tree-sitting/SKILL.md
AST-powered code navigation via tree-sitter. Auto-scans codebases and provides progressive-disclosure tree views with symbol search, source retrieval, and reference finding. Each invocation is self-contained — no cross-process state. Use when exploring unfamiliar repos, navigating code, or needing fast symbol lookup. Triggers on "map this codebase", "explore repo", "find symbol", "navigate code", "tree-sitter", or when starting work on an unfamiliar repository.
npx skillsauth add oaustegard/claude-skills tree-sittingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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AST-powered code navigation using tree-sitter. Each invocation auto-scans the codebase (~700ms for 250 files), then runs queries at sub-millisecond speed.
uv pip install --system --break-system-packages tree-sitter
Grammars are loaded from bundled parsers/*.so files — no network fetch,
no tree-sitter-language-pack dependency. Install is <1s.
Every call auto-scans, prints a tree overview, then runs any queries. No state to manage between calls.
TREESIT=/mnt/skills/user/tree-sitting/scripts/treesit.py
# Orient: root-level overview (default depth=1)
python3 $TREESIT /path/to/repo
# Featuring: complete tree, minimal detail
python3 $TREESIT /path/to/repo --depth=-1 --detail=sparse
# Explore a subdirectory in full detail
python3 $TREESIT /path/to/repo --path=src/core --detail=full
# Run queries (tree overview + query results)
python3 $TREESIT /path/to/repo 'find:Parser*' 'source:parse_input'
# Queries only, no tree
python3 $TREESIT /path/to/repo --no-tree 'refs:AuthToken'
| Option | Default | Description |
|--------|---------|-------------|
| --depth N | 1 | Directory depth: -1=all, 0=root only, 1=one level |
| --detail LEVEL | normal | Node detail: sparse, normal, full |
| --path DIR | (root) | Scope to subdirectory |
| --skip DIRS | | Extra dirs to skip (comma-separated) |
| --no-tree | | Suppress tree overview, show only queries |
| --stats | | Show scan timing and counts |
All levels include line ranges (:start-end) so you can feed the
window straight into Read --offset/--limit without another scan.
| Level | Tree-overview row (per file) | Use case |
|-------|------------------------------|----------|
| sparse | file: name:1-10, Other:30-90 +3 | featuring: see the full shape |
| normal | file: name(f):1-10, Other(c):30-90 +3 | exploring: quick orientation |
| full | full per-symbol formatter + children + imports | exploring: deep dive into a directory |
Append after the repo path. Multiple queries per call.
| Query | Example | Description |
|-------|---------|-------------|
| find:PATTERN[:KIND[:LIMIT]] | find:*Handler*:function | Symbol search (glob/substring) |
| symbols:FILE | symbols:src/api.py | All symbols in a file |
| source:SYMBOL[:FILE] | source:parse_input | Source code of a symbol |
| refs:SYMBOL[:LIMIT] | refs:AuthToken:30 | Text references across codebase |
| imports:FILE | imports:src/api.py | Import list for a file |
| dir:PATH | dir:src/core | Directory overview (engine format) |
1. treesit.py /repo → orient: what dirs, how big
2. treesit.py /repo --path=src/core → drill into interesting directory
3. treesit.py /repo 'find:Parser*' → find specific symbols
4. treesit.py /repo 'source:parse_input' → read implementation
5. treesit.py /repo 'refs:ParseState' → find usage across codebase
Each call is self-contained. No need to "scan first, query later" — scan happens automatically every time (~700ms).
For custom scripts that need the engine API directly:
import sys; sys.path.insert(0, '/mnt/skills/user/tree-sitting/scripts')
from engine import CodeCache
cache = CodeCache()
cache.scan('/path/to/repo')
# All queries in the SAME invocation:
print(cache.tree_overview())
print(cache.find_symbol('ClassName'))
print(cache.get_source_range('src/core/parser.c', 100, 150))
Important: The cache is in-memory only. All scan + query calls MUST
happen in the same Python process. Splitting across separate python -c
invocations loses the cache — use treesit.py instead.
Bundled grammars (work out of the box): Python, JavaScript, TypeScript, TSX, Go, Rust, Ruby, Java, C, HTML, Markdown, Mojo.
Three-tier extraction for bundled languages:
Files with unsupported extensions are silently skipped (they show as SKIP (no parser) with --stats). To add a grammar, drop a compiled libtree_sitter_<lang>.so into parsers/ — the engine picks it up automatically on the next run. Build from the grammar's repo (each tree-sitter/tree-sitter-<lang> repo has a src/ directory you can compile with cc -shared -fPIC -I src src/parser.c src/scanner.c -o libtree_sitter_<lang>.so, or use tree-sitter build).
If you need a language urgently and can't build the .so, you can try installing tree-sitter-language-pack as a fallback (uv pip install --system --break-system-packages 'tree-sitter-language-pack<1.6.3') — but note 1.6.3 ships a broken wheel (only _native/, missing the tree_sitter_language_pack/ python module → ModuleNotFoundError despite pip showing it installed); 1.6.2 and earlier work, hence the <1.6.3 pin and try to download grammars at runtime from a domain that may not be in your network allowlist. Bundling the .so is the reliable path.
///, #CodeCache (in-memory, per-invocation)
├── files: {relpath → FileEntry(source, tree, symbols, imports)}
├── _symbol_index: {name → [Symbol, ...]} ← fast lookup
└── methods: scan(), find_symbol(), file_symbols(), dir_overview(), ...
│
└── treesit.py CLI — auto-scan + progressive-disclosure tree + queries
Parse cost is paid once per invocation. The symbol index enables O(1) exact match and O(n) substring/glob search where n is the number of unique symbol names (not files).
testing
Disciplined, validation-gated revision of an EXISTING skill so each edit is a measured improvement rather than a guess. Use when editing, revising, or tuning a skill that already exists and there is evidence it underperforms (observed failures, drift, complaints) — invoke by name, or have versioning-skills / creating-skill defer to it before applying edits. Not for authoring a brand-new skill from scratch (use creating-skill) or one-off prose.
development
Skill-aware orchestration with context routing. Decomposes complex tasks into skill-typed subtasks, extracts targeted context subsets, executes subagents in parallel, and synthesizes results. Self-answers trivial lookups inline. No SDK dependency — uses raw HTTP via httpx. Use when tasks require multiple analytical perspectives, when context is large and subtasks only need portions, or when orchestrating-agents spawns too many redundant subagents.
tools
Orchestrates parallel API instances, delegated sub-tasks, and multi-agent workflows with streaming and tool-enabled delegation patterns. Use for parallel analysis, multi-perspective reviews, or complex task decomposition.
development
Invokes Google Gemini models for structured outputs, image generation, multi-modal tasks, and Google-specific features. Use when users request Gemini, image generation, structured JSON output, Google API integration, or cost-effective parallel processing.