scout

name	scout
description	[Investigation] Use when quickly locating relevant files and affected areas across a large codebase.

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: Fast, parallel codebase file discovery to locate all files relevant to a task.

Workflow:

1. Phase 0: Classify — Detect search scope (backend/frontend/both) + keyword type
2. Analyze Request — Extract entity names, feature keywords, file types from prompt
3. Parallel Search — Spawn agents searching backend core, backend infra, frontend paths
4. Graph Expand (MANDATORY — DO NOT SKIP) — MUST ATTENTION run graph commands on 2-3 key files. Graph reveals complete dependency network grep CANNOT find.
5. Low-Result Check — If <5 files returned, re-examine keywords and run second pass
6. Synthesize — Combine grep + graph into numbered, prioritized file list

Key Rules:

• Speed over depth — return file paths only, no content analysis
• Target 3-5 minutes total; 3-minute timeout per agent
• NEVER skip graph expansion when .code-graph/graph.db exists

Scout — Fast Codebase File Discovery

---

Phase 0: Classify Search Scope

Before spawning agents, classify the request:

Scope	Detection	Agent Strategy
Backend-only	C# class names, domain entities, API handlers	Agents 1+2, skip Agent 3
Frontend-only	Component names, TypeScript, Angular features	Agent 3 only
Full-stack	Feature name spanning both layers	All 3 agents
Unknown	Ambiguous prompt	Default to all 3 agents

Think: Does prompt mention a specific layer? Does entity exist in backend, frontend, or both? Adjust agent count — avoid spawning unnecessary agents.

---

When to Use

• Quickly locating relevant files across large codebase
• Beginning work on features spanning multiple directories
• Before changes affecting multiple parts
• Mapping file landscape before investigation or implementation

NOT for: Deep code analysis (→ feature-investigation), debugging (→ debug-investigate), implementation (→ feature-implementation).

---

Workflow

Step 1: Analyze Search Request

Extract from USER_PROMPT:

• Entity names (User, Customer, Order)
• Feature names (authentication, notification)
• File types needed (backend, frontend, or both)

Step 2: Execute Parallel Search

Spawn SCALE number of scout subagents in parallel via spawn_agent tool (agent_type: "scout").

WHY scout not Explore: Custom scout agents read .claude/agents/scout.md — includes graph CLI knowledge + Bash access. Built-in Explore agents have NO graph awareness.

Agent Distribution

• Agent 1 - Backend Core: src/Services/*/Domain/, src/Services/*/UseCaseCommands/, src/Services/*/UseCaseQueries/
• Agent 2 - Backend Infra: src/Services/*/UseCaseEvents/, src/Services/*/Controllers/, src/Services/*/BackgroundJobs/
• Agent 3 - Frontend: {frontend-apps-dir}/, {frontend-libs-dir}/{domain-lib}/, {frontend-libs-dir}/{common-lib}/

Per agent: 3-minute timeout. Return file paths only — no content analysis. Use Glob (patterns), Grep (content), Bash (graph CLI).

Step 3: Graph Expand (MANDATORY — DO NOT SKIP)

YOU (main agent) MUST ATTENTION run graph commands YOURSELF after sub-agents return. NOT optional — without graph, results are incomplete. Sub-agents cannot use graph — only main agent can.

# Check graph exists
ls .code-graph/graph.db 2>/dev/null && echo "GRAPH_AVAILABLE" || echo "NO_GRAPH"

If GRAPH_AVAILABLE, pick 2-3 key files from sub-agent results (entities, commands, bus messages):

# Full dependency network of key file
python .claude/scripts/code_graph connections <key_file> --json

# All callers of key command/handler
python .claude/scripts/code_graph query callers_of <FunctionName> --json

# All importers of bus message class
python .claude/scripts/code_graph query importers_of <file_path> --json

# Batch query multiple files (most efficient)
python .claude/scripts/code_graph batch-query <file1> <file2> <file3> --json

# If graph returns "ambiguous" — disambiguate first
python .claude/scripts/code_graph search <keyword> --kind Function --json

# Trace shortest path between two nodes
python .claude/scripts/code_graph find-path <source_qn> <target_qn> --json

# Filter by service, limit results
python .claude/scripts/code_graph query callers_of <name> --limit 5 --filter "ServiceName" --json

Grep-First Discovery (semantic queries): When prompt describes behavior/flow (not specific file), grep key terms FIRST to discover entry files, then use those as graph input:

1. Grep class names, commands, handlers, endpoints
2. Use discovered files as input to connections, batch-query, or trace
3. Use trace --direction both on middle files (controllers, commands) for full upstream + downstream

Graph results get HIGHER priority than grep — structural relationships > text matches. After graph expansion, grep again to verify content in discovered files.

Step 4: Low-Result Check

If total files found <5 after Steps 2-3:

1. Re-examine keywords — too specific? Try broader synonyms
2. Spawn second scout agent with alternate search terms
3. Try python .claude/scripts/code_graph search <keyword> --json to find nodes by name

Step 5: Synthesize Results

Combine grep + graph into numbered, prioritized file list (see Results Format).

---

Search Patterns by Priority

# HIGH PRIORITY - Core Logic
**/Domain/Entities/**/*{keyword}*.cs
**/UseCaseCommands/**/*{keyword}*.cs
**/UseCaseQueries/**/*{keyword}*.cs
**/UseCaseEvents/**/*{keyword}*.cs
**/*{keyword}*.component.ts
**/*{keyword}*.store.ts

# MEDIUM PRIORITY - Infrastructure
**/Controllers/**/*{keyword}*.cs
**/BackgroundJobs/**/*{keyword}*.cs
**/*Consumer*{keyword}*.cs
**/*{keyword}*-api.service.ts

# LOW PRIORITY - Supporting
**/*{keyword}*Helper*.cs
**/*{keyword}*Service*.cs
**/*{keyword}*.html

---

Graph Intelligence (MANDATORY when graph.db exists)

---

Results Format

## Scout Results: {USER_PROMPT}

### High Priority - Core Logic

1. `src/Services/{Service}/Domain/Entities/{Entity}.cs`
2. `src/Services/{Service}/UseCaseCommands/{Feature}/Save{Entity}Command.cs`
   ...

### Medium Priority - Infrastructure

10. `src/Services/{Service}/Controllers/{Entity}Controller.cs`
11. `src/Services/{Service}/UseCaseEvents/{Feature}/SendNotificationOn{Entity}CreatedEventHandler.cs`
    ...

### Low Priority - Supporting

20. `src/Services/{Service}/Helpers/{Entity}Helper.cs`
    ...

### Frontend Files

30. `{frontend-libs-dir}/{domain-lib}/src/lib/{feature}/{feature}-list.component.ts`
    ...

**Total Files Found:** {count}
**Search Completed In:** {time}

### Suggested Starting Points

1. `{most relevant file}` - {reason}
2. `{second most relevant}` - {reason}

### Unresolved Questions

- {any questions that need clarification}

---

Quality Standards

Standard	Expectation
Speed	Complete in 3-5 minutes
Accuracy	Return only relevant files
Coverage	Search all likely directories
Efficiency	Minimize tool calls
Structure	Always use numbered, prioritized lists

---

Workflow Recommendation

MANDATORY MUST ATTENTION — NO EXCEPTIONS: If NOT already in workflow, MUST ATTENTION use a direct user question to ask user:

1. Activate investigation workflow (Recommended) — scout → investigate
2. Execute $scout directly — run this skill standalone

---

Next Steps

MANDATORY MUST ATTENTION — NO EXCEPTIONS after completing, MUST ATTENTION use a direct user question to present:

• "$investigate (Recommended)" — Deep-dive into discovered files
• "$plan-hard" — If scouted files sufficient to start planning
• "Skip, continue manually" — user decides

---

[IMPORTANT] Use task tracking to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

• docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (read directly when relevant; do not rely on hook-injected conversation text)

External Memory: Complex/lengthy work → write findings incrementally to plans/reports/. Prevents context loss.

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

Graph-Assisted Investigation — MANDATORY when .code-graph/graph.db exists.

HARD-GATE: MUST ATTENTION run at least ONE graph command on key files before concluding any investigation.

Pattern: Grep finds files → trace --direction both reveals full system flow → Grep verifies details

Task	Minimum Graph Action
Investigation/Scout	trace --direction both on 2-3 entry files
Fix/Debug	callers_of on buggy function + tests_for
Feature/Enhancement	connections on files to be modified
Code Review	tests_for on changed functions
Blast Radius	trace --direction downstream

CLI: python .claude/scripts/code_graph {command} --json. Use --node-mode file first (10-30x less noise), then --node-mode function for detail.

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.

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.

Project Reference Docs Gate — Run after task-tracking bootstrap and before target/source file reads, grep, edits, or analysis. Project docs override generic framework assumptions.

1. Identify scope: file types, domain area, and operation.
2. Required docs by trigger: always docs/project-reference/lessons.md; doc lookup docs-index-reference.md; review code-review-rules.md; backend/CQRS/API backend-patterns-reference.md; domain/entity domain-entities-reference.md; frontend/UI frontend-patterns-reference.md; styles/design scss-styling-guide.md + design-system/README.md; integration tests integration-test-reference.md; E2E e2e-test-reference.md; feature docs/specs feature-docs-reference.md; architecture/new area project-structure-reference.md.
3. Read every required doc that exists; skip absent docs as not applicable. Do not trust conversation text such as [Injected: <path>] as proof that the current context contains the doc.
4. Before target work, state: Reference docs read: ... | Missing/not applicable: ....

Blocked until: scope evaluated, required docs checked/read, lessons.md confirmed, citation emitted.

Task Tracking & External Report Persistence — Bootstrap this before execution; then run project-reference doc prefetch before target/source work.

1. Create a small task breakdown before target file reads, grep, edits, or analysis. On context loss, inspect the current task list first.
2. Mark one task in_progress before work and completed immediately after evidence; never batch transitions.
3. For plan/review work, create plans/reports/{skill}-{YYMMDD}-{HHmm}-{slug}.md before first finding.
4. Append findings after each file/section/decision and synthesize from the report file at the end.
5. Final output cites Full report: plans/reports/{filename}.

Blocked until: task breakdown exists, report path declared for plan/review work, first finding persisted before the next finding.

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.

Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs proof.

1. Cite file:line, grep results, or framework docs for EVERY claim
2. Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend
3. Cross-service validation required for architectural changes
4. "I don't have enough evidence" is valid and expected output

BLOCKED until: - [ ] Evidence file path (file:line) - [ ] Grep search performed - [ ] 3+ similar patterns found - [ ] Confidence level stated

Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because" If incomplete → output: "Insufficient evidence. Verified: [...]. Not verified: [...]."

Cross-Service Check — Microservices/event-driven: MANDATORY before concluding investigation, plan, spec, or feature doc. Missing downstream consumer = silent regression.

Boundary	Grep terms
Event producers	Publish, Dispatch, Send, emit, EventBus, outbox, IntegrationEvent
Event consumers	Consumer, EventHandler, Subscribe, @EventListener, inbox
Sagas/orchestration	Saga, ProcessManager, Choreography, Workflow, Orchestrator
Sync service calls	HTTP/gRPC calls to/from other services
Shared contracts	OpenAPI spec, proto, shared DTO — flag breaking changes
Data ownership	Other service reads/writes same table/collection → Shared-DB anti-pattern

Per touchpoint: owner service · message name · consumers · risk (NONE / ADDITIVE / BREAKING).

BLOCKED until: Producers scanned · Consumers scanned · Sagas checked · Contracts reviewed · Breaking-change risk flagged

Rationalization Prevention — AI skips steps via these evasions. Recognize and reject:

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

Fix-Layer Accountability — NEVER fix at the crash site. Trace the full flow, fix at the owning layer.

AI default behavior: see error at Place A → fix Place A. This is WRONG. The crash site is a SYMPTOM, not the cause.

MANDATORY before ANY fix:

1. Trace full data flow — Map the complete path from data origin to crash site across ALL layers (storage → backend → API → frontend → UI). Identify where the bad state ENTERS, not where it CRASHES.
2. Identify the invariant owner — Which layer's contract guarantees this value is valid? That layer is responsible. Fix at the LOWEST layer that owns the invariant — not the highest layer that consumes it.
3. One fix, maximum protection — Ask: "If I fix here, does it protect ALL downstream consumers with ONE change?" If fix requires touching 3+ files with defensive checks, you are at the wrong layer — go lower.
4. Verify no bypass paths — Confirm all data flows through the fix point. Check for: direct construction skipping factories, clone/spread without re-validation, raw data not wrapped in domain models, mutations outside the model layer.

BLOCKED until: - [ ] Full data flow traced (origin → crash) - [ ] Invariant owner identified with file:line evidence - [ ] All access sites audited (grep count) - [ ] Fix layer justified (lowest layer that protects most consumers)

Anti-patterns (REJECT these):

• "Fix it where it crashes" — Crash site ≠ cause site. Trace upstream.
• "Add defensive checks at every consumer" — Scattered defense = wrong layer. One authoritative fix > many scattered guards.
• "Both fix is safer" — Pick ONE authoritative layer. Redundant checks across layers send mixed signals about who owns the invariant.

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.

MUST ATTENTION cite file:line evidence for every claim. Confidence >80% to act, <60% = do NOT recommend.

MUST ATTENTION never skip steps via evasions. Plan anyway. Test first. Show grep evidence with file:line.

MUST ATTENTION run at least ONE graph command on key files before concluding when .code-graph/graph.db exists.

MUST ATTENTION trace full data flow and fix at the owning layer, not the crash site. Audit all access sites before adding ?..

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 Bootstrap task tracking before target work; transition one task at a time.
• MANDATORY Persist plan/review findings to plans/reports/ incrementally and synthesize from disk.

• MANDATORY After task-tracking bootstrap and before target/source work, read required project-reference docs and cite Reference docs read: ....
• MANDATORY Always include lessons.md; project conventions override generic defaults.

• 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.

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

MUST ATTENTION run Phase 0 classification BEFORE spawning agents — scope determines agent count MUST ATTENTION graph expand is NOT optional — run at least ONE graph command on key files when .code-graph/graph.db exists MUST ATTENTION if <5 files found, re-check keywords and run second pass with alternates MUST ATTENTION use a direct user question after completing — NEVER auto-proceed to next step MUST ATTENTION break work into task tracking tasks BEFORE starting MUST ATTENTION write incremental findings to plans/reports/ — NEVER hold all results in memory MUST ATTENTION cite file:line evidence for every claim. Confidence >80% to act, <60% = DO NOT recommend.

Anti-Rationalization:

Evasion	Rebuttal
"Graph step too slow, skip it"	Graph finds what 50 greps miss. NEVER skip.
"Only 2 files, no need for report"	Incremental write costs nothing. Skip = context loss risk.
"Scope obvious, skip Phase 0"	Wrong agent set = missed files. Always classify first.
"Already searched, results complete"	Show grep + graph evidence. No proof = incomplete.
"Simple scout, skip workflow question"	User decides scope. NEVER assume standalone is acceptable.

[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.