[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set in_progress when step starts, set completed when step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.

Quick Summary

Goal: 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

Approach	Pros	Cons	Decision
Extend `/refine-review` with a reviewer-role flag	No new skill, single codebase	Drafter runs it themselves in practice; role separation breaks down without enforcement	Rejected — role separation requires a distinct invocation point owned by a different person
Fully autonomous AI verdict (no human decision)	Faster, no Dev BA PIC scheduling needed	Automation bias: AI wrong on domain specifics propagates unchecked; no human accountability for false APPROVE	Rejected — cost of false APPROVE on infeasible PBIs exceeds review time saved
Static DoR checklist given to Dev BA PIC (no AI)	Simple, no AI dependency	No domain entity context loading, no AC vagueness flagging; manual effort is high and inconsistent across reviewers	Rejected — AI domain lookup provides non-trivial value for cross-service entity detection
Async comment-thread model (AI generates questions posted as ticket comments)	Eliminates scheduling bottleneck; drafter can research before responding	Slower feedback loop; requires external ticket integration	Valid alternative for async teams; prefer if Dev BA PIC availability is chronically a bottleneck

Risk Assessment

Risk	Likelihood	Impact	Mitigation
Automation bias — Dev BA PIC rubber-stamps AI verdict without independent assessment	High	High	Workflow Step 7 shows challenge prompts BEFORE the verdict — Dev BA PIC forms their own view first
Module misdetection — AI loads wrong domain context, produces entity conflict analysis for wrong service	Medium	High	Workflow Step 2 confirms detected module with Dev BA PIC via AskUserQuestion before proceeding
Challenge prompts ignored — Drafter revises PBI superficially to satisfy reviewer without resolving root gaps	Medium	Medium	Decision Record includes drafter-response field; Dev BA PIC re-runs skill on revision, not just reads revised PBI
Suggested answers create adoption pressure — Drafter adopts suggested answer rather than reasoning independently	Medium	Medium	Suggested answers framed as "consider whether X" options, not corrections; language review in challenge prompt templates
3-way BA vote deadlock — UX BA, Designer BA, Dev BA PIC all disagree	Low	Medium	Escalation path per `ba-team-decision-model`: Engineering Manager for tech uncertainty, PO for business value

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

Locate PBI draft — Find BA drafters' draft PBI in team-artifacts/pbis/ or path provided by user
Load domain context — Auto-detect module from PBI content. MANDATORY: Use AskUserQuestion 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
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?)
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
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.
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"
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)
AskUserQuestion — 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)

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 AskUserQuestion}
**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 AskUserQuestion 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 TaskCreate 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).

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.

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

MUST ATTENTION READ before implementing:

docs/project-reference/frontend-patterns-reference.md — component base classes, stores, forms

docs/project-reference/scss-styling-guide.md — BEM methodology, SCSS variables, mixins, responsive

docs/project-reference/design-system/README.md — design tokens, component inventory, icons

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

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.

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.

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

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

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

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

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

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

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

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

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

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

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.

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.

Method:

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

Decompose phases → hours/phase → bottom_up_hours = Σ phase_hours

likely_days = ceil(bottom_up_hours / 6) × productivity_factor

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

min_days = likely_days × 0.9

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

man_days_ai = same range × AI speedup

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

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

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

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

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

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+

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

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

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

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

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

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

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

Files/components directly modified — count

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

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

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

Regression scope — areas needing re-test

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

Risk Margin (drives max bound):

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

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

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%

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

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

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).

MANDATORY frontmatter:
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."
Sanity self-check:

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

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.

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.

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.

Format (explicit mode — visible thought trail):

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

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

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

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

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

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

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

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

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).

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

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.

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

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

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

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

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:

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

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

name	pbi-challenge
version	1.0.0
description	[Code Quality] Use when you need aI-assisted Dev BA PIC review of PBI drafts.