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click-path-audit

Trace every user-facing button/touchpoint through its full state change sequence to find bugs where functions individually work but cancel each other out, produce wrong final state, or leave the UI in an inconsistent state. Use when: systematic debugging found no bugs but users report broken buttons, or after any major refactor touching shared state stores.

O que é click-path-audit?

click-path-audit is a Claude Code agent skill that trace every user-facing button/touchpoint through its full state change sequence to find bugs where functions individually work but cancel each other out, produce wrong final state, or leave the UI in an inconsistent state. Use when: systematic debugging found no bugs but users report broken buttons, or after any major refactor touching shared state stores.

Funciona com~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/click-path-audit

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Documentação

/click-path-audit — Behavioural Flow Audit

Find bugs that static code reading misses: state interaction side effects, race conditions between sequential calls, and handlers that silently undo each other.

The Problem This Solves

Traditional debugging checks:

  • Does the function exist? (missing wiring)
  • Does it crash? (runtime errors)
  • Does it return the right type? (data flow)

But it does NOT check:

  • Does the final UI state match what the button label promises?
  • Does function B silently undo what function A just did?
  • Does shared state (Zustand/Redux/context) have side effects that cancel the intended action?

Real example: A "New Email" button called setComposeMode(true) then selectThread(null). Both worked individually. But selectThread had a side effect resetting composeMode: false. The button did nothing. 54 bugs were found by systematic debugging — this one was missed.


How It Works

For EVERY interactive touchpoint in the target area:

1. IDENTIFY the handler (onClick, onSubmit, onChange, etc.)
2. TRACE every function call in the handler, IN ORDER
3. For EACH function call:
   a. What state does it READ?
   b. What state does it WRITE?
   c. Does it have SIDE EFFECTS on shared state?
   d. Does it reset/clear any state as a side effect?
4. CHECK: Does any later call UNDO a state change from an earlier call?
5. CHECK: Is the FINAL state what the user expects from the button label?
6. CHECK: Are there race conditions (async calls that resolve in wrong order)?

Execution Steps

Step 1: Map State Stores

Before auditing any touchpoint, build a side-effect map of every state store action:

For each Zustand store / React context in scope:
  For each action/setter:
    - What fields does it set?
    - Does it RESET other fields as a side effect?
    - Document: actionName → {sets: [...], resets: [...]}

This is the critical reference. The "New Email" bug was invisible without knowing that selectThread resets composeMode.

Output format:

STORE: emailStore
  setComposeMode(bool) → sets: {composeMode}
  selectThread(thread|null) → sets: {selectedThread, selectedThreadId, messages, drafts, selectedDraft, summary} RESETS: {composeMode: false, composeData: null, redraftOpen: false}
  setDraftGenerating(bool) → sets: {draftGenerating}
  ...

DANGEROUS RESETS (actions that clear state they don't own):
  selectThread → resets composeMode (owned by setComposeMode)
  reset → resets everything

Step 2: Audit Each Touchpoint

For each button/toggle/form submit in the target area:

TOUCHPOINT: [Button label] in [Component:line]
  HANDLER: onClick → {
    call 1: functionA() → sets {X: true}
    call 2: functionB() → sets {Y: null} RESETS {X: false}  ← CONFLICT
  }
  EXPECTED: User sees [description of what button label promises]
  ACTUAL: X is false because functionB reset it
  VERDICT: BUG — [description]

Check each of these bug patterns:

Pattern 1: Sequential Undo

handler() {
  setState_A(true)     // sets X = true
  setState_B(null)     // side effect: resets X = false
}
// Result: X is false. First call was pointless.

Pattern 2: Async Race

handler() {
  fetchA().then(() => setState({ loading: false }))
  fetchB().then(() => setState({ loading: true }))
}
// Result: final loading state depends on which resolves first

Pattern 3: Stale Closure

const [count, setCount] = useState(0)
const handler = useCallback(() => {
  setCount(count + 1)  // captures stale count
  setCount(count + 1)  // same stale count — increments by 1, not 2
}, [count])

Pattern 4: Missing State Transition

// Button says "Save" but handler only validates, never actually saves
// Button says "Delete" but handler sets a flag without calling the API
// Button says "Send" but the API endpoint is removed/broken

Pattern 5: Conditional Dead Path

handler() {
  if (someState) {        // someState is ALWAYS false at this point
    doTheActualThing()    // never reached
  }
}

Pattern 6: useEffect Interference

// Button sets stateX = true
// A useEffect watches stateX and resets it to false
// User sees nothing happen

Step 3: Report

For each bug found:

CLICK-PATH-NNN: [severity: CRITICAL/HIGH/MEDIUM/LOW]
  Touchpoint: [Button label] in [file:line]
  Pattern: [Sequential Undo / Async Race / Stale Closure / Missing Transition / Dead Path / useEffect Interference]
  Handler: [function name or inline]
  Trace:
    1. [call] → sets {field: value}
    2. [call] → RESETS {field: value}  ← CONFLICT
  Expected: [what user expects]
  Actual: [what actually happens]
  Fix: [specific fix]

Scope Control

This audit is expensive. Scope it appropriately:

  • Full app audit: Use when launching or after major refactor. Launch parallel agents per page.
  • Single page audit: Use after building a new page or after a user reports a broken button.
  • Store-focused audit: Use after modifying a Zustand store — audit all consumers of the changed actions.

Recommended agent split for full app:

Agent 1: Map ALL state stores (Step 1) — this is shared context for all other agents
Agent 2: Dashboard (Tasks, Notes, Journal, Ideas)
Agent 3: Chat (DanteChatColumn, JustChatPage)
Agent 4: Emails (ThreadList, DraftArea, EmailsPage)
Agent 5: Projects (ProjectsPage, ProjectOverviewTab, NewProjectWizard)
Agent 6: CRM (all sub-tabs)
Agent 7: Profile, Settings, Vault, Notifications
Agent 8: Management Suite (all pages)

Agent 1 MUST complete first. Its output is input for all other agents.


When to Use

  • After systematic debugging finds "no bugs" but users report broken UI
  • After modifying any Zustand store action (check all callers)
  • After any refactor that touches shared state
  • Before release, on critical user flows
  • When a button "does nothing" — this is THE tool for that

When NOT to Use

  • For API-level bugs (wrong response shape, missing endpoint) — use systematic-debugging
  • For styling/layout issues — visual inspection
  • For performance issues — profiling tools

Integration with Other Skills

  • Run AFTER /superpowers:systematic-debugging (which finds the other 54 bug types)
  • Run BEFORE /superpowers:verification-before-completion (which verifies fixes work)
  • Feeds into /superpowers:test-driven-development — every bug found here should get a test

Example: The Bug That Inspired This Skill

ThreadList.tsx "New Email" button:

onClick={() => {
  useEmailStore.getState().setComposeMode(true)   // ✓ sets composeMode = true
  useEmailStore.getState().selectThread(null)      // ✗ RESETS composeMode = false
}}

Store definition:

selectThread: (thread) => set({
  selectedThread: thread,
  selectedThreadId: thread?.id ?? null,
  messages: [],
  drafts: [],
  selectedDraft: null,
  summary: null,
  composeMode: false,     // ← THIS silent reset killed the button
  composeData: null,
  redraftOpen: false,
})

Systematic debugging missed it because:

  • The button has an onClick handler (not dead)
  • Both functions exist (no missing wiring)
  • Neither function crashes (no runtime error)
  • The data types are correct (no type mismatch)

Click-path audit catches it because:

  • Step 1 maps selectThread resets composeMode
  • Step 2 traces the handler: call 1 sets true, call 2 resets false
  • Verdict: Sequential Undo — final state contradicts button intent

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

api-connector-builder

Build a new API connector or provider by matching the target repo

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