Agent Skills: characterization-test-generator
Generates tests that capture current behavior of existing code before refactoring. Use when you need a safety net before AI-assisted refactoring or modifying legacy code.
ID: rshankras/claude-code-apple-skills/characterization-test-generator
73770
Install this agent skill to your local
Skill Files
The files that make up characterization-test-generator.
More agent skills
- interpolationProblem-solving strategies for interpolation in numerical methods
- lean4-theorem-provingUse when working with Lean 4 (.lean files), writing mathematical proofs, seeing "failed to synthesize instance" errors, managing sorry/axiom elimination, or searching mathlib for lemmas - provides build-first workflow, haveI/letI patterns, compiler-guided repair, and LSP integration
- diffdockDiffDock and DiffDock-L molecular docking. Use for protein-small-molecule pose prediction from PDB or sequence plus SMILES/SDF/MOL2, batch docking, virtual screening, and pose-confidence interpretation. Not for binding affinity prediction.
- filtering-bot-trafficIdentify, measure, and exclude bot / crawler / AI-agent traffic in PostHog web and product analytics using the traffic classification surface (the isLikelyBot / getTrafficType HogQL functions and the $virt_* virtual properties). Use when the user asks to "exclude bots", "filter out crawlers", "remove bot traffic from my numbers", "how much of my traffic is bots / AI crawlers", "is GPTBot / ChatGPT / Claude hitting my site", "break down traffic by human vs bot", or wants clean human-only counts in an insight or dashboard. For the real-time Live tab bot tiles, use exploring-live-traffic instead.
- clawhub-installerInstalls 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabilities or when a bioinformatics task requires specialized skills not yet installed.
- systematic-debuggingFour-phase debugging methodology with root cause analysis. Use when investigating bugs, fixing test failures, or troubleshooting unexpected behavior. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST.