MCPInstall

qe-code-intelligence

Builds semantic code indexes, maps dependency graphs, and performs intelligent code search across large codebases. Use when understanding unfamiliar code, tracing call chains, analyzing import dependencies, or reducing context window usage through targeted retrieval.

Installs
118
Last 24h
—
Trending rank
—
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill qe-code-intelligence
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads qe-code-intelligence automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

QE Code Intelligence

Purpose

Guide the use of v3's code intelligence capabilities including knowledge graph construction, semantic code search, dependency mapping, and context-aware code understanding with significant token reduction.

Activation

  • When understanding unfamiliar code
  • When searching for code semantically
  • When analyzing dependencies
  • When building code knowledge graphs
  • When reducing context for AI operations

Quick Start

# Index codebase into knowledge graph
aqe code index src/ --incremental

# Semantic code search
aqe code search "authentication middleware"

# Analyze change impact
aqe code impact src/services/UserService.ts --depth 3

# Map dependencies
aqe code deps src/

# Analyze complexity and find hotspots
aqe code complexity src/

# Generate C4 architecture diagrams (Mermaid) with a confidence score
aqe code c4 .

Agent Workflow

// Build knowledge graph
Task("Index codebase", `
  Build knowledge graph for the project:
  - Parse all TypeScript files in src/
  - Extract entities (classes, functions, types)
  - Map relationships (imports, calls, inheritance)
  - Generate embeddings for semantic search
  Store in AgentDB vector database.
`, "qe-kg-builder")

// Semantic search
Task("Find relevant code", `
  Search for code related to "user authentication flow":
  - Use semantic similarity (not just keyword)
  - Include related functions and types
  - Rank by relevance score
  - Return with minimal context (80% token reduction)
`, "qe-code-intelligence")

Knowledge Graph Operations

1. Codebase Indexing

await knowledgeGraph.index({
  source: 'src/**/*.ts',
  extraction: {
    entities: ['class', 'function', 'interface', 'type', 'variable'],
    relationships: ['imports', 'calls', 'extends', 'implements', 'uses'],
    metadata: ['jsdoc', 'complexity', 'lines']
  },
  embeddings: {
    model: 'code-embedding',
    dimensions: 384,
    normalize: true
  },
  incremental: true  // Only index changed files
});

2. Semantic Search

await semanticSearcher.search({
  query: 'payment processing with stripe',
  options: {
    similarity: 'cosine',
    threshold: 0.7,
    limit: 20,
    includeContext: true
  },
  filters: {
    fileTypes: ['.ts', '.tsx'],
    excludePaths: ['node_modules', 'dist']
  }
});

3. Dependency Analysis

await dependencyMapper.analyze({
  entry: 'src/services/OrderService.ts',
  depth: 3,
  direction: 'both',  // imports and importedBy
  output: {
    graph: true,
    metrics: {
      afferentCoupling: true,
      efferentCoupling: true,
      instability: true
    }
  }
});

Token Reduction Strategy

// Get context with 80% token reduction
const context = await codeIntelligence.getOptimizedContext({
  query: 'implement user registration',
  budget: 4000,  // max tokens
  strategy: {
    relevanceRanking: true,
    summarization: true,
    codeCompression: true,
    deduplication: true
  },
  include: {
    signatures: true,
    implementations: 'relevant-only',
    comments: 'essential',
    examples: 'top-3'
  }
});

Knowledge Graph Schema

interface KnowledgeGraph {
  entities: {
    id: string;
    type: 'class' | 'function' | 'interface' | 'type' | 'file';
    name: string;
    file: string;
    line: number;
    embedding: number[];
    metadata: Record<string, any>;
  }[];
  relationships: {
    source: string;
    target: string;
    type: 'imports' | 'calls' | 'extends' | 'implements' | 'uses';
    weight: number;
  }[];
  indexes: {
    byName: Map<string, string[]>;
    byFile: Map<string, string[]>;
    byType: Map<string, string[]>;
  };
}

Search Results

interface SearchResult {
  entity: {
    name: string;
    type: string;
    file: string;
    line: number;
  };
  relevance: number;
  snippet: string;
  context: {
    before: string[];
    after: string[];
    related: string[];
  };
  explanation: string;
}

CLI Examples

# Full reindex
aqe code index src/

# Incremental index (changed files only)
aqe code index src/ --incremental

# Index only files changed since a git ref
aqe code index . --git-since HEAD~5

# Semantic code search
aqe code search "database connection"

# Change impact analysis
aqe code impact src/services/UserService.ts

# Dependency mapping
aqe code deps src/ --depth 5

# Complexity metrics and hotspots
aqe code complexity src/ --format json

Gotchas

  • WARNING: code-intelligence domain has 18% success rate — prefer direct grep/glob over agent-based code search for simple queries
  • Knowledge graph construction fails on repos >50K LOC — scope to specific modules
  • Semantic search returns irrelevant results without domain-specific embeddings — always verify search results manually
  • Agent claims "80% token reduction" but may skip critical context — verify key files are included in results
  • Fleet must be initialized before using: run aqe health to diagnose, or aqe init to re-initialize if you get initialization errors

Coordination

Primary Agents: qe-kg-builder, qe-dependency-mapper, qe-impact-analyzer, qe-code-complexity Coordinator: qe-code-intelligence Related Skills: qe-test-generation, qe-defect-intelligence

FAQ

What does the qe-code-intelligence skill do?

Builds semantic code indexes, maps dependency graphs, and performs intelligent code search across large codebases. Use when understanding unfamiliar code, tracing call chains, analyzing import dependencies, or reducing context window usage through targeted retrieval.

How do I install qe-code-intelligence?

Run npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill qe-code-intelligence in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/qe-code-intelligence/ (personal) or .claude/skills/qe-code-intelligence/ (project).

Which AI agents can use qe-code-intelligence?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is qe-code-intelligence safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains qe-code-intelligence?

It is published by proffesor-for-testing in proffesor-for-testing/agentic-qe. It has 118 recorded installs.

More from proffesor-for-testing/agentic-qe

View all →

code-review-quality

proffesor-for-testing/agentic-qe

Conduct context-driven code reviews focusing on quality, testability, and maintainability. Use when reviewing code, providing feedback, or establishing review practices.

compatibility-testing

proffesor-for-testing/agentic-qe

Cross-browser, cross-platform, and cross-device compatibility testing ensuring consistent experience across environments. Use when validating browser support, testing responsive design, or ensuring platform compatibility.

Testing & QA652 installs

api-testing-patterns

proffesor-for-testing/agentic-qe

Comprehensive API testing patterns including contract testing, REST/GraphQL testing, and integration testing. Use when testing APIs or designing API test strategies.

Testing & QA606 installs

regression-testing

proffesor-for-testing/agentic-qe

Open the skill to read its SKILL.md instructions.

Testing & QA331 installs

test-automation-strategy

proffesor-for-testing/agentic-qe

Open the skill to read its SKILL.md instructions.

Testing & QA254 installs

github-code-review

proffesor-for-testing/agentic-qe

Comprehensive GitHub code review with AI-powered swarm coordination

Popular ai & agents skills

View category →

google-agents-cli-publish

google/agents-cli

This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).

AI & Agents513.9K installs

google-agents-cli-eval

google/agents-cli

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

AI & Agents513.5K installs

skill-creator

anthropics/skills

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

OfficialAI & Agents416.4K installs

codex-pet

prime-skills/runcomfy-agent-skills

Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.

AI & Agents402.1K installs

full-output-enforcement

leonxlnx/taste-skill

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

AI & Agents401K installs

executing-plans

obra/superpowers

Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available

AI & Agents245.7K installs