scan-frontend-patterns

name	scan-frontend-patterns
description	[Documentation] Use when scanning frontend component, state, form, API, routing, and styling patterns.

Codex compatibility note:

• Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.
• Prefer the plan-hard skill for planning guidance in this Codex mirror.
• Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes.
• User-question prompts mean to ask the user directly in Codex.
• Ignore Claude-specific mode-switch instructions when they appear.
• Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written.
• Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required spawn_agent subagent(s) for that task.
• Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first.
• For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence.
• If a required step/tool cannot run in this environment, stop and ask the user before adapting.

Codex Project-Reference Loading (No Hooks)

Codex does not receive Claude hook-based doc injection. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing.

Always read:

• docs/project-config.json (project-specific paths, commands, modules, and workflow/test settings)
• docs/project-reference/docs-index-reference.md (routes to the full docs/project-reference/* catalog)
• docs/project-reference/lessons.md (always-on guardrails and anti-patterns)

Situation-based docs:

• Backend/CQRS/API/domain/entity changes: backend-patterns-reference.md, domain-entities-reference.md, project-structure-reference.md
• Frontend/UI/styling/design-system: frontend-patterns-reference.md, scss-styling-guide.md, design-system/README.md
• Spec/test-case planning or TC mapping: feature-docs-reference.md
• Integration test implementation/review: integration-test-reference.md
• E2E test implementation/review: e2e-test-reference.md
• Code review/audit work: code-review-rules.md plus domain docs above based on changed files

Do not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.

Quick Summary

Goal: Scan frontend codebase → populate docs/project-reference/frontend-patterns-reference.md with component base classes, state management patterns, form handling, API service patterns, routing conventions, and directory structure.

Workflow:

1. Classify — Detect framework and scan mode
2. Scan — Parallel sub-agents discover patterns with file:line evidence
3. Report — Write findings incrementally to report file
4. Generate — Build/update reference doc from report
5. Fresh-Eyes — Round 2 verification validates all examples

Key Rules:

• Generic — works with any frontend framework (Angular, React, Vue, Svelte, etc.) MUST ATTENTION detect framework FIRST — agent scope and grep patterns depend on it
• Every code example from actual project files with file:line

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Scan Frontend Patterns

Phase 0: Detect Framework & Mode

[BLOCKING] Before any other step, run in parallel:

1. Read docs/project-reference/frontend-patterns-reference.md

   • Detect mode: Init (placeholder) or Sync (populated)
   • In Sync mode: extract section list → skip re-scanning well-documented sections

2. Detect frontend framework:

Signal	Framework	Key Patterns to Search
angular.json + nx.json	Angular (Nx)	AppBaseComponent, PlatformVmStore, untilDestroyed, BEM classes
angular.json (no Nx)	Angular	@Component, OnDestroy, reactive forms, HttpClient
package.json with react/next	React	hooks, context, useState, useEffect, fetch wrappers
package.json with vue/nuxt	Vue	Composition API, ref, reactive, Pinia stores
package.json with svelte/sveltekit	Svelte	$: reactivity, stores, onMount/onDestroy
Multiple frameworks	Multi-framework	Document each separately — DO NOT merge

3. Detect scan mode:

Mode	Condition	Action
Init	Target doc doesn't exist or placeholder only	Full scan, create all sections
Sync	Target doc has real content	Diff scan — check new base classes, changed patterns

4. Load app paths from docs/project-config.json contextGroups/modules[] if available.

Evidence gate: Confidence <60% on framework → report uncertainty, ask user before proceeding.

Phase 1: Plan

Create task tracking entries for each sub-agent and each verification step. Do not start Phase 2 without tasks created.

Phase 2: Execute Scan (Parallel Sub-Agents)

Launch 3 general-purpose sub-agents in parallel. Each MUST:

• Write findings incrementally after each pattern category — NEVER batch at end
• Cite file:line for every pattern example
• Confidence: >80% document; 60-80% note as "observed (unverified)"; <60% omit

All findings → plans/reports/scan-frontend-patterns-{YYMMDD}-{HHMM}-report.md

Agent 1: Component & Form Patterns

Think (Base Class dimension): What base classes exist? What does each provide — lifecycle, subscriptions, form helpers, DI? Which base class is used for simple components vs complex state vs forms?

Think (Form dimension): Is form state reactive or template-driven? Where does validation live — in the form, in validators, in the model? What's the error display pattern?

Think (Cleanup dimension): How are subscriptions cleaned up? Is there a shared mechanism (e.g., untilDestroyed()) or is each component responsible?

• Grep for component base classes (extends.*Component, AppBaseComponent, React.Component, defineComponent)
• Find form handling patterns (reactive forms, form builders, validation approach, error display)
• Discover component lifecycle conventions (init, destroy, cleanup patterns)
• Find template/JSX conventions (structural patterns, conditional rendering, BEM class patterns)
• Find component communication patterns (inputs/outputs, props/events, signals, @Input/@Output)

Agent 2: State Management & API Services

Think (State dimension): What is the data flow — unidirectional? How does a component trigger a data load? How does it receive updates? What prevents race conditions?

Think (API dimension): Is there a service base class? What does it provide — base URL, auth headers, error mapping? Who calls the HTTP layer — directly in components or via service abstraction?

Think (Subscription dimension): What patterns prevent memory leaks? Is cleanup enforced by a linter/base class or left to developer discipline?

• Grep for state management (PlatformVmStore, Store, useReducer, createStore, defineStore, signals)
• Find API service base classes (extends.*Service, PlatformApiService, HttpClient, fetch wrappers)
• Discover data fetching patterns (interceptors, error handling, loading states, caching)
• Find subscription/cleanup patterns (untilDestroyed, takeUntil, unsubscribe, dispose callbacks)
• Look for shared/common service patterns and DI registration

Agent 3: Routing, Directives & Directory Structure

Think (Routing dimension): How are routes protected? What's the lazy-loading boundary? How are navigation events handled? Is there a routing hierarchy?

Think (Reuse dimension): What custom directives/pipes exist? Are they in a shared library? What naming conventions distinguish feature-specific from cross-cutting reusables?

Think (Organization dimension): What's the pattern for where things live — feature modules, domain libraries, shared libs? How do apps consume shared code?

• Grep for routing configuration (route definitions, guards, resolvers, lazy loading, canActivate)
• Find custom directives/pipes/hooks and their registration patterns
• Discover module/library organization (shared modules, feature modules, Nx library structure)
• Map directory structure conventions (where components, services, models, and specs live)
• Find build configuration and environment patterns (proxy configs, env-specific settings)

Phase 3: Analyze & Generate

Read full report. Apply fresh-eyes protocol:

Round 1 (main agent): Build section drafts from report findings.

Round 2 (fresh sub-agent, zero memory):

• Does every code example exist at the claimed file:line? (Glob + Grep verify)
• Do base class names in examples match actual class definitions? (Grep verify)
• Are store method names real (not hallucinated)? (Grep verify)
• Are cleanup patterns documented with actual implementation evidence?

Target Sections

Section	Content
Component Base Classes	Hierarchy with what each base provides; when to use which
State Management	Store pattern, reactivity approach, data flow conventions
Forms	Form creation pattern, validation approach, error display
API Services	Service base class, HTTP call pattern, error handling
Routing	Route definition pattern, guards, lazy loading, navigation conventions
Directives & Pipes	Custom reusable behaviors, naming conventions, registration
Directory Structure	Where things live: components, services, models, shared code
Subscription Cleanup	How subscriptions/listeners are managed and cleaned up
Styling Conventions	Component styling approach (scoped, BEM, utility classes)

Phase 4: Write & Verify

1. Write updated doc with <!-- Last scanned: YYYY-MM-DD --> at top
2. Surgical update only — preserve unchanged sections
3. Verify (Glob + Grep): ALL code example file paths exist AND class/method names match
4. Verify base class hierarchy from at least 3 concrete examples
5. Report: sections created vs updated, framework detected, gaps

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[IMPORTANT] Use task tracking to break ALL work into small tasks BEFORE starting — including tasks per file read. Prevents context loss from long files. Simple tasks: ask user whether to skip.

Prerequisites: MUST ATTENTION READ before executing:

Critical Thinking Mindset — Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources, admit uncertainty, self-check output, cross-reference independently. Certainty without evidence = root of all hallucination.

Scan & Update Reference Doc — Surgical updates only, NEVER full rewrite.

1. Read existing doc first — understand structure and manual annotations
2. Detect mode: Placeholder (headings only) → Init. Has content → Sync.
3. Scan codebase (grep/glob) for current patterns
4. Diff findings vs doc — identify stale sections only
5. Update ONLY diverged sections. Preserve manual annotations.
6. Update metadata (date, version) in frontmatter/header
7. NEVER rewrite entire doc. NEVER remove sections without evidence obsolete.

Output Quality — Token efficiency without sacrificing quality.

1. No inventories/counts — stale instantly
2. No directory trees — use 1-line path conventions
3. No TOCs — AI reads linearly
4. One example per pattern — only if non-obvious
5. Lead with answer, not reasoning
6. Sacrifice grammar for concision in reports
7. Unresolved questions at end

AI Mistake Prevention — Failure modes to avoid:

Verify AI-generated content against actual code. AI hallucinates class names, method signatures, and base class hierarchies. Grep to confirm existence before documenting. Trace full dependency chain after edits. Always trace full chain. Surface ambiguity before coding. NEVER pick silently. NEVER fabricate base class names, lifecycle hooks, or store method names. Grep to confirm before documenting.

IMPORTANT MUST ATTENTION read existing doc first, scan codebase, diff, surgical update only. Never rewrite entire doc.

IMPORTANT MUST ATTENTION output quality: no counts/trees/TOCs, 1 example per pattern, lead with answer.

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.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small task tracking tasks BEFORE starting IMPORTANT MUST ATTENTION detect framework in Phase 0 — agent patterns depend on framework IMPORTANT MUST ATTENTION cite file:line for every code example — NEVER fabricate class or method names IMPORTANT MUST ATTENTION sub-agents write findings incrementally after each category — NEVER batch at end IMPORTANT MUST ATTENTION if Round 1 finds issues, Round 2 fresh-eyes is non-negotiable after fixing. Clean Round 1 ENDS the scan.

Anti-Rationalization:

Evasion	Rebuttal
"Framework obvious, skip Phase 0 detection"	Phase 0 is BLOCKING — grep patterns and agent scope depend on detected framework
"Base class names look right"	Grep-verify ALL base class names — AI hallucinates class hierarchies
"Store method names are standard"	Every store method name must be grep-verified against actual source
"Skip Round 2 even when Round 1 found issues"	Clean Round 1 ends the scan. When issues exist, fresh-eyes mandatory after fixing — main agent rationalizes own fabricated examples.
"Cleanup pattern documented, 1 example enough"	Cleanup is the most project-specific pattern — verify with 3+ grep hits

[TASK-PLANNING] Before acting, analyze task scope and break 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

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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.

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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.