# Scan All > [Documentation] Use when you need orchestrate all reference doc scans in parallel. - Skill: `duc01226/scan-all` (Agent Skill) - Install (CLI): `npx skillmds@latest add duc01226/scan-all` - Raw SKILL.md: https://api.skillmd.com/api/skills/duc01226/scan-all/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Docs & Writing - Author: duc01226 (https://skillmd.com/u/duc01226) - Updated: 2026-09-09 - Page: https://skillmd.com/skills/duc01226/scan-all --- > Codex compatibility note: > > - Invoke repository skills with `$skill-name` in Codex; this mirrored copy rewrites legacy Claude `/skill-name` references. > - Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes. > - User-question prompts mean to ask the user directly in Codex. > - Ignore Claude-specific mode-switch instructions when they appear. > - Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written. > - Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required `spawn_agent` subagent(s) for that task. > - Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first. > - For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence. > - If a required step/tool cannot run in this environment, stop and ask the user before adapting. ## Codex Project-Reference Loading (No Hooks) Codex uses static project-reference loading instead of runtime-injected project docs. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing. **Always read:** - `docs/project-config.json` (project-specific paths, commands, modules, and workflow/test settings) - `docs/project-reference/docs-index-reference.md` (routes to the full `docs/project-reference/*` catalog) - `docs/project-reference/lessons.md` (always-on guardrails and anti-patterns) **Missing/stale context route:** If `docs/project-config.json`, the docs index, `lessons.md`, `CLAUDE.md`, `AGENTS.md`, or any task-required reference doc is missing or stale, auto-run `$project-init` or the narrow setup route (`$project-config`, `$docs-init`, `$scan-all`, `$scan --target=`, `$claude-md-init`) before ordinary project-specific work. If Codex mirrors or `AGENTS.md` are missing/stale, ask the user to run `$sync-codex`; do not auto-run it. **Situation-based docs:** - Project structure/architecture/tech-stack/deployment/setup (any layer — backend, frontend, or infra): `project-structure-reference.md` - Backend/CQRS/API/domain/entity changes: `backend-patterns-reference.md`, `domain-entities-reference.md` - Frontend/UI/styling/design-system: `frontend-patterns-reference.md`, `scss-styling-guide.md`, `design-system/README.md` - Spec authoring, `docs/specs/` pathing, or TC format: `feature-spec-reference.md`, `spec-system-reference.md`, `spec-principles.md` - Behavior/public-contract changes or spec-test-code sync: `workflow-spec-test-code-cycle-reference.md` plus the spec docs above - Derived spec indexes/ERDs/reimplementation guides: `spec-system-reference.md` and source Feature Specs under `docs/specs/` - 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:** Run all 12 scan-\* skills in parallel and clear the staleness gate. **Workflow:** 1. **Check Prerequisites** — Verify project has content (not empty) 2. **Launch Parallel Scans** — All 12 skills simultaneously 3. **Collect Results** — Read scan output from reference docs 4. **Clear Staleness Flag** — Re-evaluate all docs via `refreshScanStaleFlag()`, which removes `.claude/.scan-stale` once every doc is fresh (see Post-Scan Cleanup) 5. **Build Knowledge Graph** — Run `$graph-build` to update structural graph 6. **Enhance Docs** — Run `$prompt-enhance` on all 12 scanned docs 7. **Summarize** — Report what was refreshed **Key Rules:** - All 12 scans run in PARALLEL for speed - Does NOT modify code — only populates docs/project-reference/ - Clears `.claude/.scan-stale` flag after completion - `$prompt-enhance` ensures AI attention anchoring on all generated docs ## When to Use - Staleness gate blocks prompts ("BLOCKED: Reference docs are stale") - First time using easy-claude on an existing project (project onboarding) - Periodic refresh when codebase has changed significantly - User runs `$scan-all` manually ## When to Skip - Empty/greenfield project (no code to scan) - All reference docs are already fresh (no staleness warning) ## Execution Each scan reads real code evidence and (re)populates ONE reference doc under `docs/project-reference/`. Those docs are injected into AI context downstream, so scanning is what keeps that guidance true to the current codebase — the **Purpose** column says what each scan documents and therefore why it matters. Launch all 12 code-derived scans in parallel: | # | Invocation | Target Doc | Purpose — what the scan documents | | --- | ---------------------------------- | -------------------------------- | ------------------------------------------------------------------------------------------------------------------------ | | 1 | `$scan --target=project-structure` | `project-structure-reference.md` | Service architecture, ports, directory layout, tech stack, deployment & module registry (spans backend, frontend, infra) | | 2 | `$scan --target=backend-patterns` | `backend-patterns-reference.md` | Repository, CQRS, validation, entity, event & migration patterns | | 3 | `$scan --target=seed-test-data` | `seed-test-data-reference.md` | Seeder patterns & conventions, from real code evidence | | 4 | `$scan --target=frontend-patterns` | `frontend-patterns-reference.md` | Component, state, form, API, routing & styling patterns | | 5 | `$scan --target=integration-tests` | `integration-test-reference.md` | Integration-test base classes, fixtures, helpers & service setup | | 6 | `$scan --target=feature-spec` | `feature-spec-reference.md` | Feature-doc structure, app→service mapping, spec templates & conventions | | 7 | `$scan --target=code-review-rules` | `code-review-rules.md` | Code conventions, anti-patterns, architecture rules & review checklists | | 8 | `$scan --target=scss-styling` | `scss-styling-guide.md` | SCSS architecture, BEM conventions, mixins, variables, theming & responsive patterns | | 9 | `$scan --target=design-system` | `design-system/README.md` | Design tokens, component inventory & app→doc design-system mappings | | 10 | `$scan --target=e2e-tests` | `e2e-test-reference.md` | E2E architecture, page objects, step definitions, config & framework patterns | | 11 | `$scan --target=domain-entities` | `domain-entities-reference.md` | Domain entities, DTOs, aggregate boundaries, sync patterns & ER diagrams | | 12 | `$scan --target=docs-index` | `docs-index-reference.md` | Documentation structure, categories, relationships & lookup tables | > **Coverage & count.** These 12 are the _code-derived_ docs. The child `scan` skill exposes a 13th key, `ui-system` — a meta-target that only fan-runs #4, #8, #9 together — intentionally excluded here to avoid double-scanning. Curated/static docs (`lessons.md`, `spec-principles.md`, `spec-system-reference.md`, `workflow-spec-test-code-cycle-reference.md`) are hand-authored, not scanned, so they are absent by design. Purpose text mirrors each target's `description` in `.claude/skills/scan/references/targets.md` — update it THERE first if a target's scope changes, then reflect it here. ## Post-Scan Cleanup After all scans complete, clear the staleness flag: ```bash node -e "require('./.claude/hooks/lib/session-init-helpers.cjs').refreshScanStaleFlag()" ``` This re-evaluates all docs and removes the `.scan-stale` gate if all are now fresh. ## Post-Scan: Build Knowledge Graph (MANDATORY) After all scans complete, **MUST ATTENTION create a follow-up task:** **Task tracking: "Run $graph-build to build/update code knowledge graph"** The knowledge graph uses `project-config.json` (populated by scans) for API connector patterns and implicit connection rules. Building the graph after scans ensures: - Frontend↔backend API_ENDPOINT edges use accurate service paths - MESSAGE_BUS implicit edges use correct consumer patterns - Graph trace shows full system flow (frontend → backend → cross-service consumers) ```bash python .claude/scripts/code_graph build --json ``` ## Post-Scan: Enhance Generated Docs (MANDATORY) Each scan-\* sub-skill now self-enhances its own doc as its final step. After graph build, **MUST ATTENTION confirm `$prompt-enhance` ran on every scanned doc and backfill any that were skipped.** Reference docs are injected into AI context — attention anchoring (top/bottom summaries, inline READ summaries, token density) directly improves AI output quality. **task tracking one task per doc, parallel OK:** | # | Target File | | --- | ------------------------------------------------------- | | 1 | `docs/project-reference/project-structure-reference.md` | | 2 | `docs/project-reference/backend-patterns-reference.md` | | 3 | `docs/project-reference/seed-test-data-reference.md` | | 4 | `docs/project-reference/frontend-patterns-reference.md` | | 5 | `docs/project-reference/integration-test-reference.md` | | 6 | `docs/project-reference/feature-spec-reference.md` | | 7 | `docs/project-reference/code-review-rules.md` | | 8 | `docs/project-reference/scss-styling-guide.md` | | 9 | `docs/project-reference/design-system/README.md` | | 10 | `docs/project-reference/e2e-test-reference.md` | | 11 | `docs/project-reference/domain-entities-reference.md` | | 12 | `docs/project-reference/docs-index-reference.md` | Run via: `$prompt-enhance docs/project-reference/{filename}` ## Summary Output After all scans complete, report: "Scan All Complete: - {X}/12 scans succeeded - Reference docs refreshed in docs/project-reference/ - Staleness gate cleared - Prompt-enhanced {Y}/12 docs - Knowledge graph rebuilt via $graph-build" --- > **[IMPORTANT]** Use task tracking to break ALL work into small tasks BEFORE starting. > **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. > **Output Quality** — Token efficiency without sacrificing quality. > > 1. No inventories/counts — AI can `grep | wc -l`. Counts go stale instantly > 2. No directory trees — AI can `glob`/`ls`. Use 1-line path conventions > 3. No TOCs — AI reads linearly. TOC wastes tokens > 4. No examples that repeat what rules say — one example only if non-obvious > 5. Lead with answer, not reasoning. Skip filler words and preamble > 6. Sacrifice grammar for concision in reports > 7. Unresolved questions at end, if any > **AI Mistake Prevention** — Failure modes to avoid on every task: > > **Re-read files after context changes.** Context compaction, resume, or long-running work can make memory stale; verify current files before acting. > **Verify generated content against source evidence.** AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. > **Check downstream references before deleting or renaming.** Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. > **Trace the full impact chain after edits.** Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done. > **Verify ALL affected outputs, not just the first.** One green check is not all green checks; validate every output surface the change can affect. > **Assume existing values are intentional — ask WHY before changing OR flagging one as a defect.** Before changing or reporting a constant, limit, flag, cutoff, wording, or pattern, read nearby context and history, the CALLER's ordering, and 2+ sibling call sites of the same convention. A doc stating WHAT without WHY is missing rationale, not proof of a missing guard. > **Surface ambiguity before acting — don't pick silently.** Multiple valid interpretations require an explicit question or stated assumption with risk. > **Assert the outcome your system owns, not the intermediate state your infrastructure owns.** When verifying async work, assert the final business state — never the delivery/retry bookkeeping held in shared infrastructure that any co-running process can write. Such a check passes when run alone and flakes the moment anything else shares that infrastructure. > **Keep shared guidance role-relevant.** Universal guidance must help every receiving skill or agent; code-specific obligations belong only in code-specific protocols. **IMPORTANT MUST ATTENTION** follow output quality rules: no counts/trees/TOCs, rules > descriptions, 1 example per pattern, primacy-recency anchoring. **MUST ATTENTION** apply critical + sequential thinking — every claim needs appropriate traced evidence (`file:line` for repo/code claims; source URL or artifact section for research, product, content, and docs claims); confidence >80% to act, <60% DO NOT recommend. Anti-hallucination: never present guess as fact, admit uncertainty freely, cross-reference independently, stay skeptical of own confidence. **MUST ATTENTION** apply AI mistake prevention — verify generated content against evidence, trace downstream references before deleting or renaming, verify all affected outputs, re-read files after context loss, and surface ambiguity before acting. > **Project Protocol Overlay** — Before executing this skill, resolve any PROJECT overlay rules layered onto it: match this skill's name against the `Target` column of the project's skill-protocol index (`docs/project-reference/skill-protocols-reference.md` by default; a `referenceDocs` entry in `docs/project-config.json` overrides the path), taking the most specific matching tier ONLY — exact name > glob > `*`. **That precedence orders overlays against EACH OTHER, never against this skill.** Read ONLY the matched bodies, resolved as `/.md`; a row's Body link is display text, never a read path. A matched body that is missing or malformed is REPORTED and skipped — never reconstructed from the index Description. No index, or no match -> proceed with no overlay, silently. Full contract: `.claude/skills/project-skill-protocol/references/registry.md`. > > Overlays are **ADDITIVE ONLY**: they ADD rules on top of this skill's own protocol and NEVER replace, override, disable, or reinterpret a rule it already states — removing every overlay must return this skill to exactly its documented behavior. An overlay is a BRIEF, not an authority escalation: it can NEVER waive a workflow gate, git discipline, a review gate, or a user-confirmation gate. A genuine overlay-vs-skill conflict, or two equally-specific overlays that directly contradict -> surface both to the user; NEVER resolve silently. **MUST ATTENTION** resolve project protocol overlays for this skill BEFORE executing — most specific matching tier only (exact > glob > `*`, which ranks overlays against each other, NEVER against this skill), read only matched bodies at `/.md`; a missing or malformed body is reported, never reconstructed. Overlays are ADDITIVE ONLY (they never replace this skill's own rules) and are a brief, NEVER an authority escalation; an equal-specificity contradiction goes to the user. ## Closing Reminders **Protocols in force (concise digest of the SYNC/shared blocks this skill carries) — MUST ATTENTION honor each canonical body:** - **Critical Thinking:** MUST ATTENTION traced `file:line` proof per claim, confidence >80% to act. - **Output Quality:** MUST ATTENTION no counts/trees/TOCs, rules over prose, primacy-recency anchoring. - **AI Mistake Prevention:** verify generated content against evidence, trace downstream references, verify all affected outputs, re-read after context loss, surface ambiguity. **IMPORTANT MUST ATTENTION** break work into small todo tasks using task tracking BEFORE starting **IMPORTANT MUST ATTENTION** search codebase for 3+ similar patterns before creating new code **IMPORTANT MUST ATTENTION** cite `file:line` evidence for every claim (confidence >80% to act) **IMPORTANT MUST ATTENTION** add a final review todo task to verify work quality **[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/.ck.json` + `.claude/skills/shared/sync-inline-versions.md` (`:full` blocks) + `.claude/scripts/lib/hookless-prompt-protocol.cjs` ## [WORKFLOW-EXECUTION-PROTOCOL] [BLOCKING] Workflow Execution Protocol — MANDATORY IMPORTANT MUST CRITICAL. Do not skip for any reason. **Generic portability boundary:** Reusable skills and protocol text stay project-neutral; project-specific conventions are discovered from docs/project-config.json and docs/project-reference/. Apply shared AI-SDD from `shared/sdd-artifact-contract.md`. Read `docs/project-config.json` and `docs/project-reference/docs-index-reference.md`, then open the project reference docs named there. For spec, test-case, behavior-change, public-contract, or `docs/specs/` work, route through the local spec docs named by the docs index: `feature-spec-reference.md`, `spec-system-reference.md`, `spec-principles.md`, and `workflow-spec-test-code-cycle-reference.md` when specs/tests/code must stay synchronized. If either file or a required reference doc is missing or stale, auto-run `$project-init` (or the narrow lower-level route such as `$project-config`, `$docs-init`, `$scan-all`, or `$scan --target=`) before ordinary project-specific work. Any supported AI tool may execute when this shared context and local docs are available. 1. **DETECT:** If the prompt starts with an explicit slash skill/workflow command, execute it directly. Otherwise match the prompt against the workflow catalog and skill list. 2. **ANALYZE:** Choose the best option: execute directly, invoke a skill, activate a standard workflow, or compose a custom step combination. 3. **AUTO-SELECT:** Pick the best option yourself. Do not ask the user to choose between direct execution, skill, standard workflow, or custom workflow. 4. **ACTIVATE:** For a selected workflow, call `$start-workflow `; for a selected skill, invoke that skill; for a custom workflow, sequence custom steps directly; for direct execution, proceed with the task. 5. **CREATE TASKS:** task tracking for ALL workflow/skill/custom steps before execution when the selected path has multiple steps. 6. **PARALLELIZE:** Before executing the task list, tag each task `PAR` (independent inputs + write set disjoint from every other `PAR` task) or `SEQ` (name the blocking dependency), group `PAR` tasks into waves, declare the wave plan, and spawn each wave's sub-agents in ONE message — all-return barrier per wave, fan-out one level deep unless a sub-agent's own definition authorizes further fan-out. Sequential-by-default is a defect when tasks are independent; do not parallelize shared write targets, output-consuming tasks, trivial single-file work, ordering a skill or workflow explicitly fixes, or user-approval gates. 7. **EXECUTE:** Advance per the **Workflow Step Advancement & Parallel Phases** rule in your context instructions — model-driven; a sub-agent completion advances a step identically to an inline call; a parallel-phase group is an all-return barrier (advance only after ALL members return, never serialize it) ## Shared AI-SDD Protocol Markers Source: `.claude/skills/shared/sync-inline-versions.md` ## SYNC:ai-sdd-artifact-contract > **AI-SDD Artifact Contract** — Shared spec-driven development rules stay portable and source-owned. > > 1. Keep reusable AI-SDD principles in `.claude`; put repository-specific paths, commands, owners, products, and formats in project config/reference docs. > 2. Preserve cycle: `spec -> plan -> tasks -> implement -> verify -> update spec/docs`. > 3. Trace every requirement or invariant through decision, task, TC/test, source evidence, and docs/spec update. > 4. Treat code-to-spec extraction as reference-only until accepted by the canonical spec owner. > 5. Any supported AI tool may plan, implement, review, or verify with synced context; using multiple tools is optional. > 6. Update `.claude` source first, then sync generated mirrors; do not manually edit `.agents`, `.codex`, or `AGENTS.md`. — why: mirrors are generated artifacts; hand-edits are overwritten on the next sync > 7. If `docs/project-config.json`, root instruction files, or a required project-reference doc is missing or stale, auto-run `$project-init` or the narrow lower-level route before ordinary project-specific work. > > **Active reference:** `shared/sdd-artifact-contract.md` in the active skills root. --- ## SYNC:ai-sdd-artifact-contract:reminder - **MANDATORY** Apply `shared/sdd-artifact-contract.md`; keep reusable AI-SDD in `.claude` and local rules in project docs. - **MANDATORY** Code-to-spec extraction is reference-only until canonical acceptance; any supported AI tool may execute with synced context. - **MANDATORY** Update `.claude` source before syncing generated mirrors; do not manually edit `.agents`, `.codex`, or `AGENTS.md`. - **MANDATORY** Missing or stale project config, root instruction files, or required reference docs route project-specific work through `$project-init` or the narrow setup route automatically. **[TASK-PLANNING] [MANDATORY]** BEFORE executing any workflow or skill step, create/update task tracking for all planned steps, then keep it synchronized as each step starts/completes. ## [LESSON-LEARNED-REMINDER] [BLOCKING] Task Planning & Continuous Improvement — MANDATORY. Do not skip. Break work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned". **Extract lessons — ROOT CAUSE ONLY, not symptom fixes:** 1. Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value". 2. Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up. 3. Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase. 4. Consolidate: multiple mistakes sharing one failure mode → ONE lesson. 5. **Recurrence gate:** "Would this recur in future session WITHOUT this reminder?" — No → skip `$learn`. 6. **Auto-fix gate:** "Could `$code-review`/`$code-simplifier`/`$security-review`/`$lint` catch this?" — Yes → improve review skill instead. 7. BOTH gates pass → ask user to run `$learn`. **[CRITICAL-THINKING-MINDSET]** Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. **Anti-hallucination principle:** Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination. **AI Attention principle (Primacy-Recency):** Put the 3 most critical rules at both top and bottom of long prompts/protocols so instruction adherence survives long context windows. **Goal-driven execution:** Define success criteria first, loop until verified, and stop only when observable checks pass. **Tests verify intent:** Tests must protect business rules/invariants and fail when the protected intent breaks, not only mirror current behavior. ## Common AI Mistake Prevention (System Lessons) - **Re-read files after context compaction.** Edit requires prior Read in same context; compaction wipes read state. Re-read before editing. - **Grep for old terms after bulk replacements.** AI over-trusts find/replace completeness. Grep full repo after bulk edits for missed refs in docs/configs/catalogs. - **Check downstream references before deleting.** Deletions cascade doc/code staleness. Map referencing files before removal. - **After memory loss, check existing state before creating new.** Compaction wipes prior-work memory. Query current state to resume — never blindly duplicate. - **Verify AI-generated content against actual code.** AI hallucinates APIs, class names, method signatures. Grep to confirm existence before documenting/referencing. - **Trace full dependency chain after edits.** Changing a definition misses downstream consumers. Trace the full chain. - **When renaming, grep ALL consumer file types.** Some file types silently ignore missing refs (no compile error). Search code, templates, configs, generated files. - **Trace ALL code paths when verifying correctness.** Code existing ≠ code executing. Trace early exits, error branches, conditional skips — not just happy path. - **Update docs that embed canonical data when source changes.** Docs inlining derived data (workflows, schemas, configs) go stale silently. Update all embedding docs alongside source. - **Verify sub-agent results after context recovery.** Background agents may finish while parent compacted — grep-verify output, don't trust assumed completion. - **Cross-check full target list against sub-agent assignments.** Parallel sub-agents by category miss boundary items. Reconcile union of assignments against target list before proceeding. - **Sub-agents inherit knowledge only from their agent .md definition — use custom agent types, not built-in Explore.** Tool adoption = permission + knowledge + enforcement (numbered workflow step). - **Persist sub-agent findings incrementally, not as a final batch.** Long sub-agents hit cutoffs before final write — findings lost. Instruct append-per-section to report file. - **When debugging, ask "whose responsibility?" before fixing.** Trace caller (wrong data) vs callee (wrong handling). Fix at responsible layer — never patch symptom site. - **Test failure → record a provisional verdict before trace/edit, then investigate.** Use the full five-way taxonomy: SOURCE-WRONG (production violates intent), TEST-WRONG (assertion/setup is stale), TEST-NOT-OPTIMAL (valid but fragile or low-signal test), ENVIRONMENT-BLOCKED (external state prevents a verdict), or AMBIGUOUS (intent/evidence cannot choose safely). Then trace root cause and triangulate against the governing spec (`docs/specs/**` if one exists) AND source. NEVER weaken an assertion, add a skip, relax a timeout, or change source merely to force green. - **Grep ALL removed names after extraction/refactoring.** Primary file "done" ≠ secondary files clean. Grep entire scope for every removed symbol before declaring complete. - **Assume existing values are intentional — ask WHY before changing OR flagging one as a defect.** Pattern-matching as "wrong" skips context. Before changing or reporting any constant/limit/flag/cutoff: read comments, git blame, the CALLER's ordering (the guarantee that makes the value correct usually lives in code running immediately BEFORE the cited line), and 2+ sibling call sites of the same convention. A doc stating WHAT without WHY is missing rationale, not proof of a missing guard — and in a validation pass, an accurate `file:line` citation proves the transcription, never the defect. - **Verify ALL affected outputs, not just the first.** One build green ≠ all green. Multi-stack changes (backend/frontend/tests/docs) require verifying EVERY output. - **Evaluate fit before copying a nearby pattern.** Closest example ≠ matching preconditions — verify the new context shares the same constraints, base classes, scope, lifetime. - **Holistic-first debugging — resist nearest-attention trap.** Don't dive into first plausible cause. List EVERY precondition (config, env vars, paths, DB, endpoints, creds, versions, DI, data). Verify each against evidence (grep/query — not reasoning). Ask "what would falsify this?" — if nothing, it's not a hypothesis. Most expensive failure: going deeper in "obvious" layer while bug sits in layer never questioned. - **Surgical changes — apply the diff test (context-aware).** Two modes: (1) Bug fix → every line traces to the bug; no restyling; orphan cleanup only for imports YOUR changes made unused. (2) Review/enhancement → implement improvements AND announce as "Enhancement beyond main request: [what]". Never silently scope-creep. Diff test: "Would this line exist if I wasn't asked to do X?" — if no, delete or announce. - **Surface ambiguity before coding — don't pick silently.** Multiple valid interpretations → present each with effort: "[Request] could mean (1) [N h], (2) [N h]. Which matters?" List scope/format/volume/constraints assumptions first. If simpler path exists, say so. Never silently pick. - **[MANDATORY FIRST ACTION] ALWAYS activate a suitable skill or workflow BEFORE responding.** Match task against workflow catalog + skill list; invoke via skill invocation or `$start-workflow `. NEVER answer or write code before checking. Skip = protocol violation. - **Why-Review adversarial mindset — apply when reviewing any plan, decision, or design.** Default SKEPTIC not VALIDATOR: steel-man a rejected alternative, invert each stated reason ("what does it sacrifice?"), stress-test top 2-3 assumptions, run pre-mortem ("ships, fails in 3 months — what breaks?"), surface 1-2 alternatives author missed. Section presence ≠ quality; quality = causal reasoning + concrete mitigations + evidence, not "it's better" or "monitor closely". - **Front-load report-write in sub-agent prompts for large reviews.** Many-file sub-agents hit budget before final write — findings lost. Design prompts so: (1) report-write is first explicit deliverable, (2) append per-file/section (not batched), (3) scope bounded so reads don't exhaust budget. Truncated mid-sentence with no report file → spawn narrower scope, don't retry same prompt. - **After context compaction, re-verify all prior phase outcomes before continuing.** Summaries describe intent, not environment state (git index, filesystem, processes). On resume, FIRST audit: git status, re-read modified files, verify filesystem. Every "completed" claim is an untested hypothesis until evidence confirms. - **OOM/memory: check row count before row size.** Triage: (1) Unbounded query — no DB filter for trigger? Push filter to DB; eliminates OOM. (2) Large rows? Projection reduces proportionally. Row reduction > projection in ROI. - **Assert the outcome your system OWNS, never the intermediate state your INFRASTRUCTURE owns.** When testing anything asynchronous (queue/broker delivery, retries, background jobs, caches, replication), assert the final business/entity state. NEVER assert the delivery bookkeeping — consume/send status, attempt counts, last-error, row existence or counts in a broker, scheduler, or outbox/inbox table. That bookkeeping lives in shared infrastructure that ANY co-running process (a peer worker, a second replica, a leftover local container) can write, usually under a deterministic shared key, so the assertion silently tests the developer's environment instead of the system: green when run alone, flaky the instant anything else shares that broker + database. Gate question for every assertion: "would this hold no matter WHICH process did the work?" — if no, assert the converged data state instead. Corollary: process-local fault injection and in-process telemetry cannot gate work any process may perform — use them as stress amplifiers (arm → bounded window → disarm → assert convergence), never as preconditions. - **Keep domain concepts out of generic/shared/infrastructure layers.** Reusable layer (shared library, framework, infra module) must reference NO consumer-specific domain concept — tenant/customer/product IDs, business entities, feature rules. Leak compiles + runs → passes review silently while coupling the "reusable" layer to one consumer. Keep shared type domain-free; push domain fields/logic down into the consumer via subclass/composition. — why: a layer coupled to one consumer's domain is no longer reusable.