Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
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Builds or updates the code knowledge graph via tree-sitter AST and SQLite. Use when setting up the graph before search or blast-radius analysis.
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See how to installReview the instructions the agent will receive before you install.
Build or update the .gauntlet/graph.db knowledge graph
for the current codebase.
Detect target: Use the current working directory or a user-specified path.
Check for existing graph: If .gauntlet/graph.db
exists, run an incremental update. Otherwise, run a
full build.
Run the build script:
For full build:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/graph_build.py <dir>
For incremental update:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/graph_build.py <dir> --incremental
Report results: Show the JSON output including files parsed, nodes created, edges created, and duration.
Suggest next steps: Recommend searching the graph or running blast radius analysis.
gauntlet:graph-search)gauntlet:extract)The graph extracts nodes (File, Class, Function, Type, Test) and edges (CALLS, IMPORTS_FROM, INHERITS, CONTAINS, IMPLEMENTS, TESTED_BY) from 20+ languages including Python, JavaScript, TypeScript, Go, Rust, Java, C/C++, Ruby, and PHP.
.gauntlet/graph.db (SQLite with WAL mode).gauntlet/.gitignore to prevent commits.gauntlet/graph.db exists and is a valid SQLite file after
the skill completes; .gauntlet/.gitignore exists to prevent
the database from being committedfiles_parsed,
nodes_created, edges_created, duration; values are
non-zero for non-empty codebases.gauntlet/graph.db already
exists (script invoked with --incremental); full build only
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Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
The English summary is being prepared. Showing the original description.
Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.
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Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.
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Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
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Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.
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Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.
The English summary is being prepared. Showing the original description.