benchflow

Review Benchflow or SkillsBench task-run trajectories and integration-test Benchflow code changes. Use this skill whenever the user asks to audit traj health, failed or timed-out runs, healthy pass/fail/timeout status, no-skill leakage, skill loading, reward hacking, verifier isolation, metadata completeness, token usage, timing, Daytona-vs-Docker parity, path/root handling, coverage gaps, Docker/Daytona failures, or release-readiness of benchmark data.

Run agent benchmarks, create tasks, analyze results, and manage agents using BenchFlow. Use when asked to benchmark an AI coding agent, run a benchmark suite, create tasks, view trajectories, or compare agent performance.

Run agent benchmarks, create tasks, analyze results, and manage agents using BenchFlow. Use when asked to benchmark an AI coding agent, run a benchmark suite, create tasks, view trajectories, or compare agent performance.

Adopt, convert, verify, and publish upstream benchmarks as BenchFlow benchmarks. Use when asked to port a benchmark, create a BenchFlow adapter, write or review benchmarks/<name>/benchflow.py, run parity, route a benchmark through L1/L2/L3, or decide whether a benchmark should run natively, be translated, or run as-is.

Review benchflow documentation for drift, staleness, duplication, and alignment

Manage a BenchFlow release end-to-end — choose the channel (public vs internal-preview vs release-candidate), stage and publish it safely, and run the pre-tag audit gates. Use when the user says "release", "cut a release", "release candidate", "rc", "internal tag", "publish to PyPI", "prerelease", "tag v0.x", or asks how releases/versions/channels work here. Complements `launch-prep` (which mechanically prepares a public cut); this skill owns the channel decision, the RC-without-merging-to-main flow, and the audit gates.

Periodic audit of src/benchflow/ shape (names, boundaries, file sizes, stability mix) — propose structural reorg opportunities, don't execute

Pre-push branch reviewer — runs lint+typecheck+tests, then fans /code-cleanup, /test-review, /docs-review at the branch diff, merges findings by file

Two-pass subagent sweep for trivial/small refactoring wins — find candidates, then verify each before recommending

Prepare a benchflow release for launch. Use when the user says "prepare for launch", "release prep", "cut a release", "bump version", or "launch checklist". Runs docs/labs/code review, CI gate, e2e smoke test, CHANGELOG update, version bump, and opens a PR to main.

Mutation-kill oriented review of benchflow test files — find bloat to delete/collapse and coverage gaps to add, without naive deletion

Delegate complex coding tasks to a specialist model. Use when facing algorithmic challenges, performance optimization, or tricky debugging that benefits from focused code expertise.

Analyzes 3D mesh files (STL) to calculate geometric properties (volume, components) and extract attribute data. Use this skill to process noisy 3D scan data and filter debris.

Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

Write the conformance smoke output file when the task asks for conformance.txt.

Create a tiny task-specific skill pack for BenchFlow self-gen smoke tests.

Incorporate feedback from an independent code reviewer to improve your solution. The reviewer is a different agent that analyzed your work.

Verify academic citations, detect hallucinated BibTeX entries, repair DOI metadata, and produce normalized bibliography outputs without inventing sources.

Delegate complex coding tasks to a specialist model. Use when facing algorithmic challenges, performance optimization, or tricky debugging that benefits from focused code expertise.