Pbi Challenge

Codex compatibility note:

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- Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.

- Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes.

- User-question prompts mean to ask the user directly in Codex.

- Ignore Claude-specific mode-switch instructions when they appear.

- Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written.

- Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required spawn_agent subagent(s) for that task.

- Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first.

- For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence.

- If a required step/tool cannot run in this environment, stop and ask the user before adapting.

<!-- CODEX:PROJECT-REFERENCE-LOADING:START -->

Codex Project-Reference Loading (No Hooks)

Codex does not receive Claude hook-based doc injection. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing.

Always read:

• docs/project-config.json (project-specific paths, commands, modules, and workflow/test settings)
• docs/project-reference/docs-index-reference.md (routes to the full docs/project-reference/* catalog)
• docs/project-reference/lessons.md (always-on guardrails and anti-patterns)

Situation-based docs:

• Backend/CQRS/API/domain/entity changes: backend-patterns-reference.md, domain-entities-reference.md, project-structure-reference.md
• Frontend/UI/styling/design-system: frontend-patterns-reference.md, scss-styling-guide.md, design-system/README.md
• Spec/test-case planning or TC mapping: feature-docs-reference.md
• Integration test implementation/review: integration-test-reference.md
• E2E test implementation/review: e2e-test-reference.md
• Code review/audit work: code-review-rules.md plus domain docs above based on changed files

Do not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.

<!-- CODEX:PROJECT-REFERENCE-LOADING:END -->

<!-- PROMPT-ENHANCE:STEP-TASK-ANCHOR:START -->

[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.

<!-- PROMPT-ENHANCE:STEP-TASK-ANCHOR:END -->

Quick Summary

Goal: Help Dev BA PIC (Person In Charge — the development Business Analyst responsible for technical review sign-off per squad) review BA drafters' PBI drafts by generating specific, actionable challenge prompts. AI provides analysis; human makes the decision.

Key distinction: Collaborative review tool (drafter → reviewer flow), NOT self-review (use $refine-review for AI self-review).

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

Why This Skill Exists

PBI drafts routinely pass informal review without being challenged on architectural feasibility, vague AC, missing auth scenarios, or cross-service impact. The $refine skill generates PBIs but does not adversarially challenge them — it is a creation tool, not a review tool. The $refine-review skill provides AI self-review for the drafter, but the drafter has inherent blind spots about their own assumptions. A separate reviewer (Dev BA PIC) applying AI-assisted challenge prompts breaks the drafter's confirmation bias before grooming. This skill exists to catch gaps the drafter cannot catch themselves.

Why not just use `$refine-review`? $refine-review is run by the drafter on their own work. Even with adversarial prompts, the drafter rationalizes their own choices. pbi-challenge is invoked by a different person with a different mandate — external skepticism requires a different author, not a different tool on the same author.

Alternatives Considered

Risk Assessment

Frontend/UI Context (if applicable)

When this task involves frontend or UI changes,

• Component patterns: docs/project-reference/frontend-patterns-reference.md (read directly when relevant; do not rely on hook-injected conversation text)
• Styling/BEM guide: docs/project-reference/scss-styling-guide.md
• Design system tokens: docs/project-reference/design-system/README.md

Workflow

1. Locate PBI draft — Find BA drafters' draft PBI in team-artifacts/pbis/ or path provided by user 2. Load domain context — Auto-detect module from PBI content. MANDATORY: Use a direct user question to confirm detected module with Dev BA PIC before loading domain docs. Wrong module = wrong entity context = false APPROVE risk. Then load:

• docs/project-reference/domain-entities-reference.md (entity definitions)
• Relevant feature docs from docs/business-features/{App}/
• Existing business rules (BR-{MOD}-XXX) from feature docs

3. Technical Feasibility Analysis:

• Can described features be built with the project's architecture?
• Any domain entity conflicts? (cross-reference entity definitions)
• Any cross-service implications? (message bus events, shared data between services)
• Estimated complexity alignment (does scope match story points?)

4. AC Quality Analysis:

• Vagueness detector: flag "should", "might", "TBD", "etc.", "various", "appropriate"
• Coverage check: happy path + edge case + error case + authorization scenario
• Missing scenarios: suggest specific additions based on feature type

5. Cross-Cutting Concerns Check:

• Authorization section present and complete? (roles × CRUD matrix)
• Seed data requirements addressed? (or explicit "N/A")
• Data migration implications? (schema changes)
• Performance considerations? (list/grid/export features)
• UI Layout section present? If PBI involves UI: must have ## UI Layout per UI wireframe protocol with wireframe + components (with tiers) + states + design tokens. If backend-only: explicit "N/A". Flag missing UI visualization as a gap.

6. Generate Challenge Prompts — Output specific, actionable questions:

• NOT vague: "needs work" or "improve AC"
• SPECIFIC: "AC #2 says 'user can filter results' — which filters exactly? Suggest: status, date range, priority"

7. Present Challenge Prompts first, then AI Verdict — Output challenge prompts BEFORE the verdict to prevent automation bias. Dev BA PIC reads and forms their preliminary view, THEN sees: APPROVE / REQUEST_REVISION / ESCALATE_TO_LEAD

• Technical decisions (feasibility, dependencies, cross-service impact, security): Dev BA PIC has unilateral veto power — no 2/3 vote needed
• Non-technical decisions (UI/UX design, visual design, business value): 2/3 majority vote required (Dev BA PIC + UX BA + Designer BA per ba-team-decision-model)

8. ask the user directly — Dev BA PIC records their FINAL decision (APPROVE / REQUEST_REVISION / ESCALATE_TO_LEAD) in the Decision Record. This is the human decision step — NOT the workflow routing step (handled separately in Next Steps)

M1-M6 Compliance Gate (BLOCKING — drives the AI Verdict)

Contract: See .claude/skills/shared/sdd-artifact-contract.md → "AI-SDD Mandates (M1-M6)". This challenge enforces M6: a PBI draft that violates any of M1-M5 MUST produce an AI Verdict of REQUEST_REVISION with a challenge prompt that names the violated mandate ID and cites the exact PBI section + line/AC. An APPROVE over an M1-M5 violation is itself defective. (AI provides the analysis; the human still records the final decision.)

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Carriers are EXEMPT from M1/M2 — source identifiers are CORRECT inside [Source: ...], **Evidence**, **IntegrationTest** fields, YAML frontmatter, and `mermaid ` blocks. Only challenge leakage in PBI narrative prose (problem statement, AC text, scope, rule descriptions). Banned prose token list: docs/project-reference/spec-principles.md §3.2.

Run these five checks as part of Step 4 (AC Quality) and Step 5 (Cross-Cutting Concerns); any failure becomes a specific challenge prompt and forces REQUEST_REVISION:

• [ ] M1 — Tech-agnostic prose. FAIL if problem statement, AC, or rule prose names a framework/product, language-native type, or product/design-pattern class name (banned list in spec-principles.md §3.2). Challenge: cite the section + leaked token + business-term replacement.
• [ ] M2 — No source code in prose. FAIL if a requirement is expressed as a class/method/file-path/namespace instead of a business operation. Source identifiers belong only in evidence carriers. Challenge: cite section + line.
• [ ] M3 — Abstract-IDs-first. FAIL if a requirement/rule lacks a logical ID (FR-/BR-/OP-), has a logical ID but no [Source: namespace/service/id] abstract-anchor evidence, uses a physical file:line/src/ path instead of an abstract anchor, or makes the anchor its primary citation. Evidence is REQUIRED and KEPT, but SECONDARY to the logical ID (physical coordinates live only in the provenance sidecar).
• [ ] M4 — Unambiguous AC. FAIL if any AC uses vague language ("should", "might", "appropriate", "various", "as needed"), two engineers could implement it differently while both claiming conformance, or no observable completion state / named error condition exists. (Extends the Step-4 vagueness detector to an M4 verdict.)
• [ ] M5 — Implementable from artifact alone. FAIL if a competent team with ZERO codebase knowledge could not build the PBI on a different stack from the PBI alone (relies on reading source to understand it). Challenge: cite section + missing detail.

If ANY box fails → AI Verdict is REQUEST_REVISION; tag each violated mandate ID with its concrete section/line citation in the Challenge Prompts and the AI Verdict Reason.

Output

## PBI Challenge Review

**PBI:** {PBI filename}
**Reviewer:** Dev BA PIC
**Date:** {date}
**Module:** {detected module code}

### Technical Feasibility

**Status:** FEASIBLE | CONCERNS | INFEASIBLE
{Analysis with evidence — cite domain entities, service boundaries, architecture constraints}

### AC Quality

**Status:** GOOD | NEEDS_REVISION | POOR

| AC # | Issue            | Suggested Fix             |
| ---- | ---------------- | ------------------------- |
| {#}  | {specific issue} | {specific fix suggestion} |

### Cross-Cutting Concerns

| Concern        | Status    | Issue    |
| -------------- | --------- | -------- |
| Authorization  | ✅/❌     | {detail} |
| Seed Data      | ✅/❌/N/A | {detail} |
| Data Migration | ✅/❌/N/A | {detail} |
| Performance    | ✅/❌/N/A | {detail} |

### Challenge Prompts for BA Drafters

1. {Specific actionable question with suggested answer}
2. {Specific actionable question with suggested answer}
3. {Specific actionable question with suggested answer}

### AI Verdict

**{APPROVE | REQUEST_REVISION | ESCALATE_TO_LEAD}**
**Reason:** {evidence-based justification}
**Confidence:** {X%} — {what was verified vs. what needs more investigation}

### Decision Record

**Dev BA PIC Decision:** {filled after human review via ask the user directly}
**Vote:** {approve / request-revision / escalate}
**Conditions:** {if any}
**Drafter Response (on revision):** {drafter's response to each challenge prompt — filled when Dev BA PIC re-runs on revised PBI}
**Resolution:** {how each challenge prompt was addressed, deferred, or accepted as known risk}
**Stored at:** `plans/reports/pbi-challenge-{YYMMDD}-{pbi-id}.md` (save output there for audit trail)

Key Rules

• AI provides ANALYSIS, human makes DECISION — Never auto-approve or auto-reject
• Challenge prompts must be specific — Include suggested answers, not just questions
• Domain context required — Always load entity reference + feature docs before analysis
• Technical veto scope — Dev BA PIC CAN veto: architecture feasibility, dependency correctness, cross-service impact, performance, security. CANNOT veto: UI/UX design, visual design, business value (see ba-team-decision-model-protocol.md §2)
• Evidence-based — Every concern raised must cite source (protocol section, entity definition, feature doc)
• Constructive tone — Focus on improving the PBI, not criticizing the drafters

---

Next Steps

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing this skill, you MUST ATTENTION use a direct user question to present these options. Do NOT skip because the task seems "simple" or "obvious" — the user decides:

• "$dor-gate (Recommended)" — If APPROVE: validate DoR before grooming
• "$refine" — If REQUEST_REVISION: BA drafters revise, then re-run $pbi-challenge
• "Escalate to Engineering Manager" — If ESCALATE_TO_LEAD: document concern for technical consultation
• "Skip, continue manually" — user decides

[IMPORTANT] Use task tracking to break ALL work into small tasks BEFORE starting.

Evidence Gate: MANDATORY IMPORTANT MUST ATTENTION — every claim requires file:line proof or traced evidence with confidence percentage (>80% to act).

<!-- SYNC:ai-mistake-prevention -->

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

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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:ui-system-context -->

UI System Context — For ANY task touching .ts, .html, .scss, or .css files:

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MUST ATTENTION READ before implementing:

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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

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

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

<!-- SYNC:ba-team-decision-model -->

BA Team Decision Model — 2/3 majority vote: Dev BA PIC + UX BA + Designer BA per squad. 2 of 3 agree = decision final. 3-way split = escalate to full squad + Tech Leads + Engineering Manager.

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Technical Veto: Dev BA PIC can unilaterally veto on: architecture feasibility, dependency correctness, cross-service impact, performance, security. CANNOT veto: UI/UX design, visual design, business value, user research.

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Rules: Disagree-and-commit after vote. Grooming override requires >75% non-BA squad vote. Record decisions in PBI Validation Summary (member, role, vote, notes).

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Escalation: Tech uncertainty → Engineering Manager. Business value → PO. Design feasibility → UX BA + Designer BA consensus.

<!-- /SYNC:ba-team-decision-model -->

<!-- SYNC:refinement-dor-checklist -->

Refinement DoR Checklist — ALL 7 criteria MUST ATTENTION pass before grooming:

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1. User story template — "As a {role}, I want {goal}, so that {benefit}" format

2. AC testable & unambiguous — GIVEN/WHEN/THEN. No "should/might/TBD/various/appropriate". Min 3 scenarios (happy, edge, error) + 1 auth scenario

3. Wireframes attached — UI features: ## UI Layout with wireframe + components + states + tokens. Backend-only: explicit "N/A"

4. UI design ready — Visual design + component decomposition tree. Backend-only: "N/A"

5. AI pre-review passed — $refine-review or $pbi-challenge returned PASS or WARN (not FAIL)

6. Story points estimated — Fibonacci 1-21 + complexity (Low/Medium/High). >13 SP → recommend split

7. Dependencies table complete — Dependency, Type (must-before/can-parallel/blocked-by/independent), Status

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Failure fixes: Vague AC → specify exact CRUD + roles. Missing auth → add roles × CRUD table. No wireframes → UX BA creates. TBD in AC → replace with decision.

<!-- /SYNC:refinement-dor-checklist -->

<!-- SYNC:estimation-framework -->

Estimation Framework — Bottom-up first; SP DERIVED; output min-max range when likely ≥3d. Stack-agnostic. Baseline: 3-5yr dev, 6 productive hrs/day. AI estimate assumes Claude Code + project context.

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Method:

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1. Blast Radius pass (below) — drives code AND test cost

2. Decompose phases → hours/phase → bottom_up_hours = Σ phase_hours

3. likely_days = ceil(bottom_up_hours / 6) × productivity_factor

4. Sum Risk Margin (base + add-ons) → max_days = likely_days × (1 + margin)

5. min_days = likely_days × 0.9

6. Output as range when likely_days ≥3; single point allowed <3 (still record margin)

7. man_days_ai = same range × AI speedup

8. story_points DERIVED from likely_days via SP-Days — NEVER driver. Disagreement >50% → trust bottom-up

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Productivity factor: 0.8 strong scaffolding+codegen+AI hooks · 1.0 mature default · 1.2 weak patterns · 1.5 greenfield

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Cost Driver Heuristic (apply BEFORE work-type row):

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- UI dominates in CRUD/business apps — 1.5-3x backend (states, validation, responsive, a11y, polish)

- Backend dominates ONLY: multi-aggregate invariants, cross-service contracts, schema migrations, heavy query/perf, new event flows

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Reuse-vs-Create axis (PRIMARY lever, per layer):

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| UI tier | Cost |

| -------------------------------------------- | -------- |

| Reuse component on existing screen | 0.1-0.3d |

| Add control/column to existing screen | 0.3-0.8d |

| Compose components into NEW screen | 1-2d |

| NEW screen, custom layout/states/validation | 2-4d |

| NEW shared/common component (themed, tested) | 3-6d+ |

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| Backend tier | Cost |

| ---------------------------------------------------- | --------- |

| Reuse query/handler from new place | 0.1-0.3d |

| Small update existing handler/entity | 0.3-0.8d |

| NEW query on existing repo/model | 0.5-1d |

| NEW command/handler on existing aggregate (additive) | 1-2d |

| NEW aggregate/entity (repo, validation, events) | 2-4d |

| NEW cross-service contract OR schema migration | 2-4d each |

| Multi-aggregate invariant / heavy domain rule | 3-5d |

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Rule: Sum tiers across UI+backend+tests, apply productivity factor. Reuse short-circuits tiers — call out.

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Test-Scope drivers (compute test_count EXPLICITLY — "+tests" hand-wave is #1 failure):

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| Driver | Count |

| --------------------------------- | ------------------------------------------------------ |

| Happy-path journeys | 1 per story / AC main flow |

| State-machine transitions | reachable transitions × allowed actors |

| Multi-entity state combos | state(A) × state(B) — REACHABLE only, not Cartesian |

| Authorization matrix | (owner, non-owner, elevated, unauth) × each mutation |

| Validation rules | 1 per required field / boundary / format / cross-field |

| UI states (per new screen/dialog) | happy, loading, empty, error, partial — present only |

| Negative paths / invariants | 1 per violatable business rule |

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| Test tier (Trad, incl. setup+assert+flake) | Cost |

| ------------------------------------------ | -------- |

| 1-5 cases, fixtures reused | 0.3-0.5d |

| 6-12 cases, 1 new fixture | 0.5-1d |

| 13-25 cases, multi-entity setup | 1-2d |

| 26-50 cases OR new state-machine coverage | 2-3d |

| >50 cases OR full E2E journey | 3-5d |

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Test multipliers: new fixture/seed harness +0.5d · cross-service/bus assertion +0.3d each · UI E2E ×1.5 · each new role +1-2 cases

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Blast Radius (mandatory pre-pass — affects code AND test):

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1. Files/components directly modified — count

2. Of those, "complex" (>500 LOC, multi-handler, central, frequently-modified) — count

3. Downstream consumers (callers, event subscribers, cross-service) — list

4. Shared/common code touched (multi-app blast) — yes/no

5. Regression scope — areas needing re-test

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Rule: Complex touch → add risk_factors. Each downstream consumer → +1-3 regression cases. Blast >5 areas OR >2 complex → re-evaluate SPLIT before estimating.

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Risk Margin (drives max bound):

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| likely_days | Base margin |

| ------------------- | ------------------------------- |

| <1d trivial | +10% |

| 1-2d small additive | +20% |

| 3-4d real feature | +35% |

| 5-7d large | +50% |

| 8-10d very large | +75% |

| >10d | +100% AND flag SHOULD SPLIT |

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Risk-factor add-ons (additive — enumerate in `risk_factors`):

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| Factor | +margin |

| --------------------------------------------------------------------- | ------- |

| touches-complex-existing-feature (>500 LOC, multi-handler, central) | +20% |

| cross-service-contract change | +25% |

| schema-migration-on-populated-data | +25% |

| new-tech-or-unfamiliar-pattern | +30% |

| regression-fan-out (≥3 downstream areas re-test) | +20% |

| performance-or-latency-critical | +20% |

| concurrency-race-event-ordering | +25% |

| shared-common-code (multi-consumer/multi-app) | +25% |

| unclear-requirements-or-design | +30% |

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Collapse rule: total margin >100% → STOP, split (padding past 2x is dishonesty). Margin <15% on likely_days ≥5 → under-estimated, widen.

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Work-Type Caps (hard ceilings on `likely_days`):

| Work type | Max SP | Max likely |

| --- | --- | --- |

| Single field / config flag / style fix | 1 | 0.5d |

| Add property to existing model + bind to existing UI | 2 | 1d |

| Additive endpoint + minor UI control (button/menu/column), reuses fixtures | 3 | 2-3d |

| Additive endpoint + NEW UI surface OR additive multi-layer + new domain rule + 2+ test files | 5 | 3-5d |

| NEW model/aggregate OR migration OR cross-module contract OR heavy test (>1.5d) OR NEW UI + non-trivial backend | 8 | 5-7d |

| NEW UI surface + (NEW aggregate OR migration OR cross-service contract) | 13 | SHOULD split |

| Cross-service contract + migration combined | 13 | SHOULD split |

| Beyond | 21 | MUST split |

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SP→Days (validation only): 1=0.5d/0.25d · 2=1d/0.35d · 3=2d/0.65d · 5=4d/1.0d · 8=6d/1.5d · 13=10d/2.0d (Trad/AI likely)

AI speedup: SP 1≈2x · 2-3≈3x · 5-8≈4x · 13+≈5x. AI cost = (code_gen × 1.3) + (test_gen × 1.3) (30% review overhead).

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MANDATORY frontmatter:

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```yaml

story_points: <n>

complexity: low | medium | high | critical

man_days_traditional: '<min>-<max>d' # range when likely ≥3d; '<N>d' when <3d

man_days_ai: '<min>-<max>d'

risk_margin_pct: <n> # base + add-ons

risk_factors: [touches-complex-existing-feature, regression-fan-out] # closed-list from add-ons; [] if none

blast_radius:

touched_areas: <n>

complex_touched: <n>

downstream_consumers: [list or count]

shared_common_code: yes | no

estimate_scope_included: [code, integration-tests, frontend, i18n, docs]

estimate_scope_excluded: [unit-tests, e2e, perf, deployment, code-review-rounds]

estimate_reasoning: |

5-7 lines covering:

(a) UI tier — row applied

(b) Backend tier — row applied

(c) Test scope — case breakdown by driver, file count, fixtures, tier row

(d) Cost driver — dominant tier + why

(e) Blast radius — touched, complex, regression scope

(f) Risk factors — list driving margin; why not larger/smaller

Example: "UI: compose Form/Table/Dialog → NEW screen (~1.5d). Backend: NEW command on existing aggregate,

reuses validation+repo (~1d). Tests: 4 transitions × 2 actors + 3 validation + 2 UI states = 13 cases,

1 new fixture → tier 13-25 ~1.5d. Driver: UI composition + new states. Blast: 4 areas, 1 complex.

Risk: base 35% + touches-complex +20% = 55% → max 3.9d → range 2.5-4d."

```

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Sanity self-check:

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- likely_days ≥3d and single-point? → reject, must be range

- Margin <15% on likely_days ≥5d? → under-estimated, widen

- Margin >100%? → STOP, split instead of buffer

- Complex existing feature touched, no regression budget in (c)? → reject

- Blast >5 areas OR >2 complex, no split discussion? → reject

- Purely additive on existing model AND existing UI? → cap SP 3 unless tests >1.5d

- NEW UI surface (page/complex form/dashboard)? → SP 5+ even if backend one endpoint

- Backend cross-service / migration / multi-aggregate? → SP 8+ regardless of UI

- bottom_up_hours / 6 vs SP-Days disagreement >50%? → trust bottom-up, downgrade SP

- Without tests, SP drops ≥1 bucket? → tests dominate; state explicitly

- Reasoning called out UI vs backend vs blast vs risk factors? → if missing, add

<!-- /SYNC:estimation-framework -->

<!-- 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:sequential-thinking-protocol -->

Sequential Thinking Protocol — Structured multi-step reasoning for complex/ambiguous work. Use when planning, reviewing, debugging, or refining ideas where one-shot reasoning is unsafe.

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Trigger when: complex problem decomposition · adaptive plans needing revision · analysis with course correction · unclear/emerging scope · multi-step solutions · hypothesis-driven debugging · cross-cutting trade-off evaluation.

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Format (explicit mode — visible thought trail):

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1. Thought N/M: [aspect] — one aspect per thought, state assumptions/uncertainty

2. Thought N/M [REVISION of Thought K]: ... — when prior reasoning invalidated; state Original / Why revised / Impact

3. Thought N/M [BRANCH A from Thought K]: ... — explore alternative; converge with decision rationale

4. Thought N/M [HYPOTHESIS]: ... then [VERIFICATION]: ... — test before acting

5. Thought N/N [FINAL] — only when verified, all critical aspects addressed, confidence >80%

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Mandatory closers: Confidence % stated · Assumptions listed · Open questions surfaced · Next action concrete.

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Stop conditions: confidence <80% on any critical decision → escalate via ask the user directly · ≥3 revisions on same thought → re-frame the problem · branch count >3 → split into sub-task.

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Implicit mode: apply methodology internally without visible markers when adding markers would clutter the response (routine work where reasoning aids accuracy).

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Deep-dive: see $sequential-thinking skill (.claude/skills/sequential-thinking/SKILL.md) for worked examples (api-design, debug, architecture), advanced techniques (spiral refinement, hypothesis testing, convergence), and meta-strategies (uncertainty handling, revision cascades).

<!-- /SYNC:sequential-thinking-protocol -->

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

• MANDATORY IMPORTANT MUST ATTENTION read frontend-patterns-reference, scss-styling-guide, design-system/README before any UI change.

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

<!-- SYNC:estimation-framework:reminder -->

• MANDATORY MUST ATTENTION estimation: bottom-up phase hours drive man_days_traditional (Σh/6 × productivity_factor); SP DERIVED. UI cost usually dominates — bump SP one bucket if NEW UI surface (page/complex form/dashboard). Frontmatter MUST include story_points, complexity, man_days_traditional, man_days_ai, estimate_scope_included, estimate_scope_excluded, estimate_reasoning (UI vs backend cost driver). Cap SP 3 for additive-on-existing-model+existing-UI unless test scope >1.5d. SP 13 SHOULD split, SP 21 MUST split.

<!-- /SYNC:estimation-framework:reminder -->

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MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

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MUST ATTENTION apply sequential-thinking — multi-step Thought N/M, REVISION/BRANCH/HYPOTHESIS markers, confidence % closer; see $sequential-thinking skill.

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MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

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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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Closing Reminders

MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using task tracking BEFORE starting. MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via a direct user question — 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:

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

[IMPORTANT] Analyze how big the task is and break it into many small todo tasks systematically before starting — this is very important.

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Hookless Prompt Protocol Mirror (Auto-Synced)

Source: .claude/hooks/lib/prompt-injections.cjs + .claude/.ck.json

[WORKFLOW-EXECUTION-PROTOCOL] [BLOCKING] Workflow Execution Protocol — MANDATORY IMPORTANT MUST CRITICAL. Do not skip for any reason.

Generic portability boundary: Reusable skills and protocol text stay project-neutral; project-specific conventions are discovered from docs/project-config.json and docs/project-reference/. Apply shared AI-SDD from shared/sdd-artifact-contract.md. Read docs/project-config.json and docs/project-reference/docs-index-reference.md, then open the project reference docs named there. Any supported AI tool may execute when this shared context and local docs are available.

1. DETECT: Match prompt against workflow catalog 2. ANALYZE: Find best-match workflow AND evaluate if a custom step combination would fit better 3. ASK (REQUIRED FORMAT): Use a direct user question with this structure unless the user explicitly invoked a workflow/skill and the local protocol treats explicit invocation as confirmation:

• Question: "Which workflow do you want to activate?"
• Option 1: "Activate [BestMatch Workflow] (Recommended)"
• Option 2: "Activate custom workflow: [step1 → step2 → ...]" (include one-line rationale)

4. ACTIVATE (if confirmed): Call $workflow-start <workflowId> for standard; sequence custom steps manually 5. CREATE TASKS: task tracking for ALL workflow steps 6. EXECUTE: Follow each step in sequence [CRITICAL-THINKING-MINDSET] Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination principle: 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 Attention principle (Primacy-Recency): Put the 3 most critical rules at both top and bottom of long prompts/protocols so instruction adherence survives long context windows. Goal-driven execution: Define success criteria first, loop until verified, and stop only when observable checks pass. Tests verify intent: Tests must protect business rules/invariants and fail when the protected intent breaks, not only mirror current behavior.

[LESSON-LEARNED-REMINDER] [BLOCKING] Task Planning & Continuous Improvement — MANDATORY. Do not skip.

Break work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned".

Extract lessons — ROOT CAUSE ONLY, not symptom fixes:

1. Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value". 2. Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up. 3. Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase. 4. Consolidate: multiple mistakes sharing one failure mode → ONE lesson. 5. Recurrence gate: "Would this recur in future session WITHOUT this reminder?" — No → skip $learn. 6. Auto-fix gate: "Could $code-review/$code-simplifier/$security/$lint catch this?" — Yes → improve review skill instead. 7. BOTH gates pass → ask user to run $learn. [TASK-PLANNING] [MANDATORY] BEFORE executing any workflow or skill step, create/update task tracking for all planned steps, then keep it synchronized as each step starts/completes.

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