workflow-product-discovery

name	workflow-product-discovery
description	[Workflow] Use when activating the Product Discovery workflow for turning raw opportunities into ranked PBIs.
disable-model-invocation	true

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.

Quick Summary

Goal: [Workflow] Trigger Product Discovery workflow — raw vision or problem → structured brainstorm → prioritized opportunity map → N PBIs with stories, challenge review, DoR gate, and wireframes → cross-PBI ranked backlog ready for sprint planning.

Workflow:

1. Detect — classify request scope and target artifacts.
2. Execute — apply required steps with evidence-backed actions.
3. Verify — confirm constraints, output quality, and completion evidence.

Key Rules:

• MUST ATTENTION keep claims evidence-based (file:line) with confidence >80% to act.
• MUST ATTENTION keep task tracking updated as each step starts/completes.
• NEVER skip mandatory workflow or skill gates.

When to Use

• PO/BA has a raw product vision, big problem statement, or "we need to build X" starting point
• Team needs to go from zero to a grooming-ready backlog for sprint planning
• Strategic product initiative needs to be broken down into implementable PBIs
• Existing product needs a discovery sprint to generate new feature opportunities

When NOT to Use

• Single well-defined feature → use feature or idea-to-pbi
• Implementation work (code writing) → use feature or big-feature
• Bug fixes → use bugfix
• Research only, no PBI output needed → use investigation or deep-research

Key Mechanics

0. Task Decomposition Gate (MANDATORY — Runs After Brainstorm, Before First $idea)

After the opportunity map is produced and the user selects which opportunities to develop, STOP and call task tracking for every upcoming unit of work before processing any opportunity:

Formula: N opportunities × 8 steps = N×8 tasks. For 5 opportunities: 40 tasks.

Per-opportunity task set:

Task tracking: "Opportunity {#}: Idea capture — {opportunity-slug}"
Task tracking: "Opportunity {#}: PBI refinement — {opportunity-slug}"
Task tracking: "Opportunity {#}: PBI review — {opportunity-slug}"
Task tracking: "Opportunity {#}: User stories — {opportunity-slug}"
Task tracking: "Opportunity {#}: Story review — {opportunity-slug}"
Task tracking: "Opportunity {#}: Challenge review — {opportunity-slug}"
Task tracking: "Opportunity {#}: DoR gate — {opportunity-slug}"
Task tracking: "Opportunity {#}: Mockup — {opportunity-slug}" [skip if backend-only]

Plus: Task tracking: "Cross-PBI prioritization (final step)" — one task at the end.

Context Window Management:

• Write each artifact immediately after completing its task — never batch
• For 6+ opportunities, use sub-agent parallel processing:
  • Spawn one sub-agent per opportunity with its task list and brainstorm context
  • Each sub-agent runs idea → mockup and writes artifacts to team-artifacts/pbis/
  • Main context runs $prioritize across all completed PBIs at the end
• After every 3 opportunities completed, update the session summary table

1. Brainstorm → Opportunity Map

The $brainstorm step is the engine. It uses the Double Diamond process:

• Problem framing: POV statement, 5 Whys / Fishbone, JTBD job stories, HMW questions
• Opportunity framing: Opportunity Solution Tree (enhancement) OR Lean Canvas (new product)
• Ideation: SCAMPER, Crazy 8s, Impact Mapping — target 25–40 raw ideas
• Convergence: RICE scoring, Kano classification, 2×2 Effort/Impact, MoSCoW

Output: A scored opportunity map with 3–8 ranked items. AI presents the map and asks: "Which opportunities should we develop into PBIs?" (multi-select).

2. Why-Review Gate (After domain-analysis, Before per-opportunity loop)

Before committing to the per-PBI loop, validate the opportunity map rationale with $why-review:

Challenge prompts:

• Are the top-ranked opportunities truly the right problems to solve? What was deprioritized and why?
• Are RICE scores well-founded or speculative? Challenge Reach and Impact estimates independently.
• Pre-mortem: if these opportunities are built and miss in 6 months, what was the root cause?
• Are there systemic alternatives (platform change, process change) that make these opportunities unnecessary?

Result	Action
PASS	Proceed to per-opportunity loop
WARN	Document risk, acknowledge with user, proceed
FAIL on high-ranked opportunity	Remove from selection or revisit brainstorm framing

3. Multi-Opportunity Loop

For each selected opportunity, the following steps run in sequence:

Step	Purpose	Output
$idea	Capture as structured artifact	team-artifacts/ideas/{date}-po-idea-{slug}.md
$refine	PBI with hypothesis, AC (GIVEN/WHEN/THEN), RICE	team-artifacts/pbis/{date}-pbi-{slug}.md
$refine-review	BA quality check on PBI	Reviewed PBI
$story	User stories per PBI	Stories in PBI artifact
$story-review	Story quality and completeness check	Reviewed stories
$pbi-challenge	Dev BA PIC review — challenge prompts, AC quality, feasibility	Challenge log
$dor-gate	INVEST check — PASS/WARN/FAIL	DoR result
$pbi-mockup	ASCII wireframe (skip for backend-only)	Mockup in PBI

Track progress: After each opportunity loop, AI updates a session summary table in the plan dir.

5. Cross-PBI Prioritize

After all loops complete, $prioritize aggregates all PBIs:

• Cross-PBI RICE ranking
• Dependency graph (which PBIs must come before others)
• Release scope (Must-Have / Should-Have / Could-Have)
• Output: team-artifacts/backlog/product-discovery-{date}-backlog.md

6. Handoff

At $workflow-end, AI presents:

• Session summary: N PBIs created, X passed DoR, Y need rework
• Ranked backlog with RICE scores
• Recommended next step: /sprint-planning (backlog ready) or /big-feature (single large PBI needs deep research + implementation)
• Blocked PBIs: list DoR failures with specific blocking items

Conditional Skip Rules

Step	Skip When
$web-research	Internal tool, well-understood domain, user says "skip market research"
$domain-analysis	No new domain entities or aggregates involved
$why-review	User has already validated opportunity rationale; no alternatives available
$pbi-mockup (per PBI)	PBI is backend-only — no UI changes

---

IMPORTANT MANDATORY Steps: $brainstorm -> $web-research -> $domain-analysis -> $why-review -> $idea -> $refine -> $why-review -> $refine-review -> $story -> $why-review -> $story-review -> $pbi-challenge -> $dor-gate -> $pbi-mockup -> $review-changes -> $prioritize -> $watzup -> $workflow-end

IMPORTANT MANDATORY Steps: $brainstorm -> $web-research -> $domain-analysis -> $why-review -> $idea -> $refine -> $why-review -> $refine-review -> $story -> $why-review -> $story-review -> $pbi-challenge -> $dor-gate -> $pbi-mockup -> $review-changes -> $prioritize -> $watzup -> $workflow-end

[BLOCKING] Each step MUST ATTENTION invoke its skill invocation — marking a task completed without skill invocation is a workflow violation. NEVER batch-complete validation gates.

Activate the product-discovery workflow. Run $workflow-start product-discovery with the user's prompt as context.

Steps: $brainstorm → $web-research → $domain-analysis → $why-review → [TASK DECOMPOSITION GATE] Create task tracking for every opportunity × step BEFORE looping → [loop per opportunity] $idea → $refine → $refine-review → $story → $story-review → $pbi-challenge → $dor-gate → $pbi-mockup → $review-changes → $prioritize → $watzup → $workflow-end

Scale awareness: This workflow can generate 8 opportunities × 8 steps = 64 artifact units plus a ranked backlog. Use the Task Decomposition Gate and incremental-write patterns to prevent context overrun. For 6+ opportunities, use sub-agent parallel processing (one sub-agent per opportunity, main context assembles at $prioritize).

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.

Nested Task Expansion Contract — For workflow-step invocation, the [Workflow] ... row is only a parent container; the child skill still creates visible phase tasks.

1. Call the current task list first. If a matching active parent workflow row exists, set nested=true and record parentTaskId; otherwise run standalone.
2. Create one task per declared phase before phase work. When nested, prefix subjects [N.M] $skill-name — phase.
3. When nested, link the parent with TaskUpdate(parentTaskId, addBlockedBy: [childIds]).
4. Orchestrators must pre-expand a child skill's phase list and link the workflow row before invoking that child skill or sub-agent.
5. Mark exactly one child in_progress before work and completed immediately after evidence is written.
6. Complete the parent only after all child tasks are completed or explicitly cancelled with reason.

Blocked until: the current task list done, child phases created, parent linked when nested, first child marked in_progress.

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.

Incremental Result Persistence — MANDATORY for all sub-agents or heavy inline steps processing >3 files.

1. Before starting: Create report file plans/reports/{skill}-{date}-{slug}.md
2. After each file/section reviewed: Append findings to report immediately — never hold in memory
3. Return to main agent: Summary only (per SYNC:subagent-return-contract) with Full report: path
4. Main agent: Reads report file only when resolving specific blockers

Why: Context cutoff mid-execution loses ALL in-memory findings. Each disk write survives compaction. Partial results are better than no results.

Report naming: plans/reports/{skill-name}-{YYMMDD}-{HHmm}-{slug}.md

Sub-Agent Return Contract — When this skill spawns a sub-agent, the sub-agent MUST return ONLY this structure. Main agent reads only this summary — NEVER requests full sub-agent output inline.

## Sub-Agent Result: [skill-name]

Status: ✅ PASS | ⚠️ PARTIAL | ❌ FAIL
Confidence: [0-100]%

### Findings (Critical/High only — max 10 bullets)

- [severity] [file:line] [finding]

### Actions Taken

- [file changed] [what changed]

### Blockers (if any)

- [blocker description]

Full report: plans/reports/[skill-name]-[date]-[slug].md

Main agent reads Full report file ONLY when: (a) resolving a specific blocker, or (b) building a fix plan. Sub-agent writes full report incrementally (per SYNC:incremental-persistence) — not held in memory.

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

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

• MANDATORY Parent workflow rows do not replace child phase tracking; expand phases and link the parent when nested.
• MANDATORY Orchestrators pre-expand child skill phases before invocation; use [N.M] $skill-name — phase prefixes and one-in_progress discipline.

Closing Reminders

• MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using task tracking BEFORE starting — one task per opportunity × step
• MANDATORY IMPORTANT MUST ATTENTION brainstorm output MUST produce a scored opportunity map before any $idea step
• MANDATORY IMPORTANT MUST ATTENTION why-review runs after domain-analysis — FAIL removes opportunity from selection, WARN requires user acknowledgment
• MANDATORY IMPORTANT MUST ATTENTION repeat idea→pbi chain for EACH selected opportunity — not just once
• MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via a direct user question — never auto-select opportunities
• MANDATORY IMPORTANT MUST ATTENTION $prioritize runs ONCE at the end across ALL PBIs, not per-opportunity
• MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify all PBIs and backlog artifact

[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.

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.