Replay Buffer

Local experience replay: lookup known fixes before debugging, record new fixes, promote on success.

Mandatory Workflow

On ANY tool failure (non-zero exit or error output), execute in order:

Step A: Lookup First

Before exploring fixes, call the mcp__replay-memory__lookup_fix tool:

{
  "tool": "<tool name>",
  "args": ["<args>"],
  "stderr": "<stderr output>",
  "stdout": "<stdout if small>",
  "cwd": "<repo path>"
}

If confidence >= 0.7:

• Say: "Replay buffer hit: applying prior fix: "
• Apply the fix immediately (patch or described actions)
• Skip brainstorming

If no match: proceed with normal debugging.

Step B: Record Failure

On failure, call the mcp__replay-memory__record_failure tool:

{
  "tool": "<tool>",
  "args": ["<args>"],
  "exit_code": "<code>",
  "stderr": "<stderr>",
  "stdout": "<stdout>",
  "goal": "<what I was trying to do>"
}

Save returned failure_id for correlation.

Step C: Record Fix

After applying code edits, call the mcp__replay-memory__record_fix tool:

{
  "failure_id": "<failure_id>",
  "summary": "<1-sentence specific fix, e.g. 'Mock time.Now() in TestTokenRefresh setup'>",
  "patch": "<diff or file list>"
}

Step D: Promote on Success

When the same tool/test now passes, call the mcp__replay-memory__record_success tool:

{
  "failure_id": "<failure_id>"
}

If fix didn't work: do NOT promote. Try another fix.

Data Management Tools

Optional tools for managing replay buffer data:

List Failures

Browse recorded failures with filters:

{
  "limit": 50,
  "offset": 0,
  "tool_filter": "go test",
  "has_fix": true
}

Get Statistics

View overall success rate and top failing tools:

{}

Export Backup

Export all failures and fixes to JSON for backup:

{}

Clear Old Failures

Remove failures older than N days:

{
  "days": 30
}

Error Patterns to Watch

Invoke this skill when stderr/stdout contains:

• FAIL / FAILED / error / panic / exception
• error: / fatal: / compilation terminated
• Test framework failures
• Lint rule violations
• Build tool errors

Features

• Exact matching: Normalizes line numbers, timestamps, file paths, UUIDs
• Optional fuzzy search: Requires sentence-transformers package for vector similarity
• Secret redaction: Automatically redacts API keys, tokens, passwords before storage
• Confidence scoring: Fixes promoted after 2 confirmed successes

Guardrails

• Redact secrets before recording: API keys, tokens, passwords, credentials
• Prefer minimal patches: If diff is huge, store summary + key snippet only
• Don't force replay if codebase changed materially: treat as hint, not command
• Check stats periodically: Use get_statistics to see success rate and top issues