Debug

Debug a web/web-app issue by instrumenting code with structured logging via window.__debug_logs. This skill does NOT use console.log — all debug data is collected in a single global array for clean export and analysis.

How It Works

1. A global array window.__debug_logs collects structured log entries
2. Debug statements are inserted at key points in the code flow
3. The dev reproduces the bug, then copies window.__debug_logs to a JSON file
4. An agent reads that JSON to diagnose and fix the issue

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Phase 1: Understand the Bug

Analyze $ARGUMENTS and the relevant code to understand:

• What feature/component is affected?
• What is the expected vs actual behavior?
• What data flows through the affected code path?

Use AskUserQuestion if the bug description is unclear or if you need to narrow down the scope.

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Phase 2: Identify Key Instrumentation Points

Explore the codebase and identify every critical point in the code path where data changes or decisions are made. Typical points include:

• Initial load / mount: component mount, initial data fetch
• Data arrival: API responses, store hydration, prop changes
• User interactions: clicks, form changes, selections
• State transitions: state updates, effect triggers, re-renders
• Derived computations: filtered lists, computed values, transformations
• Error boundaries: catch blocks, error states, fallbacks

Map out these points before writing any code.

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Phase 3: Instrument the Code

3.1 — Initialize the global logger

Add this initialization at the app entry point or at the top of the root component/page being debugged (whichever is more appropriate):

// --- DEBUG START ---
if (typeof window !== 'undefined') {
  window.__debug_logs = []
}
// --- DEBUG END ---

3.2 — Add a helper (optional, for convenience)

If there are many log points, add a small helper near the initialization:

// --- DEBUG START ---
function __debugLog(key: string, data: Record<string, unknown>) {
  if (typeof window !== 'undefined' && window.__debug_logs) {
    window.__debug_logs.push({
      timestamp: Date.now(),
      key,
      ...data,
    })
  }
}
// --- DEBUG END ---

3.3 — Insert log points

At each instrumentation point, push a structured entry:

// --- DEBUG START ---
__debugLog('initial_data', {
  data: { id: product.id, status: product.status, price: product.price },
})
// --- DEBUG END ---

Log Entry Format

Every entry MUST have these fields:

Field	Type	Description
timestamp	number	Date.now() — milliseconds since epoch
key	string	Descriptive snake_case ID for this point (see naming conventions below)

Additional fields are added as needed per log point (e.g., data, props, state, error, response).

Key Naming Conventions

Use descriptive, snake_case keys that tell a story when read in sequence:

first_load
initial_props
fetch_start
fetch_response
state_after_fetch
on_filter_change
filtered_results
on_item_click
selected_item_data
on_submit
submit_response
error_caught

Data Pruning Rules

CRITICAL: Only log what's relevant to the bug. For each log point:

• ✅ Log IDs, statuses, counts, flags, selected values
• ✅ Log the specific fields that might be wrong
• ✅ Log array lengths instead of full arrays (unless the array content matters)
• ✅ Log error messages and codes
• ❌ Do NOT log entire API responses — pick the relevant fields
• ❌ Do NOT log full component props — pick what matters
• ❌ Do NOT log DOM elements or React internals
• ❌ Do NOT log large objects (images, blobs, full user profiles)

Example — instead of logging an entire product list:

// ❌ Bad: logs everything
__debugLog('products_loaded', { data: products })

// ✅ Good: logs what matters
__debugLog('products_loaded', {
  data: {
    count: products.length,
    firstId: products[0]?.id,
    lastId: products[products.length - 1]?.id,
    statuses: [...new Set(products.map(p => p.status))],
  },
})

Wrapping Convention

ALL debug code MUST be wrapped in clearly marked comments for easy removal:

// --- DEBUG START ---
__debugLog('some_key', { data: relevantData })
// --- DEBUG END ---

This makes cleanup trivial — search for DEBUG START and remove all blocks.

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Phase 4: Prepare the Debug Output File

4.1 — Find or create the output location

Check if there is a spec folder for the feature being debugged:

• Look for a matching folder in the specs directory (check project config or default .specs/)
• If a spec folder exists → create a .debug/ subfolder inside it
• If no spec folder exists → create .debug/ in the project root

4.2 — Create the empty log file

Determine the next available index:

.debug/logs-1.json
.debug/logs-2.json
.debug/logs-3.json
...

Create the file with a placeholder:

[]

4.3 — Tell the dev what to do

After instrumenting, output clear instructions:

Debug instrumentation is ready.

To capture logs:
1. Reproduce the bug in your browser
2. Open DevTools console and run: copy(JSON.stringify(window.__debug_logs, null, 2))
3. Paste into: <path-to-debug-file>
4. Then ask me to analyze the logs and fix the bug

To clean up after debugging:
- Search for "DEBUG START" and remove all blocks between DEBUG START/END markers

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Phase 5: Analyze Logs (when the dev comes back with filled logs)

If the user provides a populated debug JSON file or asks to analyze:

1. Read the JSON file
2. Build a timeline of events from the timestamp and key fields
3. Identify anomalies:
   • Unexpected data values
   • Missing expected log entries (gaps in the flow)
   • Wrong ordering of events
   • State inconsistencies between steps
4. Correlate findings with the code
5. Propose a fix

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Important Rules

• NO console.log — all logging goes through window.__debug_logs only
• Prune aggressively — each log entry should be small and focused
• Mark all debug code with // --- DEBUG START --- and // --- DEBUG END ---
• TypeScript: If the project uses TypeScript, add the global type declaration:

  // --- DEBUG START ---
  declare global {
    interface Window {
      __debug_logs: Array<Record<string, unknown>>
    }
  }
  // --- DEBUG END ---
  

• Don't break the app — debug instrumentation must not change any behavior
• Framework-aware: Use appropriate patterns for the framework (e.g., useEffect for React, onMounted for Vue, etc.)