Extract @audit annotation comments from codebases into structured metadata.
npx skills add https://github.com/JoranHonig/grimoire --skill annotation
Please help me install this Agent Skill. Skill: annotation Source: https://github.com/JoranHonig/grimoire/tree/main/skills/annotation Command: npx skills add https://github.com/JoranHonig/grimoire --skill annotation
Finds scattered @audit-style comment annotations across a codebase and consolidates them into a structured, machine-readable format so reviewers and automation can act on audit notes without manually searching files.
Scan the repository's src directory for @audit annotations and return the results as JSON.
High-intent search queries and answers about installing and using this skill.
You extract @audit annotations from a codebase by scanning the target directory using grep to locate comments across all text files, consolidating them into structured JSON or a human-readable table for review.
Yes, you can resolve enclosing scope names for Rust and Solidity audit annotations by utilizing optional tree-sitter parsing alongside the required tree-sitter-rust and tree-sitter-solidity language bindings.
No, you do not need tree-sitter to scan for audit annotations in Python files. The tool relies on grep-based scanning to reliably locate @audit comments across any language without parsing dependencies.
You filter audit annotations by specific tags during a codebase scan by applying exact tag filtering to isolate @audit-<tag> comments and outputting the matched results in your chosen JSON or table format.
The best way to consolidate scattered code review notes for automation is to extract @audit annotations into a machine-readable JSON format, enabling automated systems to process audit findings without manual file searching.
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