EasyPlatform story-review

[Code Quality] Review user stories for completeness, coverage, dependencies, and quality before implementation. AI self-review gate after /story.

install
source · Clone the upstream repo
git clone https://github.com/duc01226/EasyPlatform
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/duc01226/EasyPlatform "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/story-review" ~/.claude/skills/duc01226-easyplatform-story-review && rm -rf "$T"
manifest: .claude/skills/story-review/SKILL.md
source content

[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.

Evidence Gate: MANDATORY IMPORTANT MUST ATTENTION — every claim, finding, and recommendation requires

file:line
proof or traced evidence with confidence percentage (>80% to act, <80% must verify first).

OOP & DRY Enforcement: MANDATORY IMPORTANT MUST ATTENTION — flag duplicated patterns that should be extracted to a base class, generic, or helper. Classes in the same group or suffix (ex *Entity, *Dto, *Service, etc...) MUST ATTENTION inherit a common base (even if empty now — enables future shared logic and child overrides). Verify project has code linting/analyzer configured for the stack.

External Memory: For complex or lengthy work (research, analysis, scan, review), write intermediate findings and final results to a report file in

plans/reports/
— prevents context loss and serves as deliverable.

<!-- SYNC:critical-thinking-mindset -->

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.

<!-- /SYNC:critical-thinking-mindset --> <!-- SYNC:ai-mistake-prevention -->

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

  • Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal.
  • Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing.
  • Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain.
  • Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path.
  • When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site.
  • Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code.
  • Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks.
  • Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis.
  • Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly.
  • Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.
<!-- /SYNC:ai-mistake-prevention --> <!-- SYNC:double-round-trip-review -->

Deep Multi-Round Review — Escalating rounds. Round 1 in main session. Round 2+ and EVERY recursive re-review iteration MUST use a fresh sub-agent.

Round 1: Main-session review. Read target files, build understanding, note issues. Output baseline findings.

Round 2: MANDATORY fresh sub-agent review — see

SYNC:fresh-context-review
for the spawn mechanism and
SYNC:review-protocol-injection
for the canonical Agent prompt template. The sub-agent re-reads ALL files from scratch with ZERO Round 1 memory. It must catch:

  • Cross-cutting concerns missed in Round 1
  • Interaction bugs between changed files
  • Convention drift (new code vs existing patterns)
  • Missing pieces that should exist but don't
  • Subtle edge cases the main session rationalized away

Round 3+ (recursive after fixes): After ANY fix cycle, MANDATORY fresh sub-agent re-review. Spawn a NEW Agent tool call each iteration — never reuse Round 2's agent. Each new agent re-reads ALL files from scratch with full protocol injection. Continue until PASS or 3 fresh-subagent rounds max, then escalate to user via

AskUserQuestion
.

Rules:

  • NEVER declare PASS after Round 1 alone
  • NEVER reuse a sub-agent across rounds — every iteration spawns a NEW Agent call
  • Main agent READS sub-agent reports but MUST NOT filter, reinterpret, or override findings
  • Max 3 fresh-subagent rounds per review — if still FAIL, escalate via
    AskUserQuestion
    (do NOT silently loop)
  • Track round count in conversation context (session-scoped)
  • Final verdict must incorporate ALL rounds

Report must include

## Round N Findings (Fresh Sub-Agent)
for every round N≥2.

<!-- /SYNC:double-round-trip-review --> <!-- SYNC:fresh-context-review -->

Fresh Sub-Agent Review — Eliminate orchestrator confirmation bias via isolated sub-agents.

Why: The main agent knows what it (or

/cook
) just fixed and rationalizes findings accordingly. A fresh sub-agent has ZERO memory, re-reads from scratch, and catches what the main agent dismissed. Sub-agent bias is mitigated by (1) fresh context, (2) verbatim protocol injection, (3) main agent not filtering the report.

When: Round 2 of ANY review AND every recursive re-review iteration after fixes. NOT needed when Round 1 already PASSes with zero issues.

How:

  1. Spawn a NEW
    Agent
    tool call — use
    code-reviewer
    subagent_type for code reviews,
    general-purpose
    for plan/doc/artifact reviews
  2. Inject ALL required review protocols VERBATIM into the prompt — see
    SYNC:review-protocol-injection
    for the full list and template. Never reference protocols by file path; AI compliance drops behind file-read indirection (see
    SYNC:shared-protocol-duplication-policy
    )
  3. Sub-agent re-reads ALL target files from scratch via its own tool calls — never pass file contents inline in the prompt
  4. Sub-agent writes structured report to
    plans/reports/{review-type}-round{N}-{date}.md
  5. Main agent reads the report, integrates findings into its own report, DOES NOT override or filter

Rules:

  • NEVER reuse a sub-agent across rounds — every iteration spawns a NEW
    Agent
    call
  • NEVER skip fresh-subagent review because "last round was clean" — every fix triggers a fresh round
  • Max 3 fresh-subagent rounds per review — escalate via
    AskUserQuestion
    if still failing; do NOT silently loop or fall back to any prior protocol
  • Track iteration count in conversation context (session-scoped, no persistent files)
<!-- /SYNC:fresh-context-review --> <!-- SYNC:review-protocol-injection -->

Review Protocol Injection — Every fresh sub-agent review prompt MUST embed 10 protocol blocks VERBATIM. The template below has ALL 10 bodies already expanded inline. Copy the template wholesale into the Agent call's

prompt
field at runtime, replacing only the
{placeholders}
in Task / Round / Reference Docs / Target Files / Output sections with context-specific values. Do NOT touch the embedded protocol sections.

Why inline expansion: Placeholder markers would force file-read indirection at runtime. AI compliance drops significantly behind indirection (see

SYNC:shared-protocol-duplication-policy
). Therefore the template carries all 10 protocol bodies pre-embedded.

Subagent Type Selection

  • code-reviewer
    — for code reviews (reviewing source files, git diffs, implementation)
  • general-purpose
    — for plan / doc / artifact reviews (reviewing markdown plans, docs, specs)

Canonical Agent Call Template (Copy Verbatim)

Agent({
  description: "Fresh Round {N} review",
  subagent_type: "code-reviewer",
  prompt: `
## Task
{review-specific task — e.g., "Review all uncommitted changes for code quality" | "Review plan files under {plan-dir}" | "Review integration tests in {path}"}

## Round
Round {N}. You have ZERO memory of prior rounds. Re-read all target files from scratch via your own tool calls. Do NOT trust anything from the main agent beyond this prompt.

## Protocols (follow VERBATIM — these are non-negotiable)

### Evidence-Based Reasoning
Speculation is FORBIDDEN. Every claim needs proof.
1. Cite file:line, grep results, or framework docs for EVERY claim
2. Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend
3. Cross-service validation required for architectural changes
4. "I don't have enough evidence" is valid and expected output
BLOCKED until: Evidence file path (file:line) provided; Grep search performed; 3+ similar patterns found; Confidence level stated.
Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because".
If incomplete → output: "Insufficient evidence. Verified: [...]. Not verified: [...]."

### Bug Detection
MUST check categories 1-4 for EVERY review. Never skip.
1. Null Safety: Can params/returns be null? Are they guarded? Optional chaining gaps? .find() returns checked?
2. Boundary Conditions: Off-by-one (< vs <=)? Empty collections handled? Zero/negative values? Max limits?
3. Error Handling: Try-catch scope correct? Silent swallowed exceptions? Error types specific? Cleanup in finally?
4. Resource Management: Connections/streams closed? Subscriptions unsubscribed on destroy? Timers cleared? Memory bounded?
5. Concurrency (if async): Missing await? Race conditions on shared state? Stale closures? Retry storms?
6. Stack-Specific: JS: === vs ==, typeof null. C#: async void, missing using, LINQ deferred execution.
Classify: CRITICAL (crash/corrupt) → FAIL | HIGH (incorrect behavior) → FAIL | MEDIUM (edge case) → WARN | LOW (defensive) → INFO.

### Design Patterns Quality
Priority checks for every code change:
1. DRY via OOP: Same-suffix classes (*Entity, *Dto, *Service) MUST share base class. 3+ similar patterns → extract to shared abstraction.
2. Right Responsibility: Logic in LOWEST layer (Entity > Domain Service > Application Service > Controller). Never business logic in controllers.
3. SOLID: Single responsibility (one reason to change). Open-closed (extend, don't modify). Liskov (subtypes substitutable). Interface segregation (small interfaces). Dependency inversion (depend on abstractions).
4. After extraction/move/rename: Grep ENTIRE scope for dangling references. Zero tolerance.
5. YAGNI gate: NEVER recommend patterns unless 3+ occurrences exist. Don't extract for hypothetical future use.
Anti-patterns to flag: God Object, Copy-Paste inheritance, Circular Dependency, Leaky Abstraction.

### Logic & Intention Review
Verify WHAT code does matches WHY it was changed.
1. Change Intention Check: Every changed file MUST serve the stated purpose. Flag unrelated changes as scope creep.
2. Happy Path Trace: Walk through one complete success scenario through changed code.
3. Error Path Trace: Walk through one failure/edge case scenario through changed code.
4. Acceptance Mapping: If plan context available, map every acceptance criterion to a code change.
NEVER mark review PASS without completing both traces (happy + error path).

### Test Spec Verification
Map changed code to test specifications.
1. From changed files → find TC-{FEAT}-{NNN} in docs/business-features/{Service}/detailed-features/{Feature}.md Section 15.
2. Every changed code path MUST map to a corresponding TC (or flag as "needs TC").
3. New functions/endpoints/handlers → flag for test spec creation.
4. Verify TC evidence fields point to actual code (file:line, not stale references).
5. Auth changes → TC-{FEAT}-02x exist? Data changes → TC-{FEAT}-01x exist?
6. If no specs exist → log gap and recommend /tdd-spec.
NEVER skip test mapping. Untested code paths are the #1 source of production bugs.

### Fix-Layer Accountability
NEVER fix at the crash site. Trace the full flow, fix at the owning layer. The crash site is a SYMPTOM, not the cause.
MANDATORY before ANY fix:
1. Trace full data flow — Map the complete path from data origin to crash site across ALL layers (storage → backend → API → frontend → UI). Identify where bad state ENTERS, not where it CRASHES.
2. Identify the invariant owner — Which layer's contract guarantees this value is valid? Fix at the LOWEST layer that owns the invariant, not the highest layer that consumes it.
3. One fix, maximum protection — If fix requires touching 3+ files with defensive checks, you are at the wrong layer — go lower.
4. Verify no bypass paths — Confirm all data flows through the fix point. Check for direct construction skipping factories, clone/spread without re-validation, raw data not wrapped in domain models, mutations outside the model layer.
BLOCKED until: Full data flow traced (origin → crash); Invariant owner identified with file:line evidence; All access sites audited (grep count); Fix layer justified (lowest layer that protects most consumers).
Anti-patterns (REJECT): "Fix it where it crashes" (crash site ≠ cause site, trace upstream); "Add defensive checks at every consumer" (scattered defense = wrong layer); "Both fix is safer" (pick ONE authoritative layer).

### Rationalization Prevention
AI skips steps via these evasions. Recognize and reject:
- "Too simple for a plan" → Simple + wrong assumptions = wasted time. Plan anyway.
- "I'll test after" → RED before GREEN. Write/verify test first.
- "Already searched" → Show grep evidence with file:line. No proof = no search.
- "Just do it" → Still need TaskCreate. Skip depth, never skip tracking.
- "Just a small fix" → Small fix in wrong location cascades. Verify file:line first.
- "Code is self-explanatory" → Future readers need evidence trail. Document anyway.
- "Combine steps to save time" → Combined steps dilute focus. Each step has distinct purpose.

### Graph-Assisted Investigation
MANDATORY when .code-graph/graph.db exists.
HARD-GATE: MUST run at least ONE graph command on key files before concluding any investigation.
Pattern: Grep finds files → trace --direction both reveals full system flow → Grep verifies details.
- Investigation/Scout: trace --direction both on 2-3 entry files
- Fix/Debug: callers_of on buggy function + tests_for
- Feature/Enhancement: connections on files to be modified
- Code Review: tests_for on changed functions
- Blast Radius: trace --direction downstream
CLI: python .claude/scripts/code_graph {command} --json. Use --node-mode file first (10-30x less noise), then --node-mode function for detail.

### Understand Code First
HARD-GATE: Do NOT write, plan, or fix until you READ existing code.
1. Search 3+ similar patterns (grep/glob) — cite file:line evidence.
2. Read existing files in target area — understand structure, base classes, conventions.
3. Run python .claude/scripts/code_graph trace <file> --direction both --json when .code-graph/graph.db exists.
4. Map dependencies via connections or callers_of — know what depends on your target.
5. Write investigation to .ai/workspace/analysis/ for non-trivial tasks (3+ files).
6. Re-read analysis file before implementing — never work from memory alone.
7. NEVER invent new patterns when existing ones work — match exactly or document deviation.
BLOCKED until: Read target files; Grep 3+ patterns; Graph trace (if graph.db exists); Assumptions verified with evidence.

## Reference Docs (READ before reviewing)
- docs/project-reference/code-review-rules.md
- {skill-specific reference docs — e.g., integration-test-reference.md for integration-test-review; backend-patterns-reference.md for backend reviews; frontend-patterns-reference.md for frontend reviews}

## Target Files
{explicit file list OR "run git diff to see uncommitted changes" OR "read all files under {plan-dir}"}

## Output
Write a structured report to plans/reports/{review-type}-round{N}-{date}.md with sections:
- Status: PASS | FAIL
- Issue Count: {number}
- Critical Issues (with file:line evidence)
- High Priority Issues (with file:line evidence)
- Medium / Low Issues
- Cross-cutting findings

Return the report path and status to the main agent.
Every finding MUST have file:line evidence. Speculation is forbidden.
`
})

Rules

  • DO copy the template wholesale — including all 10 embedded protocol sections
  • DO replace only the
    {placeholders}
    in Task / Round / Reference Docs / Target Files / Output sections with context-specific content
  • DO choose
    code-reviewer
    subagent_type for code reviews and
    general-purpose
    for plan / doc / artifact reviews
  • DO NOT paraphrase, summarize, or skip any protocol section
  • DO NOT pass file contents inline — the sub-agent reads via its own tool calls so it has a fresh context
  • DO NOT reference protocols by file path or tag name — the bodies are already embedded above
  • DO NOT introduce placeholder markers for the protocols — they must stay literally expanded
<!-- /SYNC:review-protocol-injection --> <!-- SYNC:graph-impact-analysis -->

Graph Impact Analysis — When

.code-graph/graph.db
exists, run
blast-radius --json
to detect ALL files affected by changes (7 edge types: CALLS, MESSAGE_BUS, API_ENDPOINT, TRIGGERS_EVENT, PRODUCES_EVENT, TRIGGERS_COMMAND_EVENT, INHERITS). Compute gap: impacted_files - changed_files = potentially stale files. Risk: <5 Low, 5-20 Medium, >20 High. Use
trace --direction downstream
for deep chains on high-impact files.

<!-- /SYNC:graph-impact-analysis -->

Quick Summary

Goal: Auto-review user stories for completeness, acceptance criteria coverage, dependency ordering, and quality before implementation proceeds.

Key distinction: AI self-review (automatic), NOT user interview.

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Frontend/UI Context (if applicable)

When this task involves frontend or UI changes,

<!-- SYNC:ui-system-context -->

UI System Context — For ANY task touching

.ts
,
.html
,
.scss
, or
.css
files:

MUST ATTENTION READ before implementing:

  1. docs/project-reference/frontend-patterns-reference.md
    — component base classes, stores, forms
  2. docs/project-reference/scss-styling-guide.md
    — BEM methodology, SCSS variables, mixins, responsive
  3. docs/project-reference/design-system/README.md
    — design tokens, component inventory, icons

Reference

docs/project-config.json
for project-specific paths.

<!-- /SYNC:ui-system-context -->
  • Component patterns:
    docs/project-reference/frontend-patterns-reference.md
    (content auto-injected by hook — check for [Injected: ...] header before reading)
  • Styling/BEM guide:
    docs/project-reference/scss-styling-guide.md
  • Design system tokens:
    docs/project-reference/design-system/README.md

Adversarial Review Mindset (NON-NEGOTIABLE)

Default stance: SKEPTIC challenging story quality, not confirming it.

Self-review trap: You wrote these stories. You will find them coherent because you made them coherent. This section forces deliberate challenge before rubber-stamping.

Adversarial Techniques (apply ALL before concluding)

1. Strawman AC Check For each acceptance criterion: "Is this AC so obvious it was only included to pad coverage?" (e.g., "User can see the page" — trivially true and tests nothing meaningful). Flag trivial ACs that would pass even if the feature is completely broken.

2. Vertical Slice Challenge For each story: "Can a stakeholder demo THIS STORY ALONE to a real user and get useful feedback?" If the story only delivers a backend endpoint, a DB migration, or a UI component in isolation — it is a horizontal layer, not a vertical slice. Flag it.

3. Dependency Challenge If story B is blocked by story A: "What happens to the sprint if story A is descoped or delayed?" A story set with rigid sequential dependencies is fragile. Are dependencies truly required, or can stories be resequenced?

4. INVEST Violation Hunt Deliberately look for the WEAKEST INVEST criterion for each story. Ask: "Which of I/N/V/E/S/T does this story fail most obviously?" If a story is not Estimable — why not? If not Independent — can it be split?

5. Pre-Mortem Assume all stories in this set are implemented exactly as written. The feature ships and fails. Write the most plausible failure scenario. Which story was the gap?

6. Contrarian Pass Before writing any verdict, generate at least 2 sentences arguing the OPPOSITE conclusion. Then decide which argument is stronger.

Forbidden Patterns

  • "Stories follow GIVEN/WHEN/THEN" → Format is NOT quality. Are the scenarios meaningful?
  • "Coverage looks complete" → What failure mode is NOT covered by any story?
  • "Dependencies are identified" → Are they truly required, or is there a split that removes them?
  • "Vertical slices" → Can you actually demo each story independently? Prove it.
  • Confirming story set without adversarial challenge → Forbidden.

Anti-Bias Gate (MANDATORY before finalizing verdict)

  • Identified at least 1 trivial/strawman AC across the story set
  • Verified each story delivers a demeable vertical slice
  • Checked dependency chain — fragile if >2 sequential dependencies
  • Found the weakest INVEST criterion per story
  • Ran pre-mortem (plausible failure scenario)
  • Generated at least 2 sentences arguing the opposite verdict

If any box is unchecked → adversarial review incomplete. Go back.

Workflow

  1. Locate stories — Find story artifacts in
    team-artifacts/stories/
    or plan context
  2. Load source PBI — Read the parent PBI to cross-reference acceptance criteria
  3. Evaluate checklist — Score each check
  4. Classify — PASS/WARN/FAIL
  5. Output verdict

Checklist

Required (all must pass)

#CheckPresenceQuality Depth
1AC coverage — Every acceptance criterion from PBI has at least one corresponding storyDoes every PBI AC have a story?Does every PBI AC have a story? Or are some ACs split across multiple stories in ways that create coverage gaps?
2GIVEN/WHEN/THEN — Each story has minimum 3 BDD scenarios (happy, edge, error)Are all 3 BDD parts present per scenario?Are all 3 BDD parts present per scenario? Are scenarios testing REAL user behavior or just "the system does X"?
3INVEST criteria — Stories are Independent, Negotiable, Valuable, Estimable, Small, TestableAre all 6 INVEST criteria named or implied?Are stories genuinely Independent (no hidden chains), Valuable (real user impact), Testable (automatable)?
4Story points — All stories have SP <=8 (>8 must be split)Are SP assigned and all <=8?Do SP reflect actual complexity? Is <=8 justified, or is the story undersized to pass the gate?
5Dependency table — Story set includes dependency ordering table (must-after, can-parallel, independent)Does a dependency ordering table exist?Does the ordering reflect ACTUAL dependencies, not just arbitrary sequencing?
6No overlapping scope — Stories don't duplicate functionalityDo any 2 stories reference the same AC?Do any 2 stories claim the same AC? Would implementing both create duplication?
7Vertical slices — Each story delivers end-to-end value (not horizontal layers)Does each story touch more than one layer (UI + API or API + DB)?Can a stakeholder demo EACH story to a real user independently? Or do some deliver only infrastructure?
8Authorization scenarios — Every story includes at least 1 authorization scenario (unauthorized access → rejection) per PBI roles tableIs an authorization scenario present per story?Is the unauthorized-access scenario testing a realistic attack vector, not just "wrong role → 403"?
9UI Wireframe section — If story involves UI: has
## UI Wireframe
section per UI wireframe protocol (wireframe + component tree + interaction flow + states + responsive). If backend-only: explicit "N/A"
Does the section exist (or explicit N/A for backend-only)?If UI: does the wireframe show interaction flow + states + responsive breakpoints? If backend-only: is "N/A" explicit?

Recommended (>=50% should pass)

#CheckPresenceQuality Depth
1Edge cases — Boundary values, empty states, max limits addressedAre edge case scenarios listed?Are boundary values story-specific (not generic "empty state")? Do they include concurrency or partial-data scenarios?
2Error scenarios — Failure paths explicitly covered in storiesAre error path scenarios present?Do error stories specify the exact error message/code returned, or just "shows error"?
3API contract — If API changes needed, story specifies contractIs a request/response contract defined?Does the contract specify request/response schema fully? Are breaking vs non-breaking changes distinguished?
4UI/UX visualization — Frontend stories have component decomposition tree with EXISTING/NEW classification, design token mapping, and responsive breakpoint behavior per UI wireframe protocolIs a component decomposition tree present?Are components EXISTING vs NEW classified? Are design token names (not just colors) specified?
5Seed data stories — If PBI has seed data requirements, Sprint 0 seed data story existsDoes a seed data story exist (or N/A if not required)?If present, does the seed data story specify the exact data shape needed?
6Data migration stories — If PBI has schema changes, data migration story existsDoes a data migration story exist (or N/A if no schema changes)?If present, does it specify rollback behavior?

Output

## Story Review Result

**Status:** PASS | WARN | FAIL
**Stories reviewed:** {count}
**Source PBI:** {pbi-path}

### AC Coverage Matrix

| Acceptance Criterion | Covered By Story | Status |
| -------------------- | ---------------- | ------ |

### Required ({X}/{Y})

- ✅/❌ Check description

### Recommended ({X}/{Y})

- ✅/⚠️ Check description

### Missing Stories

- {Any PBI AC not covered}

### Dependency Issues

- {Circular deps, missing ordering}

### Verdict

{PROCEED | REVISE_FIRST}

Round 2+ : Fresh Sub-Agent Re-Review (MANDATORY)

Protocol:

SYNC:double-round-trip-review
+
SYNC:fresh-context-review
+
SYNC:review-protocol-injection
(all inlined above in this file).

After completing Round 1 checklist evaluation, spawn a fresh

general-purpose
sub-agent for Round 2 using the canonical Agent template from
SYNC:review-protocol-injection
above. Story artifact reviews are NOT code reviews — use
subagent_type: "general-purpose"
. When constructing the Agent call prompt:

  1. Copy the Agent call shape from the
    SYNC:review-protocol-injection
    template verbatim
  2. Set
    subagent_type: "general-purpose"
  3. Embed the full verbatim body of these SYNC blocks:
    SYNC:evidence-based-reasoning
    ,
    SYNC:rationalization-prevention
    ,
    SYNC:understand-code-first
    (omit code-specific protocols like
    SYNC:bug-detection
    ,
    SYNC:design-patterns-quality
    ,
    SYNC:fix-layer-accountability
    which are not applicable to story artifacts)
  4. Set the Task as
    "Review the user story artifacts for completeness and quality. Focus on: implicit assumptions not validated, missing acceptance criteria coverage, edge cases not addressed in BDD scenarios, cross-references not verified, vague language, authorization gaps, INVEST violations."
  5. Set Target Files as the explicit story file paths being reviewed
  6. Set report path as
    plans/reports/story-review-round{N}-{date}.md

After sub-agent returns:

  1. Read the sub-agent's report
  2. Integrate findings as
    ## Round {N} Findings (Fresh Sub-Agent)
    in the main report — DO NOT filter or override
  3. If FAIL: fix issues in the stories, then spawn a NEW Round N+1 fresh sub-agent (new Agent call — never reuse Round 2's agent)
  4. Max 3 fresh rounds — escalate to user via
    AskUserQuestion
    if still failing after 3 rounds
  5. Final verdict must incorporate findings from ALL rounds

Key Rules

  • FAIL blocks workflow — If FAIL, do NOT proceed. List specific fixes.
  • Cross-reference PBI — Every check against stories MUST ATTENTION trace back to PBI acceptance criteria.
  • No guessing — Reference specific story content as evidence.
  • Flag missing stories — If a PBI acceptance criterion has no covering story, that's a FAIL.

Next Steps

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing this skill, you MUST ATTENTION use

AskUserQuestion
to present these options. Do NOT skip because the task seems "simple" or "obvious" — the user decides:

  • "/plan (Recommended)" — Create implementation plan from validated stories
  • "/story" — Re-create stories if FAIL verdict
  • "/prioritize" — Prioritize stories in backlog
  • "Skip, continue manually" — user decides

Closing Reminders

MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using

TaskCreate
BEFORE starting. MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via
AskUserQuestion
— never auto-decide. MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality. MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:

<!-- SYNC:double-round-trip-review:reminder -->
  • MANDATORY IMPORTANT MUST ATTENTION execute TWO review rounds. Round 2 delegates to fresh code-reviewer sub-agent (zero prior context) — never skip or combine with Round 1. <!-- /SYNC:double-round-trip-review:reminder --> <!-- SYNC:graph-impact-analysis:reminder -->
  • IMPORTANT MUST ATTENTION run graph blast-radius on changed files to find potentially stale consumers/handlers (when graph.db exists). <!-- /SYNC:graph-impact-analysis:reminder --> <!-- SYNC:ui-system-context:reminder -->
  • IMPORTANT MUST ATTENTION read frontend-patterns-reference, scss-styling-guide, design-system/README before any UI change. <!-- /SYNC:ui-system-context:reminder --> <!-- SYNC:critical-thinking-mindset:reminder -->
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact. <!-- /SYNC:critical-thinking-mindset:reminder --> <!-- SYNC:ai-mistake-prevention:reminder -->
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction. <!-- /SYNC:ai-mistake-prevention:reminder -->