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Found 969 Skills
Per-client asset templates scoped by workspace.
Create a concise plan. Use when a user explicitly asks for a plan related to a coding task.
Configure and manage the GrepAI watch daemon. Use this skill for real-time code indexing and file monitoring.
Troubleshooting guide for GrepAI. Use this skill to diagnose and fix common issues.
Configure multi-project workspaces in GrepAI. Use this skill for monorepos and multiple related projects.
Configure Ollama as embedding provider for GrepAI. Use this skill for local, private embedding generation.
Generate a Codex Wrapped usage recap from local Codex logs, including last 30 days, last 7 days, and an all-time focus-hours callout. Use when the user asks for a usage summary, activity recap, or Codex Wrapped report.
Guidance for fixing LaTeX overfull hbox warnings by replacing words with shorter synonyms from an allowed list. This skill applies when tasks involve modifying LaTeX documents to eliminate typographic warnings while adhering to strict word replacement constraints. Use when dealing with synonym-constrained text editing in LaTeX or similar markup languages.
Integration patterns and best practices for adding persistent memory to LLM agents using the Letta Learning SDK
Comprehensive guide for developing Letta agents, including architecture selection, memory design, model selection, and tool configuration. Use when building or troubleshooting Letta agents.
Guide for building CompCert, the formally verified C compiler, from source. This skill should be used when compiling, building, or installing CompCert, or when working with Coq-based software that has strict dependency version requirements. Covers OCaml/opam setup, Coq version compatibility, memory management, and common build pitfalls.
Guidance for implementing PyTorch pipeline parallelism for distributed model training. This skill should be used when tasks involve implementing pipeline parallelism, distributed training with model partitioning across GPUs/ranks, AFAB (All-Forward-All-Backward) scheduling, or inter-rank tensor communication using torch.distributed.