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Found 10 Skills
Token-efficient GitHub source code exploration via tree-sitter AST parsing and structured retrieval
Finds and recovers content from Claude Code session history files. This skill should be used when searching for deleted files, tracking changes across sessions, analyzing conversation history, or recovering code from previous Claude interactions. Triggers include mentions of "session history", "recover deleted", "find in history", "previous conversation", or ".claude/projects".
Only responsible for answering questions, finding answers from documents and code, read-only, no code modification allowed.
Benchmark CodeGraph retrieval quality on a real codebase by comparing agent behavior with vs without CodeGraph. Use when the user runs /agent-eval or asks to test, benchmark, audit, or validate a codegraph version (the local dev build or a published npm version) against a language's repo.
Guide for setup Serena MCP server for semantic code retrieval and editing capabilities
Interpret the meaning of paper figures and output a highly readable Markdown report that 'teaches humans how to read figures'; supports input of absolute paths to one or more figure files and manual interpretations, automatically attempts to retrieve the source code used to generate the figures from the vicinity of the figures, and uses a parallel-vibe-like approach to interpret each figure with process-level isolation via `codex exec`/`claude -p` (default concurrency limit is 3, adjustable in config.yaml). ⚠️ Not applicable: Users only want to adjust figure size/crop/change format; or request direct modification of images/source code (this skill has read-only access to images and source code throughout, modification is strictly prohibited).
Evidence-first live messaging workflow for ECC. Use when the user wants to read texts or DMs, recover a recent one-time code, inspect a thread before replying, or prove which message source was actually checked.
Fetch source code for npm, PyPI, or crates.io packages and GitHub/GitLab repos to provide AI agents with implementation context beyond types and docs. Use when needing to understand how a library works internally, debug dependency issues, or explore package implementations.
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.
Guide for setup Serena MCP server for semantic code retrieval and editing capabilities