ci.yml → GitLab CI
• azure-pipelines.yml → Azure Pipelines
• Jenkinsfile → Jenkins
• bitbucket-pipelines.yml → Bitbucket Pipelines

If not detected → AskUserQuestion: "Which CI provider/tooling does this repository use?"

Generate CI job/step that:

1. Restores tool cache (install only on cache miss)
2. Runs formatter check (fail on diff — --check mode, no auto-fix)
3. Runs linter (fail on any error)
4. Runs type checker (fail on any error)
5. Runs static analyzer (fail on threshold: configurable complexity and duplication)
6. Runs dependency vulnerability scanner (fail on HIGH/CRITICAL CVEs)
7. Reports line-coverage as a DIAGNOSTIC only — NEVER fail the build on a coverage %. Low coverage is a useful untested-area signal; high coverage is not evidence of quality. If a test-strength gate is wanted, AskUserQuestion: "Configure a mutation-testing tool (e.g. Stryker / PITest / mutmut, per stack) as the CI test-quality gate?" — gate on mutation score (surviving mutant = missing/weak assertion), with line-coverage reported but ungated. Keep behavior/change-coverage (each behavior-changing file has a test asserting the changed outcome) as the meaningful coverage notion.

MANDATORY: CI gate must match pre-commit hooks. If a check runs locally, it runs in CI. No divergence.

Verification Checklist

After all config files generated, verify MUST ATTENTION each item:

• Config files exist at project root (linter, formatter, type-checker configs)
• .editorconfig created at project root
• Pre-commit hook fires on git commit — test with an intentional violation (e.g., add a lint error, attempt commit, verify hook blocks)
• CI step defined and references the correct config files
• Team setup documented in README.md — new devs know to run {hook install command} after clone
• .gitignore updated with tool cache directories

Next Steps

AskUserQuestion:

• "/harness-setup continues (Recommended)" — Set up feedforward guides + inferential sensors to complete the outer harness
• "/feature-implement" — Skip harness inventory and begin implementation
• "Skip" — Continue manually

[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.

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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.

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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.

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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

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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.

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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.

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Closing Reminders

IMPORTANT MUST ATTENTION Goal: Every code change is caught by an automated quality sensor — both locally (fast feedback) AND in CI (enforcement gate) — before it reaches main, with ZERO divergence between the two, by installing the full sensor layer (linter, formatter, type checker, static analyzer, dependency scanner, architecture fitness, pre-commit hook, CI gate) for the detected stack.

IMPORTANT MUST ATTENTION Main steps (in order — do not skip): (1) detect stack → (2) research tool categories, present 2-3 per category via AskUserQuestion → (3) install & configure strict + .editorconfig + .gitignore → (4) wire pre-commit hook (format→lint→type, staged-only, <30s) → (5) mirror it in a CI quality gate → (6) verify the hook blocks an INTENTIONAL violation → (7) offer /harness-setup next.

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

• Critical Thinking: MUST ATTENTION apply critical/sequential thinking; cite proof, NEVER present guess as fact.
• AI Mistake Prevention: verify generated content against evidence, trace downstream references, verify all affected outputs, re-read after context loss, surface ambiguity.

IMPORTANT MUST ATTENTION use QUERY TEMPLATES in Tool Research — NEVER hardcode tool names in the research phase; research the detected stack's current ecosystem and present options — why: tool ecosystems churn fast, hardcoded names cargo-cult dead tools. IMPORTANT MUST ATTENTION present top 2-3 options per category via AskUserQuestion — let the user pick; NEVER auto-select — why: tool choice is a team-owned decision, not the skill's. IMPORTANT MUST ATTENTION verify the pre-commit hook fires with an INTENTIONAL violation (add a lint error, attempt commit, confirm it blocks) before marking complete — why: an unproven gate is no gate. IMPORTANT MUST ATTENTION CI gate MUST match pre-commit hooks — if a check runs locally it runs in CI, no divergence — why: divergent local/CI checks let violations slip through one path.

MUST ATTENTION detect the stack FIRST (plan.md → architecture report → tech-stack report); if a critical field is undetectable, AskUserQuestion before research — why: every downstream tool choice depends on the stack profile. MUST ATTENTION configure with the STRICTEST reasonable defaults; loosen ONLY with explicit user approval via AskUserQuestion — why: starting strict is easier to loosen than starting loose is to tighten. MUST ATTENTION ALWAYS emit a stack-agnostic .editorconfig and add tool cache dirs to .gitignore — why: editorconfig is the one truly portable cross-tool baseline; cached artifacts must never be committed. MUST ATTENTION order hooks formatter→linter→type-check, staged-files-only, <30s; defer slow checks (static analysis, full type-check) to CI — why: a slow hook gets bypassed, killing local feedback. MUST ATTENTION report line-coverage as a DIAGNOSTIC only — NEVER fail the build on a coverage %; gate on mutation score if a test-strength gate is wanted — why: high coverage is not evidence of assertion quality. MUST ATTENTION pre-commit hook framework names ARE allowed (ecosystem glue, not research choices) — the quality tools invoked inside them are the research-driven selections — why: keep the generic/research boundary clear.

MUST ATTENTION when confidence in the current ecosystem is <80% (fast-moving or unfamiliar stack), use WebSearch to verify before presenting options — cite confidence % for every recommendation; <60% DO NOT recommend — why: stale tool advice fails silently. MUST ATTENTION grep/glob the repo for 3+ existing config/CI patterns before generating new ones — match the project's existing layout, don't impose a foreign convention — why: a config that fights local convention gets reverted. MUST ATTENTION evaluate fit before copying a nearby config — verify the new stack shares the same package manager, CI provider, and conventions as the source — why: closest example ≠ matching preconditions. MUST ATTENTION bootstrap a TaskCreate breakdown (one task per category/config file + a final verification task) BEFORE acting; keep exactly one task in_progress — why: long research/config work loses context without external tracking.

Anti-Rationalization:

IMPORTANT MUST ATTENTION use QUERY TEMPLATES — NEVER hardcode tool names; present top 2-3 via AskUserQuestion. IMPORTANT MUST ATTENTION prove the pre-commit hook blocks an intentional violation before declaring complete. IMPORTANT MUST ATTENTION CI gate must match pre-commit hooks — zero divergence between local and CI checks.

[TASK-PLANNING] Before acting, analyze task scope and break it into small todo tasks using TaskCreate.