Explore AI Agent Skills & Claude Prompts

Guide for debugging and fixing bugs in the OCaml garbage collector runtime, particularly issues in memory management code like sweeping, pool management, and run-length compression. This skill should be used when encountering segfaults during OCaml bootstrap, debugging crashes in runtime/shared_heap.c or similar GC code, or investigating pointer arithmetic bugs in memory allocator implementations.

fix-ocaml-gc

Guide for debugging and fixing bugs in the OCaml garbage collector, particularly memory management issues in the runtime's sweeping and allocation code. This skill applies when working on OCaml runtime C code, investigating segfaults in GC operations, or fixing pointer arithmetic bugs in memory managers with size-classed pools and run-length encoding.

yelp-search

Search Yelp for local businesses, get contact info, ratings, and hours. Use when finding services (cleaners, groomers, restaurants, etc.), looking up business phone numbers to text, or checking ratings before booking. Triggers on queries about finding businesses, restaurants, services, or "look up on Yelp".

schedule Updated 5 months ago

gcode-to-text

Decode and interpret text content from G-code files by analyzing toolpath geometry and coordinate patterns. This skill should be used when extracting text, letters, or symbols that are encoded as movement commands in G-code files (e.g., 3D printing, CNC engraving, laser cutting). Applies to tasks like identifying what text a G-code file will print/engrave, reverse-engineering embossed or engraved text from toolpaths, or visualizing G-code geometry to reveal hidden content.

bn-fit-modify

Guidance for Bayesian Network DAG structure recovery, parameter learning, and causal intervention tasks. This skill should be used when tasks involve recovering DAG structure from observational data, learning Bayesian Network parameters, performing causal interventions (do-calculus), or generating samples from modified networks. Applies to tasks mentioning Bayesian networks, DAG recovery, structure learning, causal inference, or interventional distributions.

bn-fit-modify

Guide for Bayesian Network tasks involving structure learning, parameter fitting, intervention, and sampling. This skill should be used when working with pgmpy or similar libraries to recover DAG structures from data, fit conditional probability distributions, perform causal interventions (do-calculus), or sample from modified networks.

kv-store-grpc

Guide for implementing gRPC-based key-value store services in Python. This skill should be used when building gRPC servers with protobuf definitions, implementing KV store operations (Get, Set, Delete), or troubleshooting gRPC service connectivity. Applicable to tasks involving grpcio, protobuf code generation, and background server processes.

kv-store-grpc

Guidance for building gRPC-based key-value store services in Python. This skill should be used when tasks involve creating gRPC servers, defining protocol buffer schemas, or implementing key-value storage APIs with gRPC. Covers proto file creation, code generation, server implementation, and verification strategies.

crack-7z-hash

This skill provides guidance for cracking 7z archive password hashes. It should be used when tasked with recovering passwords from 7z encrypted archives, extracting and cracking 7z hashes, or working with password-protected 7z files in CTF challenges, security testing, or authorized recovery scenarios.

crack-7z-hash

This skill provides guidance for cracking 7z archive password hashes. It should be used when tasks involve extracting hashes from password-protected 7z archives, selecting appropriate cracking tools, and recovering passwords through dictionary or brute-force attacks. Applicable to password recovery, security testing, and CTF challenges involving encrypted 7z files.

raman-fitting

This skill provides guidance for Raman spectrum peak fitting tasks. It should be used when analyzing spectroscopic data, fitting Lorentzian or Gaussian peaks to Raman spectra, or working with graphene/carbon material characterization. The skill emphasizes critical data parsing verification, physical constraints from domain knowledge, and systematic debugging of curve fitting problems.

circuit-fibsqrt

Guide for implementing combinational/sequential logic circuits using gate-level descriptions in text-based simulators. This skill applies when building circuits for mathematical functions like integer square root, Fibonacci sequences, or similar computations that require both combinational logic (arithmetic operations) and sequential logic (feedback loops, state machines). Use this skill when the task involves generating gate netlists, implementing multi-bit arithmetic circuits, or debugging event-driven circuit simulators.