Find a file's local imports, reverse imports and tests connected by imports. Each relationship includes a source path and line as evidence. Static file relationships, not runtime callers or test coverage. Scans JavaScript/TypeScript including tests, with bounded work and explicit unresolved imports and scan limits. Deterministic; no provider call.

Return static complexity metrics and a heuristic risk score (0-1) for a single JavaScript or TypeScript file. Deterministic and fast — no model call. Call this when reviewing a file to find out where the structural risk sits (nested loops, long functions, async boundaries, unguarded mutation) before reading the whole file yourself.

Walk a directory and rank its JavaScript/TypeScript files by risk density — how concentrated the failure-prone code is, not how big the file is. Test files are left out by default; pass includeTests to rank them too. Deterministic and fast — no model call. Call this at the start of a code review to decide which files are worth your attention, instead of reading the tree in arbitrary order.

Score a log file's lines by severity and how unusual their wording is, and return the anomalies, worst first. Deterministic — no model call, no API key. Call this when you have a log file and want the handful of lines worth reading rather than the whole file.

Combine static analysis with a second-opinion verdict from the signed-in Claude Code, Codex, or GitHub Copilot CLI, returning the most likely runtime failure with a line number and reason. status distinguishes actionable, uncertain, no-finding, and unavailable results. checked lists the bug categories the model reports having considered, so a clean file weighed against the whole catalogue is distinguishable from one where it stopped early; it is a self-report, and an empty list means no coverage was reported. Pass multi: true to get every finding the model can demonstrate, ranked, in a findings array instead of one verdict — experimental, and more findings per call is also more surface for false positives per call. Treat it as a defect only when actionable is true; that applies the measured score >= 0.7 precision gate. This spawns another model and takes 5-15 seconds, so only call it when you specifically want an independent second opinion. If you are yourself reviewing the code, use analyze_file and read the source instead. Reviewing several files? Pass them all as files in one call rather than calling once per file: the verdicts run concurrently, so the batch costs the same and takes about as long as a single file.

Report which supported CLIs (Claude Code, Codex, GitHub Copilot) are installed and signed in. Call this to diagnose why predict_failures is failing.