| name | claude-md-init |
| description | [Documentation] Use when you need initialize, update, or refactor CLAUDE markdown from project-config JSON and codebase scan results. |
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=<key>, $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:
- 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 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: Automate CLAUDE.md lifecycle — generate from project-config.json + template, incrementally update marked sections, or refactor for token efficiency.
Workflow:
- Detect Mode — init (no CLAUDE.md or
--mode init), update (--mode update), refactor (--mode refactor)
- Run Generator —
node .claude/skills/claude-md-init/scripts/generate-claude-md.cjs --mode <mode>
- AI Fill — Review output, fill creative sections (project description, golden rules inference)
- Verify — Confirm output is valid, no project-specific leaks from template
- Sync Mirrors — After CLAUDE.md is written (init/update/refactor), call
$sync-codex to regenerate the stale AGENTS.md + Codex mirror surfaces from the new CLAUDE.md
Key Rules:
- Generic — works in any project by reading
docs/project-config.json
- Section markers (
<!-- SECTION:key -->) enable incremental updates without overwriting user content
- Conditional sections — generated ONLY when config has matching data; empty config = section omitted
- Static framework sections (8 total) are portable across all projects
Bootstrap Gate (when CLAUDE.md is missing or incomplete)
This skill is the AI-runnable route the agent-files bootstrap gate offers when a portable
.claude install lands in a project without a root CLAUDE.md — or with one that carries only
project-specific knowledge and is missing the universal portable guides. A single hook detects the gap
and routes here (shared detection lib: .claude/hooks/lib/agent-files-state.cjs):
init-prompt-gate.cjs (UserPromptSubmit) — blocks the first prompt once project-config.json
is populated but CLAUDE.md / AGENTS.md is missing or incomplete. This UserPromptSubmit
gate is the sole agent-files bootstrap router.
Three-state detection per root file: missing → routes to --mode init (fresh from template);
incomplete → routes to --mode update (smart-merge — preserves your project content, injects the
guides); ok → no block. Completeness is decided by hasUniversalGuides(): a current-or-newer
sentinel (<!-- CK:UNIVERSAL-GUIDES v1 -->) → complete; an older sentinel → flag for update; no
sentinel → fall back to scanning required anchors (First Action Decision, Workflow Step Advancement,
Task Planning Rules, Code Responsibility Hierarchy, Evidence-Based Reasoning) so legacy/hand-written
complete files still pass.
Run $claude-md-init (or the generator directly) to produce CLAUDE.md from
docs/project-config.json + template. The generated file ships the universal session-start guides
(workflow ask-confirm gate, workflow step-advancement + parallel-phase barrier, task-planning rules,
code hierarchy, naming, evidence/confidence rules) and stamps the sentinel at the top so the gate
recognizes it as complete. It also stamps the hook-independent Workflow-First Gate (from
.claude/skills/shared/workflow-first-gate.md, via stampHeader()) immediately after the sentinel —
the primacy-anchor routing rule (bug→workflow-bugfix workflow, feature/enhancement→workflow-feature workflow) that
mirrors into AGENTS.md and survives with no hooks.
Opt-out — to keep a project-only CLAUDE.md/AGENTS.md (your custom knowledge, none of the
universal guides), set portability.requireUniversalGuides: false in docs/project-config.json
(persistent; default true). The gate then checks only existence, never completeness. The transient
skip init escape still dismisses both hooks for 24h. The gate is dormant in empty/greenfield folders
and before config is populated. AGENTS.md is generated separately by $sync-codex (user-invoke-only).
Modes
| Mode | When | Behavior |
|---|
init | No CLAUDE.md exists, or first-time setup | Generate fresh CLAUDE.md from template + config. Populates all markers. |
update | CLAUDE.md exists with markers | Replace only content between markers. Preserve everything else. |
refactor | CLAUDE.md exists, needs optimization | AI reads entire CLAUDE.md, optimizes for token efficiency, removes redundancy, improves structure. No script — pure AI. |
Prerequisites
docs/project-config.json — primary data source (run $project-config first if missing)
- Node.js available (for generator script)
Phase 1: Detect Mode
node .claude/skills/claude-md-init/scripts/generate-claude-md.cjs --detect
Decision logic:
- No CLAUDE.md →
init
- CLAUDE.md with markers →
update
- CLAUDE.md without markers →
smart-merge (see below)
- User explicit
--mode flag → override detection
Phase 2: Run Generator Script
node .claude/skills/claude-md-init/scripts/generate-claude-md.cjs --mode init
node .claude/skills/claude-md-init/scripts/generate-claude-md.cjs --mode update
Script behavior:
- Reads
docs/project-config.json
- Reads template (
references/claude-md-template.md) for init, or existing CLAUDE.md for update
- Calls section builders to generate content for each marker key
- Writes output to
CLAUDE.md (creates backup .claude-md.backup first)
- Outputs report: which sections were generated, which skipped (no data), which preserved
Smart-Merge (Update on CLAUDE.md Without Markers)
When running update on an existing CLAUDE.md that has NO section markers:
- Read existing CLAUDE.md
- Match sections by
## heading text against known section keys (see references/section-registry.md)
- For each matched section: wrap with markers, replace content with generated content
- For unmatched user sections: preserve as-is (no markers added)
- Write output with backup
Phase 3: AI Fill (Post-Script)
After the script generates the mechanical parts, AI reviews and fills:
- Project description in TL;DR — write a concise 2-3 sentence description based on config + codebase
- Golden rules — infer from
contextGroups[].rules in config, but rewrite as human-readable rules
- Decision quick-ref — build from
modules[] + framework config, add project-specific patterns
- Naming conventions — detect from codebase patterns if not in config
Phase 4: Verify
Phase 5: Sync Mirrors (after CLAUDE.md is written)
Writing/updating CLAUDE.md leaves the generated mirror surfaces stale — AGENTS.md (Codex), the
.codex/ mirrors, and other downstream surfaces are derived FROM CLAUDE.md and
do not update on their own.
MUST add a final todo task — "Sync Codex mirrors from updated CLAUDE.md" — and run it after
init/update/refactor completes, by invoking the $sync-codex skill (the full cross-surface
migrate → hooks → context → verify pipeline, which regenerates AGENTS.md). Create this as
the LAST task tracking item so it always follows the verify step:
Task tracking: "Sync Codex mirrors from updated CLAUDE.md → invoke $sync-codex"
Skip only when no CLAUDE.md content actually changed (e.g. generator reported all sections preserved /
no diff). Otherwise the AGENTS.md mirror drifts from CLAUDE.md and Codex runs against stale
guidance.
Refactor Mode (AI-Only)
When --mode refactor or user asks to optimize CLAUDE.md:
- Read entire CLAUDE.md
- Identify: redundant sections, verbose explanations, duplicate info available in referenced docs
- Apply token efficiency: remove duplication, consolidate tables, shorten where possible
- Preserve all section markers
- Report: lines before/after, sections changed, estimated token savings
Section Marker Protocol
<!-- SECTION:tldr -->
Auto-generated content here...
<!-- /SECTION:tldr -->
Rules:
- Only content between markers is replaced on update
- Content outside markers is never touched
- Missing markers in update mode → section skipped (not inserted)
- Init mode uses template which includes all markers
- Markers use lowercase kebab-case keys matching section-registry.md
Section Keys (Quick Reference)
See references/section-registry.md for full mapping. Summary:
| Key | Source | Conditional? |
|---|
tldr | project.*, modules[], framework.* | No — always generated |
golden-rules | contextGroups[].rules | Yes — skip if no rules |
decision-quick-ref | modules[], framework.* | Yes — skip if no modules |
key-locations | modules[].pathRegex | Yes — skip if no modules |
dev-commands | testing.commands, infrastructure.* | Yes — skip if no commands |
infra-ports | modules[].meta.port (infra) | Yes — skip if no ports |
api-ports | modules[].meta.port (services) | Yes — skip if no ports |
integration-testing | framework.integrationTestDoc | Yes — skip if no doc |
e2e-testing | framework.e2eTestDoc or scan | Yes — skip if no tests |
doc-index | Scan docs/ directory | Yes — skip if no docs/ |
doc-lookup | modules[] + business features | Yes — skip if no modules |
Running Tests
Generator + bootstrap-gate coverage lives in the hooks test suite:
node .claude/hooks/tests/run-all-tests.cjs --filter=agent-files
[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.
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.
- No inventories/counts — AI can
grep | wc -l. Counts go stale instantly
- No directory trees — AI can
glob/ls. Use 1-line path conventions
- No TOCs — AI reads linearly. TOC wastes tokens
- No examples that repeat what rules say — one example only if non-obvious
- Lead with answer, not reasoning. Skip filler words and preamble
- Sacrifice grammar for concision in reports
- 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. Before changing a constant, limit, flag, wording, or pattern, read nearby context and history.
Surface ambiguity before acting — don't pick silently. Multiple valid interpretations require an explicit question or stated assumption with risk.
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 maintain >=8 rules per 100 lines. Critical rules in first+last 5 lines. Tables over prose.
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.
Closing Reminders
Protocols in force (concise digest of the SYNC/shared blocks this skill carries): MUST ATTENTION honor every protocol below.
- Critical Thinking: apply critical + sequential thinking; traced proof, confidence >80% to act.
- Output Quality: token-efficient — no inventories/trees/TOCs; tables over prose.
- 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=<key>) before ordinary project-specific work. Any supported AI tool may execute when this shared context and local docs are available.
- 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.
- ANALYZE: Choose the best option: execute directly, invoke a skill, activate a standard workflow, or compose a custom step combination.
- AUTO-SELECT: Pick the best option yourself. Do not ask the user to choose between direct execution, skill, standard workflow, or custom workflow.
- ACTIVATE: For a selected workflow, call
$start-workflow <workflowId>; for a selected skill, invoke that skill; for a custom workflow, sequence custom steps directly; for direct execution, proceed with the task.
- CREATE TASKS: task tracking for ALL workflow/skill/custom steps before execution when the selected path has multiple steps.
- 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.
- Keep reusable AI-SDD principles in
.claude; put repository-specific paths, commands, owners, products, and formats in project config/reference docs.
- Preserve cycle:
spec -> plan -> tasks -> implement -> verify -> update spec/docs.
- Trace every requirement or invariant through decision, task, TC/test, source evidence, and docs/spec update.
- Treat code-to-spec extraction as reference-only until accepted by the canonical spec owner.
- Any supported AI tool may plan, implement, review, or verify with synced context; using multiple tools is optional.
- 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
- 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:
- Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value".
- Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up.
- Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase.
- Consolidate: multiple mistakes sharing one failure mode → ONE lesson.
- Recurrence gate: "Would this recur in future session WITHOUT this reminder?" — No → skip
$learn.
- Auto-fix gate: "Could
$code-review/$code-simplifier/$security-review/$lint catch this?" — Yes → improve review skill instead.
- 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.
- 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. Pattern-matching as "wrong" skips context. Before changing any constant/limit/flag: read comments, git blame, surrounding code.
- 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 <workflowId>. 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.
- 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.