Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Structural code graph queries via CodeGraphContext MCP (tree-sitter + KuzuDB). Find callers, callees, class hierarchies, dead code, and module dependencies.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
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.
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Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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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.
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Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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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.
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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
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