Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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。
Structural code graph queries via CodeGraphContext MCP (tree-sitter + KuzuDB). Find callers, callees, class hierarchies, dead code, and module dependencies.
インストール方法を見る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。
Structural code graph queries using the CodeGraphContext MCP server (tree-sitter AST + KuzuDB property graph).
| Need | Tool |
|---|---|
Who calls foo()? | find_callers (this skill) |
What does foo() call? | find_callees (this skill) |
| Class hierarchy / interface implementors | get_class_hierarchy (this skill) |
| Dead code / unreachable functions | find_dead_code (this skill) |
| Module-level import graph | get_module_deps (this skill) |
| Keyword / regex search | pnpm search:code or ripgrep |
| Semantic / conceptual search | code-semantic-search skill |
| AST shape matching | code-structural-search skill |
| Compiler-verified definition/references | lsp-navigator skill |
Use this skill when you need relationship traversal across the call graph or import graph, not text matching.
| Tool | Purpose | Key Parameters |
|---|---|---|
find_callers | All functions/methods that call a symbol | symbol, file?, depth? |
find_callees | All symbols called by a function | symbol, file?, depth? |
get_class_hierarchy | Superclasses, subclasses, interfaces | class_name, direction? |
find_dead_code | Functions with no callers in graph | scope?, min_confidence? |
get_module_deps | Import/require dependency graph | module, direction?, depth? |
query_graph | Raw Cypher query against KuzuDB | cypher, params? |
# Install CodeGraphContext MCP server
npm install -g @codetiger/code-graph-context-mcp
# Index your codebase (run from project root)
code-graph-context index --root . --lang typescript,javascript
Add to .claude/settings.json under mcpServers:
"CodeGraphContext": {
"command": "code-graph-context-mcp",
"args": ["--db", ".claude/context/data/code-graph.kuzu"]
}
// 1. Find all callers of a function
mcp__CodeGraphContext__find_callers({ symbol: 'shouldUseWorktree', depth: 2 });
// 2. Trace what a function depends on
mcp__CodeGraphContext__find_callees({ symbol: 'routeRequest', file: 'routing-table.cjs' });
// 3. Dead code candidates (low confidence = more results)
mcp__CodeGraphContext__find_dead_code({ scope: 'src/', min_confidence: 0.8 });
// 4. Raw Cypher for custom traversal
mcp__CodeGraphContext__query_graph({
cypher: 'MATCH (a:Function)-[:CALLS]->(b:Function) WHERE b.name = $name RETURN a',
params: { name: 'handleAuth' },
});
After graph analysis, record structural findings:
MemoryRecord({
type: 'pattern',
content: 'routeRequest has 12 callers — high-risk refactor target',
area: 'architecture',
});
MemoryRecord({
type: 'gotcha',
content: 'worktree-utils dead code: shouldPruneWorktree() never called',
area: 'cleanup',
});
CodeGraphContext supports two operation modes:
CLI mode (batch indexing, one-shot queries):
code-graph-context index --root . --lang typescript,javascript
code-graph-context query --cypher "MATCH (f:Function) RETURN f.name LIMIT 10"
MCP server mode (live, incremental — recommended for agent use):
npx @codetiger/code-graph-context-mcp --watch --db .claude/context/data/code-graph.kuzu
With --watch, the server monitors file changes and re-indexes incrementally. No manual re-index after refactors.
For large codebases (>100K nodes), replace KuzuDB with Neo4j:
code-graph-context index --root . --backend neo4j --uri bolt://localhost:7687
Add to settings.json:
"CodeGraphContext": {
"command": "code-graph-context-mcp",
"args": ["--backend", "neo4j", "--uri", "bolt://localhost:7687"]
}
Generate a browsable call graph:
code-graph-context visualize --output .claude/context/tmp/call-graph.html
For CI/CD pipelines, ship a pre-built graph bundle with the repo:
# In CI: build + archive
code-graph-context index --root . --export .claude/context/data/code-graph.bundle.gz
# In agent startup: restore
code-graph-context restore --bundle .claude/context/data/code-graph.bundle.gz
// Find high-complexity functions (cyclomatic > 10)
mcp__CodeGraphContext__query_graph({
cypher:
'MATCH (f:Function) WHERE f.complexity > $threshold RETURN f.name, f.file, f.complexity ORDER BY f.complexity DESC',
params: { threshold: 10 },
});
query_graph raw Cypher before checking if a purpose-built tool covers the needfind_dead_code results as certain — dynamic dispatch and reflection create false positives--watch MCP mode, manual re-index is not needed — avoid running index --incremental during active MCP sessionsSkill({ skill: 'code-graph-context' });
Invoke for: impact analysis before refactoring, call chain debugging, dead code audits, module dependency reviews, and architectural dependency mapping.
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
Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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。
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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。
N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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。
Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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。
Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
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。
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
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。