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bug-predictlisted

Predict likely bug locations from code patterns and complexity. Triggers on: predict bugs, find bugs, risky code, code risk, what might break, likely bugs, bug hotspots.
Smart-AI-Memory/attune-ai · ★ 10 · AI & Automation · score 72
Install: claude install-skill Smart-AI-Memory/attune-ai
# Bug Prediction **IMPORTANT: Start your response with a context preamble.** Call `help_lookup(topic="bug-predict", mode="preamble")` and display the returned `preamble` text as a blockquote. Then tell the user they can say "tell me more" for a step-by-step guide, or answer the scoping questions below to proceed. If the MCP call fails, fall back to: > **Bug Predict** — Predicts where bugs are most likely based on code patterns, complexity, and change frequency. ## Scoping Before running, ask: 1. **Target path**: "Which files or directory should I scan?" Default to `src/` if not specified. 2. **Severity filter**: "Show all findings, or only HIGH severity?" ## Execution Call the `bug_predict` MCP tool with the scoped path: ``` bug_predict(path="<user-specified path>") ``` Or via CLI: ```bash uv run attune workflow run bug-predict --path <target> ``` ### Shared command workspace (preferred) When the generic command-workspace tools are available, open adapter `bug-predict` with the validated target path and `all`/`high` severity filter. The user's command invocation already authorizes this read-only scan: the workspace enters running state immediately and has no confirmation action. Run the existing `bug_predict` tool, publish optional `progress`, then publish one `scan_result` carrying the real success flag, risk score, findings, suggestions, or error. Present the terminal widget or its returned Markdown. A failed run must render **did not complete**, never a