Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
日本語の概要は準備中です。原文の説明を表示しています。
Traces execution paths through the code graph with criticality scoring and Mermaid charts. Use when understanding how a function propagates through the system.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Trace execution flows through the codebase using the code knowledge graph.
cartograph:dependency-graph)pensive:blast-radius)This skill requires the gauntlet plugin for graph data. Discover it:
GRAPH_QUERY=$(find ~/.claude/plugins -name "graph_query.py" -path "*/gauntlet/*" 2>/dev/null | head -1)
If gauntlet is not installed: Fall back to static
analysis. Use grep to trace function calls and build
a Mermaid diagram manually from import/call patterns.
Skip graph-specific steps.
If installed but no graph.db: Tell the user to run
/gauntlet-graph build.
Accept target: Get a function name or entry point from the user (or trace all entry points).
Run flow tracing (requires gauntlet):
python3 "$GRAPH_QUERY" --action flows --depth 15
To filter by entry point:
python3 "$GRAPH_QUERY" --action flows --entry "main"
Fallback (no gauntlet): Trace calls with rg (or grep):
# Prefer rg (ripgrep) for speed; fall back to grep
if command -v rg &>/dev/null; then
rg -n "function_name\(" --type py . | head -20
else
grep -rn "function_name(" --include="*.py" . | head -20
fi
Build the call tree manually from search results.
Display as indented tree:
main() [criticality: 0.72]
-> validate_input()
-> parse_config()
-> process_data()
-> db.execute_query()
-> cache.store()
-> send_response()
Generate Mermaid flowchart:
flowchart LR
main --> validate_input
main --> process_data
main --> send_response
validate_input --> parse_config
process_data --> db.execute_query
process_data --> cache.store
Show criticality breakdown:
| Factor | Weight | Meaning |
|---|---|---|
| File spread | 0.30 | Touches many files |
| Security | 0.25 | Contains auth/crypto code |
| External calls | 0.20 | Unresolved dependencies |
| Test gap | 0.15 | Untested nodes in flow |
| Depth | 0.10 | Deep call chains |
[criticality: N.NN]flowchart LR generated with edges representing
each caller-to-callee relationship in the traced pathrg/grep
analysis is used and the absence of graph data is notedgraph.db is absent, user is
told to run /gauntlet-graph build before the skill haltsまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
日本語の概要は準備中です。原文の説明を表示しています。
Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.
日本語の概要は準備中です。原文の説明を表示しています。
Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.
日本語の概要は準備中です。原文の説明を表示しています。
Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.
日本語の概要は準備中です。原文の説明を表示しています。
Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.
日本語の概要は準備中です。原文の説明を表示しています。