This skill should be used when performing exhaustive code reviews using multi-agent analysis, ultra-thinking, and worktrees.

Review Command

<command_purpose> Perform exhaustive code reviews using multi-agent analysis, ultra-thinking, and Git worktrees for deep local inspection. </command_purpose>

Introduction

<role>Senior Code Review Architect with expertise in security, performance, architecture, and quality assurance</role>

Prerequisites

<requirements> - Git repository with GitHub CLI (`gh`) installed and authenticated - Clean main/master branch - Proper permissions to create worktrees and access the repository - For document reviews: Path to a markdown file or document </requirements>

Main Tasks

0. Setup

Load project conventions:

# Load project conventions
if [[ -f "CLAUDE.md" ]]; then
  cat CLAUDE.md
fi

Read CLAUDE.md if it exists - apply project conventions during review.

1. Determine Review Target & Setup (ALWAYS FIRST)

<review_target> #$ARGUMENTS </review_target>

<thinking> First, I need to determine the review target type and set up the code for analysis. </thinking>

Immediate Actions:

<task_list>

Determine review type: PR number (numeric), GitHub URL, file path (.md), or empty (current branch)
Check current git branch
If ALREADY on the target branch (PR branch, requested branch name, or the branch already checked out for review) → proceed with analysis on current branch
If DIFFERENT branch than the review target → offer to use worktree: "Use git-worktree skill for isolated Call skill: git-worktree with branch name
Fetch PR metadata using gh pr view --json for title, body, files, linked issues
Set up language-specific analysis tools
Prepare security scanning environment
Make sure we are on the branch we are reviewing. Use gh pr checkout to switch to the branch or manually checkout the branch.

Ensure that the code is ready for analysis (either in worktree or on current branch). ONLY then proceed to the next step.

</task_list>

Change Classification Gate

Before spawning review agents, classify the PR to avoid spawning agents whose expertise is irrelevant to the change.

Run git diff --name-only origin/main...HEAD | head -n 200 to get the list of changed files.
Check for override: scan $ARGUMENTS for "deep review" or "full review". Also run gh pr view --json body,title --jq '.body + " " + .title' and check for the same phrases. If override detected, skip classification and spawn all 8 agents.
Apply a single judgment on the file list: Does this PR contain source code files? Source code includes: .ts, .js, .jsx, .tsx, .rb, .py, .go, .rs, .swift, .kt, .java, .c, .cpp, .cs, .php, .sh, .bash, .zsh — any file that contains executable logic. Non-code includes: .md, .txt, .yml, .yaml, .toml, .json, .css, .html, .njk, .svg, .png, .jpg, .gif, .pen, LICENSE, CHANGELOG*, .github/** workflow files, and plugin/agent/skill definition files (plugins/**/*.md, agents/**/*.md).
Announce the classification result before spawning agents.

Parallel Agents to review the PR:

<parallel_tasks>

If the PR contains source code files (or override detected), spawn all 8 agents:

Task git-history-analyzer(PR content)
Task pattern-recognition-specialist(PR content)
Task architecture-strategist(PR content)
Task security-sentinel(PR content)
Task performance-oracle(PR content)
Task data-integrity-guardian(PR content)
Task agent-native-reviewer(PR content) - Verify new features are agent-accessible
Task code-quality-analyst(PR content) - Detect code smells and produce refactoring roadmap

If the PR contains NO source code files (non-code only), spawn 4 agents:

Task git-history-analyzer(PR content)
Task pattern-recognition-specialist(PR content)
Task security-sentinel(PR content) - Still needed: config/CI can expose secrets, markdown can contain code examples
Task code-quality-analyst(PR content) - Still needed: docs/config quality matters

Skipped for non-code PRs: architecture-strategist, performance-oracle, data-integrity-guardian, agent-native-reviewer. These agents analyze source code structure, runtime performance, database integrity, and agent accessibility — none are relevant to documentation, configuration, or CI changes.

Announce: "Change classified as [code/non-code]. Spawning [N]/8 review agents. [If non-code: Skipped: architecture-strategist, performance-oracle, data-integrity-guardian, agent-native-reviewer — not relevant to non-code changes. Use 'deep review' to force full pipeline.]"

</parallel_tasks>

Note: The conditional agents block below (agents 9-14: Rails reviewers, migration experts, test-design-reviewer, semgrep) is unaffected by the classification gate. Both gates run independently — the classification controls only the always-on agents above.

Conditional Agents (Run if applicable):

<conditional_agents>

These agents are run ONLY when the PR matches specific criteria. Check the PR files list and project structure to determine if they apply:

If project is a Rails app (Gemfile AND config/routes.rb exist at repo root):

Task kieran-rails-reviewer(PR content) - Rails conventions and quality bar
Task dhh-rails-reviewer(PR title) - Rails philosophy and anti-patterns

When to run Rails review agents:

Repository root contains both Gemfile and config/routes.rb
PR modifies Ruby files (*.rb)
PR title/body mentions: Rails, Ruby, controller, model, migration, ActiveRecord

What these agents check:

kieran-rails-reviewer: Strict Rails conventions, naming clarity, controller complexity, Turbo patterns
dhh-rails-reviewer: Rails philosophy adherence, JavaScript framework contamination, unnecessary abstraction

If PR contains database migrations (db/migrate/*.rb files) or data backfills:

Task data-migration-expert(PR content) - Validates ID mappings match production, checks for swapped values, verifies rollback safety
Task deployment-verification-agent(PR content) - Creates Go/No-Go deployment checklist with SQL verification queries

When to run migration agents:

PR includes files matching db/migrate/*.rb
PR modifies columns that store IDs, enums, or mappings
PR includes data backfill scripts or rake tasks
PR changes how data is read/written (e.g., changing from FK to string column)
PR title/body mentions: migration, backfill, data transformation, ID mapping

What these agents check:

data-migration-expert: Verifies hard-coded mappings match production reality (prevents swapped IDs), checks for orphaned associations, validates dual-write patterns
deployment-verification-agent: Produces executable pre/post-deploy checklists with SQL queries, rollback procedures, and monitoring plans

If PR contains test files:

Task test-design-reviewer(PR content) - Score test quality against Farley's 8 properties

When to run test review agent:

PR includes files matching *_test.rb, *_spec.rb
PR includes files matching test_*.py, *_test.py
PR includes files matching *.test.ts, *.test.js, *.spec.ts, *.spec.js
PR includes files matching *_test.go
PR includes files matching *_test.swift, *Tests.swift
PR includes files in __tests__/ or spec/ or test/ directories

What this agent checks:

test-design-reviewer: Scores tests against Farley's 8 properties, produces a weighted Test Quality Score with letter grade and top 3 improvement recommendations

If PR modifies source code files, semgrep-sast is a mandatory gate:

Task semgrep-sast(PR content) - Deterministic SAST scanning for known vulnerability patterns

When to run SAST agent:

PR modifies source code files (.py,.js, .ts,.rb, .go,.java, .rs,.swift, *.kt, etc.)
Not needed for documentation-only or config-only changes

Bootstrap (mandatory before spawning the agent): Run ensure-semgrep.sh from the repo root. The script checks PATH first, then auto-installs via brew → pipx → pip --user in that order. Exits 0 when semgrep is reachable. Exit 1 means an install was attempted and failed; exit 2 means no install path was available (no brew, pipx, or python3 with pip). On non-zero exit, print the script's stderr to the user and abort the review. Do NOT silently skip — the deterministic SAST pass is what catches CodeQL-equivalent patterns like js/file-system-race before push.

Custom rules file: semgrep-custom-rules.yaml ships alongside the public rule packs and covers CodeQL queries the public packs miss (e.g. the TOCTOU patterns that blocked PR #2463 in CI). The semgrep-sast agent loads it via --config=plugins/soleur/skills/review/references/semgrep-custom-rules.yaml. Extend it whenever a CodeQL finding in CI was not caught locally — the goal is no-surprises on CI.

What this agent checks:

semgrep-sast: Known vulnerability signatures (CWE patterns), hardcoded secrets, insecure function calls, taint analysis. Complements security-sentinel's LLM-based architectural review with deterministic rule-based scanning.

</conditional_agents>

2. Rate Limit Fallback

<decision_gate>

After all parallel and conditional agents complete, check their outputs:

If ALL agents returned empty output or rate-limit errors (e.g., "out of extra usage", "rate limit exceeded", zero findings across every agent): perform an inline review in the main context covering all four core dimensions — security, architecture, performance, and simplicity. This is expected fallback behavior during high-usage periods, not an error condition.
If ANY agent returned substantive output: proceed normally with available results. No fallback needed — partial coverage from real agents is better than duplicating their work inline.

This is a binary gate: all-failed triggers the fallback; any-succeeded means continue.

</decision_gate>

4. Ultra-Thinking Deep Dive Phases

<ultrathink_instruction> For each phase below, spend maximum cognitive effort. Think step by step. Consider all angles. Question assumptions. And bring all reviews in a synthesis to the user.</ultrathink_instruction>

<deliverable> Complete system context map with component interactions </deliverable>

Phase 3: Stakeholder Perspective Analysis

<thinking_prompt> ULTRA-THINK: Put yourself in each stakeholder's shoes. What matters to them? What are their pain points? </thinking_prompt>

<stakeholder_perspectives>

Developer Perspective <questions>
- How easy is this to understand and modify?
- Are the APIs intuitive?
- Is debugging straightforward?
- Can I test this easily? </questions>
Operations Perspective <questions>
- How do I deploy this safely?
- What metrics and logs are available?
- How do I troubleshoot issues?
- What are the resource requirements? </questions>
End User Perspective <questions>
- Is the feature intuitive?
- Are error messages helpful?
- Is performance acceptable?
- Does it solve my problem? </questions>
Security Team Perspective <questions>
- What's the attack surface?
- Are there compliance requirements?
- How is data protected?
- What are the audit capabilities? </questions>
Business Perspective <questions>
- What's the ROI?
- Are there legal/compliance risks?
- How does this affect time-to-market?
- What's the total cost of ownership? </questions> </stakeholder_perspectives>

Phase 4: Scenario Exploration

<thinking_prompt> ULTRA-THINK: Explore edge cases and failure scenarios. What could go wrong? How does the system behave under stress? </thinking_prompt>

<scenario_checklist>

6. Multi-Angle Review Perspectives

Technical Excellence Angle

Code craftsmanship evaluation
Engineering best practices
Technical documentation quality
Tooling and automation assessment

Business Value Angle

Feature completeness validation
Performance impact on users
Cost-benefit analysis
Time-to-market considerations

Risk Management Angle

Security risk assessment
Operational risk evaluation
Compliance risk verification
Technical debt accumulation

Team Dynamics Angle

Code review etiquette
Knowledge sharing effectiveness
Collaboration patterns
Mentoring opportunities

4. Simplification and Minimalism Review

Run the Task code-simplicity-reviewer() to see if we can simplify the code.

4.5. CLI-Verification Check (user-facing docs only)

When reviewing a PR that changes *.njk, *.md, README, or content under apps/**, scan every fenced code block tagged bash, sh, shell, or untagged-but-CLI-shaped. For each <command> <subcommand> pair:

If the tool is well-known (git, gh, npm, bun, curl, ollama, supabase, doppler, etc.), verify the subcommand exists. Cross-reference the tool's official docs via WebFetch or run <tool> --help. If unsure, flag as cli-verification-unverified and require an explicit annotation or citation before approving.
If the tool is project-local (./scripts/*, plugins/soleur/skills/*/scripts/*), verify the script exists at the path.
If the snippet names a model or registry tag (<model>:<tag>, @<version>), fetch the registry or cite the registry URL.

Flag any unverified CLI invocation as P1 (docs-trust) — NOT P3 polish. A fabricated CLI command on a high-intent landing page breaks first-touch trust (#1810/#2550).

5. Findings Synthesis and GitHub Issue Creation

<critical_requirement> Each finding's default action is to FIX IT INLINE on the PR branch: make the edit, commit with a message review: <summary> (P<N>), and push. Apply to P1, P2, P3 equally.

Filing a GitHub issue instead of fixing is allowed ONLY when the finding meets one of these four scope-out criteria:

cross-cutting-refactor — fix requires touching ≥3 files that are materially unrelated to this PR's core change, where core change = files named in the PR's linked issue, OR files in the same top-level directory (e.g., apps/web-platform/, plugins/soleur/) as the primary changed file. Bare multi-file fixes do NOT qualify; the unrelatedness must be concrete and defensible — count specific files or drop the scope-out.
contested-design — multiple valid fix approaches AND the review agent (not the PR author) independently names ≥2 concrete approaches that trade off differently on durability, cost, or complexity AND recommends a design cycle outside this PR. Author-initiated contested-design claims ("I don't feel like implementing approach X here") do NOT qualify; the agent must independently surface the tradeoff.
architectural-pivot — fix would change a pattern used across the codebase and deserves its own planning cycle.
pre-existing-unrelated — finding existed on main before this PR and is not exacerbated by the PR's changes. (Does NOT block merge.) Only reachable through the pre-existing branch of the provenance triage in Step 1 below — never applies to pr-introduced findings.

When filing:

The issue body MUST contain a ## Scope-Out Justification section naming the specific criterion and a 1-3 sentence rationale.
The issue MUST be created with --label deferred-scope-out and --milestone (per guardrails:require-milestone).
The issue title MUST use a review-origin prefix (review:, Code review #, Refactor:, arch:, compound:, follow-through:).
Use gh issue create --body-file <path> — never --body "$VAR" — so untrusted finding text (diffs, agent output) cannot shell-interpolate.

Everything else (magic numbers, duplicated helpers, small refactors, missing tests for PR-introduced code, polish, naming, a11y on PR-introduced surfaces, performance issues introduced by the PR) MUST be fixed inline.

Second-reviewer confirmation gate: Before creating a scope-out issue under any criterion, invoke code-simplicity-reviewer via Task. The prompt MUST include:

The finding (location, description).
The proposed fix.
The exact four scope-out criteria definitions from this section (cross-cutting-refactor ≥3 unrelated files, contested-design with independent agent-named tradeoffs, architectural-pivot, pre-existing- unrelated). Do not rely on the agent's prior knowledge of the criteria — pass the definitions literally.
The criterion being claimed and a 1-3-sentence rationale.
This instruction: "Default to rejecting the scope-out filing. Only co-sign when the claimed criterion is concretely and obviously correct against the four definitions above. Reply with a single line as the first line of your output: CONCUR (to co-sign the filing) or DISSENT: <one-sentence reason> (to flip to fix-inline). Everything after the first line is advisory context."

If the first line of the agent's reply begins with DISSENT, the disposition flips to fix-inline — do not file the issue. If the first line is CONCUR, proceed with filing. Any other first-line content is treated as DISSENT (fail-safe toward fix-inline).

Rationale: One agent's "scope-out is fine here" can be wrong in the same way a single test can miss a bug. Requiring a second, simplicity-biased agent to co-sign blocks the most common regression pattern: an agent-author pair rationalizing a filing that a fresh pair of eyes would reject. See knowledge-base/project/learnings/2026-04-15-multi-agent-review-catches-bugs-tests-miss.md.

Filing without scope-out justification will be caught by /ship Phase 5.5 Review- Findings Exit Gate and BLOCK merge. See rule rf-review-finding-default-fix-inline. </critical_requirement>

Step 1: Synthesize All Findings

<thinking> Consolidate all agent reports into a categorized list of findings. Remove duplicates, prioritize by severity and impact. </thinking>

<synthesis_tasks>

Collect findings from all parallel agents
Categorize by type: security, performance, architecture, quality, etc.
Assign severity levels: CRITICAL (P1), IMPORTANT (P2), NICE-TO-HAVE (P3)
Remove duplicate or overlapping findings
Estimate effort for each finding (Small/Medium/Large)
Tag each finding with provenance: pr-introduced or pre-existing. A finding is pr-introduced if the code the finding critiques was added or modified by this PR's diff (verify with git log -L :<function>:<file> origin/main..HEAD or git diff origin/main...HEAD -- <file>). A finding is pre-existing if the code existed on main before this PR and the PR neither changed nor moved it. Provenance-ambiguous findings (e.g., a helper the PR refactored but didn't introduce) default to pr-introduced — the PR touched it, the PR owns the fix.

Disposition by provenance:

pr-introduced: MUST be fixed inline. No scope-out allowed regardless of criterion — the PR introduced the concern, the PR resolves it. If a fix is genuinely too large, reduce the PR (split or revert the offending commit) rather than filing a scope-out.
pre-existing: Triage into exactly one of three buckets:
1. Fix inline — small, load-bearing, cheap to include. Default for sub-20-line fixes on files the PR already touches.
2. File as scope-out — legitimately needs its own cycle. MUST carry the pre-existing-unrelated criterion AND a re-evaluation deadline (a target phase milestone such as Phase 4, or a concrete trigger condition such as "revisit when syncWorkspace lands in #2244"). Open-ended scope-outs with no deadline are NOT permitted — they become the backlog this rule exists to drain.
3. Close as wontfix — polish-only, low-value noise, or concern already covered by existing code. Close immediately (do not file) with a 1-sentence rationale in the summary report.

The pr-introduced → fix inline rule is the mechanical version of rule rf-review-finding-default-fix-inline: it removes the judgment loophole ("is this really cross-cutting?") for findings the PR itself introduced.

</synthesis_tasks>

Coupling note: Ship Phase 1.5, Phase 5.5, and pre-merge hook pre-merge:review-evidence-gate detect review evidence by searching for GitHub issues with the code-review label whose body contains PR #<number>. If the issue body template or label changes, update detection logic in ship/SKILL.md and .claude/hooks/pre-merge-rebase.sh. Phase 5.5 Review-Findings Exit Gate (new in #2374) additionally detects open review-origin issues cross-referencing the PR by body regex (Ref|Closes|Fixes) #<N>\b without deferred-scope-out label; filing without scope-out justification will block merge.

Step 2: Create GitHub Issues

<critical_instruction> Fix inline or, where a scope-out criterion applies, create a deferred-scope-out issue. Do NOT present findings for per-item user approval. </critical_instruction>

Read plugins/soleur/skills/review/references/review-todo-structure.md now for the complete GitHub issue creation flow: label prerequisite, issue body template, --body-file pattern, label/milestone selection, duplicate detection, error handling, and batch strategy.

Step 3: Summary Report

After creating all GitHub issues, present comprehensive summary:

## Code Review Complete

**Review Target:** PR #XXXX - [PR Title] **Branch:** [branch-name]

### Findings Summary

- **Total Findings:** [X]
- **P1 CRITICAL:** [count] - BLOCKS MERGE
- **P2 IMPORTANT:** [count] - Should Fix
- **P3 NICE-TO-HAVE:** [count] - Enhancements
- **By provenance:** [pr-introduced count] pr-introduced, [pre-existing count] pre-existing
- **Pre-existing disposition:** [fix-inline count] fixed, [scope-out count] scoped-out, [wontfix count] wontfix

### Fixed Inline

**P1 - Critical (BLOCKS MERGE):**

- {description} — commit {sha}
- {description} — commit {sha}

**P2 - Important:**

- {description} — commit {sha}

**P3 - Nice-to-Have:**

- {description} — commit {sha}

### Filed as Deferred Scope-Out

**Scope-out criterion required per finding (cross-cutting-refactor | contested-design | architectural-pivot | pre-existing-unrelated):**

- #NNN - review: {description} — criterion: {name} — rationale: {1-3 sentences}
- #NNN - review: {description} — criterion: {name} — rationale: {1-3 sentences}

**Failed (if any):**

- {description} - Error: {error message}

### Review Agents Used

- security-sentinel
- performance-oracle
- architecture-strategist
- agent-native-reviewer
- [other agents]

### Next Steps

1. **Verify inline fixes landed**: Each finding above should have a commit on the PR branch.

   ```bash
   git log --oneline origin/main..HEAD | grep '^[a-f0-9]* review:'
   ```

2. **Inspect any scope-out issues**: Review findings filed as `deferred-scope-out` with justification.

   ```bash
   gh issue list --label deferred-scope-out --search "Ref #<PR_NUMBER>"
   ```

3. **Phase 5.5 gate self-check**: `/ship` will run the Review-Findings Exit Gate and block merge on any open review-origin issue cross-referencing the PR without the `deferred-scope-out` label. If the gate blocks, either fix inline and close the issue, or add the `deferred-scope-out` label + `## Scope-Out Justification`.

Severity Breakdown:

P1 (Critical - Blocks Merge):

Security vulnerabilities
Data corruption risks
Breaking changes
Critical architectural issues

P2 (Important - Should Fix):

Performance issues
Significant architectural concerns
Major code quality problems
Reliability issues

P3 (Nice-to-Have):

Minor improvements
Code cleanup
Optimization opportunities
Documentation updates

6. Exit Gate

Pipeline detection: If the conversation contains skill: soleur:work output earlier (indicating review was invoked by work's Phase 4 chain) or soleur:one-shot output (indicating review was invoked by one-shot step 4), skip the exit gate. The calling pipeline handles compound, commit, and lifecycle progression. When review is invoked by work or one-shot, do not duplicate these steps.

If invoked directly by the user (no work or one-shot orchestrator in the conversation):

Run skill: soleur:compound to capture learnings from the review session. If compound finds nothing to capture, it will skip gracefully — do not block on this.
Commit any local artifacts. GitHub issues are already created remotely, but local files may have been modified (plan updates, todo resolutions). Run git status --short. If there are changes:
```
git add <changed files>
git commit -m "docs: review artifacts for feat-<name>"
git push
```
If there are no local changes, skip the commit (this is the expected case — review's primary output is GitHub issues, which are remote-only). If push fails (no network), warn and continue.
Display: "Review complete. All findings are tracked as GitHub issues. Run /clear then /soleur:work or /soleur:ship for maximum context headroom."

7. End-to-End Testing (Optional)

Read plugins/soleur/skills/review/references/review-e2e-testing.md now for project type detection, testing offers (Web/iOS/Hybrid), and subagent procedures for browser and Xcode testing.

Defect Classes This Review Reliably Catches

Multi-agent parallel review has been shown to catch bugs in shipped, green-CI code across these classes (each a real P1 caught on PR #2347):

Shared mutable state across co-mounted instances — module-level let bindings captured by a once-built object that multiple components import. Pattern-recognition and code-quality agents spot the closure capture in seconds; unit tests rarely co-mount instances.
Validator scope on sibling message fields — new top-level fields added to a schema whose existing validator covers only one field. Security-sentinel asks "what if the client sends X?" for every permutation without waiting for the test author to imagine it.
DB partial-index predicate drift — the application's query filter (.is("archived_at", null)) no longer matches the index's WHERE clause. Data-integrity-guardian reads both files and compares WHERE clauses symbolically; the bug stays silent until a user archives a row.

See knowledge-base/project/learnings/2026-04-15-multi-agent-review-catches-bugs-tests-miss.md for the full pattern catalogue.

Sharp Edges: Review Agent Limitations

Review agent suggestions that modify workflow if conditions or event filters must be smoke tested against the full user journey (not just the reduced trigger case) before shipping -- agents optimize locally and can break flows they don't fully model.

When a reviewer prescribes --arg for jq injection defense in a gh ... --jq context, verify the CLI forwards jq flags before implementing. gh --jq accepts a single expression string and does NOT forward --arg, --argjson, or --slurp to the underlying jq binary — applying the fix produces unknown arguments at runtime. Fall back to shape-validating the shell variable (e.g., [[ "$VAR" =~ ^[0-9]+$ ]]) before interpolation, or pipe to a second-stage standalone jq --arg. See knowledge-base/project/learnings/2026-04-15-gh-jq-does-not-forward-arg-to-jq.md.

Generalizing the rule above: whenever a review agent prescribes a CLI flag or subcommand as a fix (e.g., gh issue create --json number, gh issue close --body-file, <tool> <subcommand> --<flag>), verify the flag exists on that exact subcommand via <tool> <subcommand> --help BEFORE applying. Agents hallucinate flags by generalizing from sibling subcommands (gh issue list has --json, gh issue create does not). Cost of verification: one --help call. Cost of applying a non-existent flag: revert + rework + commit pollution. If the prescribed flag is absent, fall back to a verified pattern (split into two verified commands, parse output with awk -F/, etc.) and note the substitution in the disposition table. See knowledge-base/project/learnings/best-practices/2026-04-19-verify-reviewer-prescribed-cli-flags-before-applying.md.

Parallel review batches can stall silently — spawning 12 review agents at once has been observed to produce completion notifications for only 6, with the remaining agents' transcripts frozen ~15s after spawn and no completion event emitted. When more than 30% of spawned agents stop producing output for >2 minutes after launch, proactively announce "N of M agents stalled" rather than silently waiting. Proceed with synthesis from the agents that returned — the Rate Limit Fallback gate already permits partial coverage. See knowledge-base/project/learnings/2026-04-17-postgrest-aggregate-disabled-forces-rpc-option.md.

Before reporting a broken link or missing file, reviewer agents MUST verify via Glob or Read. Unverified "broken link" claims waste reviewer-response cycles — the file may exist at the exact path. Why: PR #2226 pattern-recognition-specialist false-positive on a runtime-errors/2026-02-13-... learning file that did exist.

When reviewing a Nunjucks/Eleventy page that pairs a visible HTML answer with a FAPage/FAQPage JSON-LD acceptedAnswer.text, compare the two surfaces character-for-character per Question. Google's FAQ rich-result parity check compares codepoints — flag (a) {{ ... }} interpolation in HTML paired with a hardcoded value in JSON-LD, and (b) HTML entities (’, &, etc.) in one surface and ASCII or \uXXXX in the other. See knowledge-base/project/learnings/2026-04-18-faq-html-jsonld-parity.md.

When flagging a skill description word-budget overrun, the tokenizer MUST match the CI gate. plugins/soleur/test/components.test.ts uses desc.split(/\s+/).filter(Boolean).length against the YAML value only (1800-word skill budget); the grep -h 'description:' | wc -w pattern in AGENTS.md belongs to the agent 2500-word budget and includes YAML framing, inflating counts by ~5 words per skill. Run bun test plugins/soleur/test/components.test.ts before reporting — if it passes, the budget is satisfied. See knowledge-base/project/learnings/2026-04-19-skill-description-word-budget-tokenizer.md.

Important: P1 Findings Block Merge

Any P1 (CRITICAL) findings must be addressed before merging the PR. Present these prominently and ensure they're resolved before accepting the PR.