idea

name	idea
description	[Project Management] Use when capturing new ideas, feature requests, or concepts for future refinement.

Codex compatibility note:

• Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.
• Prefer the plan-hard skill for planning guidance in this Codex mirror.
• 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 (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.

[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: Capture raw product ideas as structured backlog artifacts with project module context.

MANDATORY IMPORTANT MUST ATTENTION task tracking task to READ project-specific reference doc: project-structure-reference.md — project patterns and structure. Not found → search: project documentation, coding standards, architecture docs.

Workflow:

1. Gather Info — Ask problem, value, scope, target users
2. Generate Artifact — Create idea file with ID (IDEA-YYMMDD-NNN) + draft status
3. Detect Module — Auto-match project module, load feature context from docs
4. Discovery Interview — a direct user question 3-5 structured questions (MANDATORY)
5. Validate — Confirm problem statement, scope, stakeholders (MANDATORY)
6. Suggest Next — Point to $refine for PBI creation

Key Rules:

• Output: team-artifacts/ideas/{YYMMDD}-{role}-idea-{slug}.md
• Validation NEVER optional — MANDATORY step
• Auto-detect module silently; prompt only when ambiguous
• MUST ATTENTION include t_shirt_size (XS/S/M/L/XL) in artifact for early sizing

Greenfield Mode

Auto-detected: No codebase found (no src/, app/, lib/, server/, packages/ dirs; no package.json/*.sln/go.mod; no project-config.json) → greenfield mode. Planning artifacts (docs/, plans/, .claude/) don't count — project must have actual code dirs with content.

When greenfield detected:

1. Skip module auto-detection (no modules exist yet)
2. Skip project-structure-reference.md read (won't exist)
3. Focus broader problem-space: market gap, competitors, differentiation
4. Output tech-agnostic problem statement
5. Enable WebSearch for market/competitor context
6. Increase a direct user question frequency — capture vision, constraints, team profile, scale expectations
7. [CRITICAL] NEVER ask about tech stack during idea capture. Tech stack = research-driven decision AFTER full business analysis (business-evaluation phase). User volunteers preference → acknowledge but defer to tech stack research phase.

Detailed Workflow

Step 1: Gather Information

• No title → ask: "What's the idea in one sentence?"
• Ask: "What problem does this solve?"
• Ask: "Who benefits from this?"
• Ask: "Any initial scope thoughts?"

Step 2: Generate Artifact

• Template: .claude/docs/team-artifacts/templates/idea-template.md
• ID: IDEA-{YYMMDD}-{NNN} (sequential)
• Status: draft

Step 3: Capture Details

• Document problem statement, expected value, target users

Step 4: Detect Project Module

Dynamic Discovery:

1. Run: Glob("docs/business-features/*/README.md")
2. Extract module names from paths
3. Match idea keywords against module keywords

Scenario	Action
Clear match	Auto-detect — NEVER show confidence levels
Ambiguous / no match	Prompt: "Which project module?" + Glob results + "Cross-cutting/Infrastructure"
2+ modules detected	Load ALL modules, add all to related_features

If module detected:

1. Read docs/business-features/{module}/README.md (first 200 lines)
2. Extract feature list from Quick Navigation section
3. Add to frontmatter: module: {detected_module}, related_features: [Feature1, Feature2]

Step 5: Load Feature Context

1. Read module README overview (~2K tokens)
2. Identify closest matching feature(s)
3. Read corresponding feature doc (3-5K tokens)
4. Extract: related entities, existing business rules (BR-{MOD}-XXX), test case patterns (TC-{FEATURE}-{NNN})

Token Budget: Target 8-12K tokens total.

Step 6: Save Artifact

• Path: team-artifacts/ideas/{YYMMDD}-{role}-idea-{slug}.md
• Role: infer from context or ask
• Include domain context if detected

Step 6.5: Discovery Interview (MANDATORY)

Use a direct user question — 3-5 structured questions. Each MUST ATTENTION have 2-4 options with one marked "(Recommended)".

Category	Purpose	Example
Problem Clarity	Distinguish problem from solution	"What problem does this solve?" + options
User Persona	Identify primary user	"Who benefits most?" + role options
Scope	MVP vs full vision	"What's smallest valuable version?"
Testability	Define done?	"How would you verify this works?"
Impact	Business value sizing	"How many users/processes affected?"
Constraints	Known blockers	"Any technical/business constraints?"
Scale	Expected load/growth	"How many users/transactions expected?"

Greenfield: NEVER include tech stack questions. Focus on business problem, users, scale, constraints.

Testability Question (ALWAYS include): "How would you verify this feature works correctly?" — Options: manual test steps, automated test criteria, metric thresholds.

Document all answers under ## Discovery Interview.

Step 7: Validate Idea (MANDATORY)

a direct user question — 2-3 validation questions:

Category	Example Question
Problem	"Is the problem statement clear and user-focused?"
Value	"What's the expected business value or user benefit?"
Scope	"Any scope boundaries to clarify now?"
Stakeholders	"Who else should review this idea?"

Document under ## Validation Summary. Update artifact based on answers.

Validation Output Format:

## Validation Summary

**Validated:** {date}

### Confirmed

- {decision}: {user choice}

### Action Items

- [ ] {follow-up if any}

Step 8: Suggest Next Step

a direct user question after capture:

1. $refine — Refine into PBI (Recommended)
2. $tdd-spec — Jump straight to test spec
3. $plan-hard — Start implementation planning

Output: "Idea captured! To refine into a PBI, run: $refine {filename}" Module detected: "Module context from {module} will be used during refinement."

Output Formats

Domain Context Section

## Domain Context (Project Features)

### Module

{module_name}

### Related Features

- {Feature1} - [docs link]
- {Feature2} - [docs link]

### Domain Entities

- **Primary:** {Entity1}, {Entity2}
- **Related:** {Entity3}

### Existing Business Rules

- BR-{MOD}-XXX: {Brief description}

UI Sketch Section

## UI Sketch

### Layout

{Rough ASCII wireframe — see UI wireframe protocol}

### Key Components

- **{Component}** — {purpose} _(tier: common | domain-shared | page/app)_

Search existing libs before proposing new components. Backend-only idea: ## UI Sketch → N/A — Backend-only change. No UI affected.

Examples

$idea "Dark mode toggle for settings"
# Creates: team-artifacts/ideas/260119-po-idea-dark-mode-toggle.md

$idea "Add goal progress tracking notification"
# Creates with module context: team-artifacts/ideas/260119-po-idea-goal-progress-notification.md

---

Workflow Recommendation

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS: Not already in workflow → MUST ATTENTION use a direct user question:

1. Activate idea-to-pbi workflow (Recommended) — idea → refine → refine-review → story → story-review → prioritize
2. Execute $idea directly — run standalone

---

Next Steps

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing skill, use a direct user question:

• "$refine (Recommended)" — Transform idea into actionable PBI
• "$web-research" — Idea needs market research first
• "Skip, continue manually" — user decides

---

[IMPORTANT] task tracking break ALL work into small tasks BEFORE starting — including tasks each file read. Simple tasks: AI MUST ATTENTION ask user whether to skip.

External Memory: Complex/lengthy work (research, analysis, scan, review) → write intermediate findings to plans/reports/ — prevents context loss, serves as deliverable.

Evidence Gate: MANDATORY IMPORTANT MUST ATTENTION — every claim, finding, recommendation requires file:line proof or traced evidence, confidence percentage (>80% act, <80% verify first).

UI Wireframe — Process visual design input (Figma URLs, screenshots, wireframes) via appropriate tool BEFORE creating wireframes. Use box-drawing ASCII characters for spatial layout. Classify every component into exactly ONE tier: Common (cross-app reusable) / Domain-Shared (cross-domain) / Page (single-page). Duplicate UI code = wrong tier. Search existing component libraries before creating new (>=80% match = reuse). Detail level varies by skill (idea=rough, story=full decomposition).

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.

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):

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%

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

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.

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).

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

IMPORTANT MUST ATTENTION task tracking break ALL work into small tasks BEFORE starting IMPORTANT MUST ATTENTION validate all decisions with user via a direct user question — NEVER auto-decide IMPORTANT MUST ATTENTION Discovery Interview + Validation NEVER optional — MANDATORY steps IMPORTANT MUST ATTENTION NEVER ask about tech stack in greenfield mode — defer to business-evaluation phase IMPORTANT MUST ATTENTION auto-detect module silently — prompt only when ambiguous IMPORTANT MUST ATTENTION add final review task to verify work quality

Anti-Rationalization:

Evasion	Rebuttal
"Idea is simple, skip interview"	NEVER skip — discovery uncovers hidden constraints
"Module is obvious, skip detection"	Still run Glob() — confirm with evidence not assumption
"Validation is redundant after interview"	ALWAYS run both — different question categories
"Greenfield check is optional"	Auto-detect is MANDATORY — no manual override

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

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.

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:
   • 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.

Learned Lessons

Lessons Learned

[CRITICAL] Hard-won project debugging/architecture rules. MUST ATTENTION apply BEFORE forming hypothesis or writing code.

Quick Summary

Goal: Prevent recurrence of known failure patterns — debugging, architecture, naming, AI orchestration, environment.

Top Rules (apply always):

• MUST ATTENTION verify ALL preconditions (config, env, DB names, DI regs) BEFORE code-layer hypothesis
• MUST ATTENTION fix responsible layer — NEVER patch symptom sites with caller-specific defensive code
• MUST ATTENTION use ExecuteInjectScopedAsync for parallel async + repo/UoW — NEVER ExecuteUowTask
• MUST ATTENTION name by PURPOSE not CONTENT — adding member forces rename = abstraction broken
• MUST ATTENTION persist sub-agent findings incrementally after each file — NEVER batch at end
• MUST ATTENTION Windows bash: verify Python alias (where python/where py) — NEVER assume python/python3 resolves

---

Debugging & Root Cause Reasoning

• [2026-04-11] Holistic-first: verify environment before code. Failure → list ALL preconditions (config, env vars, DB names, endpoints, DI regs, credentials, permissions, data prerequisites) → verify each via evidence (grep/cat/query) BEFORE code-layer hypothesis. Worst rabbit holes: diving nearest layer while bug sits elsewhere — e.g., hours debugging "sync timeout", real cause: test appsettings pointing wrong DB. Cheapest check first.
• [2026-04-01] Ask "whose responsibility?" before fixing. Trace: bug in caller (wrong data) or callee (wrong handling)? Fix responsible layer — NEVER patch symptom site masking real issue.
• [2026-04-01] Trace data lifecycle, not error site. Follow data: creation → transformation → consumption. Bug usually where data created wrong, not consumed.
• [2026-04-01] Code is caller-agnostic. Functions/handlers/consumers don't know who invokes them. Comments/guards/messages describe business intent — NEVER reference specific callers (tests, seeders, scripts).

Architecture Invariants

• [2026-03-31] ParallelAsync + repo/UoW MUST use ExecuteInjectScopedAsync, NEVER ExecuteUowTask. ExecuteUowTask creates new UoW but reuses outer DI scope (same DbContext) — parallel iterations sharing non-thread-safe DbContext silently corrupt data. ExecuteInjectScopedAsync creates new UoW + new DI scope (fresh repo per iteration).
• [2026-03-31] Bus message naming MUST include service name prefix — core services NEVER consume feature events. Prefix declares schema ownership (AccountUserEntityEventBusMessage = Accounts owns). Core services (Accounts, Communication) are leaders. Feature services (Growth, Talents) sending to core MUST use {CoreServiceName}...RequestBusMessage — never define own event for core to consume.

Naming & Abstraction

• [2026-04-12] Name PURPOSE not CONTENT — "OrXxx" anti-pattern. HrManagerOrHrOrPayrollHrOperationsPolicy names set members, not what it guards. Add role → rename = broken abstraction. Rule: names express DOES/GUARDS, not CONTAINS. Test: adding/removing member forces rename? YES = content-driven = bad → rename to purpose (e.g., HrOperationsAccessPolicy). Nuance: "Or" fine in behavioral idioms (FirstOrDefault, SuccessOrThrow) — expresses HAPPENS, not membership.

Environment & Tooling

• [2026-04-20] Windows bash: NEVER assume python/python3 resolves — verify alias first. Python may not be in bash PATH under those names. Check: where python / where py. Prefer py (Windows Python Launcher) for one-liners, node if JS alternative exists.

Test-specific lessons → docs/project-reference/integration-test-reference.md Lessons Learned section. Production-code anti-patterns → docs/project-reference/backend-patterns-reference.md Anti-Patterns section. Generic debugging/refactoring reminders → System Lessons in .claude/hooks/lib/prompt-injections.cjs.

---

Closing Reminders

• IMPORTANT MUST ATTENTION holistic-first: verify ALL preconditions (config, env, DB names, endpoints, DI regs) BEFORE code-layer hypothesis — cheapest check first
• IMPORTANT MUST ATTENTION fix responsible layer — NEVER patch symptom site; trace caller (wrong data) vs callee (wrong handling), fix root owner
• IMPORTANT MUST ATTENTION parallel async + repo/UoW → ALWAYS ExecuteInjectScopedAsync, NEVER ExecuteUowTask (shared DbContext = silent data corruption)
• IMPORTANT MUST ATTENTION bus message prefix = schema ownership; feature services NEVER define events for core services — use {CoreServiceName}...RequestBusMessage
• IMPORTANT MUST ATTENTION name by PURPOSE — adding/removing member forces rename = broken abstraction
• IMPORTANT MUST ATTENTION sub-agents MUST write findings after each file/section — NEVER batch all findings into one final write
• IMPORTANT MUST ATTENTION Windows bash: NEVER assume python/python3 resolves — run where python/where py first, use py launcher or node

[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.