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Codeql

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codeql

Comprehensive guide for setting up and configuring CodeQL code scanning via GitHub Actions workflows and the CodeQL CLI. This skill should be used when users need help with code scanning configuration, CodeQL workflow files, CodeQL CLI commands, SARIF output, security analysis setup, or troubleshooting CodeQL analysis.

Overview

Publishergithub
Repositoryawesome-copilot
Skill namecodeql
Stars
39.6K
Forks
5K
Bundled files
6
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by github on GitHub. Read the source before you install it.

Installation

Install the Codeql AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/github/awesome-copilot/tree/main/skills/codeql
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p .claude/skills
cp -r /tmp/awesome-copilot/skills/codeql .claude/skills/codeql
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codeql in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Codeql on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Codeql is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CodeQL Code Scanning

This skill provides procedural guidance for configuring and running CodeQL code scanning — both through GitHub Actions workflows and the standalone CodeQL CLI.

When to Use This Skill

Use this skill when the request involves:

  • Creating or customizing a codeql.yml GitHub Actions workflow
  • Choosing between default setup and advanced setup for code scanning
  • Configuring CodeQL language matrix, build modes, or query suites
  • Running CodeQL CLI locally (codeql database create, database analyze, github upload-results)
  • Understanding or interpreting SARIF output from CodeQL
  • Troubleshooting CodeQL analysis failures (build modes, compiled languages, runner requirements)
  • Setting up CodeQL for monorepos with per-component scanning
  • Configuring dependency caching, custom query packs, or model packs

Supported Languages

CodeQL supports the following language identifiers:

LanguageIdentifierAlternatives
C/C++c-cppc, cpp
C#csharp—
Gogo—
Java/Kotlinjava-kotlinjava, kotlin
JavaScript/TypeScriptjavascript-typescriptjavascript, typescript
Pythonpython—
Rubyruby—
Rustrust—
Swiftswift—
GitHub Actionsactions—

Alternative identifiers are equivalent to the standard identifier (e.g., javascript does not exclude TypeScript analysis).

Core Workflow — GitHub Actions

Step 1: Choose Setup Type

  • Default setup — Enable from repository Settings → Advanced Security → CodeQL analysis. Best for getting started quickly. Uses none build mode for most languages.
  • Advanced setup — Create a .github/workflows/codeql.yml file for full control over triggers, build modes, query suites, and matrix strategies.

To switch from default to advanced: disable default setup first, then commit the workflow file.

Step 2: Configure Workflow Triggers

Define when scanning runs:

yaml
on:
  push:
    branches: [main, protected]
  pull_request:
    branches: [main]
  schedule:
    - cron: '30 6 * * 1'  # Weekly Monday 6:30 UTC
  • push — scans on every push to specified branches; results appear in Security tab
  • pull_request — scans PR merge commits; results appear as PR check annotations
  • schedule — periodic scans of the default branch (cron must exist on default branch)
  • merge_group — add if repository uses merge queues

To skip scans for documentation-only PRs:

yaml
on:
  pull_request:
    paths-ignore:
      - '**/*.md'
      - '**/*.txt'

paths-ignore controls whether the workflow runs, not which files are analyzed.

Step 3: Configure Permissions

Set least-privilege permissions:

yaml
permissions:
  security-events: write   # Required to upload SARIF results
  contents: read            # Required to checkout code
  actions: read             # Required for private repos using codeql-action

Step 4: Configure Language Matrix

Use a matrix strategy to analyze each language in parallel:

yaml
jobs:
  analyze:
    name: Analyze (${{ matrix.language }})
    runs-on: ubuntu-latest
    strategy:
      fail-fast: false
      matrix:
        include:
          - language: javascript-typescript
            build-mode: none
          - language: python
            build-mode: none

For compiled languages, set the appropriate build-mode:

  • none — no build required (supported for C/C++, C#, Java, Rust)
  • autobuild — automatic build detection
  • manual — custom build commands (advanced setup only)

For detailed per-language autobuild behavior and runner requirements, search references/compiled-languages.md.

Step 5: Configure CodeQL Init and Analysis

yaml
steps:
  - name: Checkout repository
    uses: actions/checkout@v4

  - name: Initialize CodeQL
    uses: github/codeql-action/init@v4
    with:
      languages: ${{ matrix.language }}
      build-mode: ${{ matrix.build-mode }}
      queries: security-extended
      dependency-caching: true

  - name: Perform CodeQL Analysis
    uses: github/codeql-action/analyze@v4
    with:
      category: "/language:${{ matrix.language }}"

Query suite options:

  • security-extended — default security queries plus additional coverage
  • security-and-quality — security plus code quality queries
  • Custom query packs via packs: input (e.g., codeql/javascript-queries:AlertSuppression.ql)

Dependency caching: Set dependency-caching: true on the init action to cache restored dependencies across runs.

Analysis category: Use category to distinguish SARIF results in monorepos (e.g., per-language, per-component).

Step 6: Monorepo Configuration

For monorepos with multiple components, use the category parameter to separate SARIF results:

yaml
category: "/language:${{ matrix.language }}/component:frontend"

To restrict analysis to specific directories, use a CodeQL configuration file (.github/codeql/codeql-config.yml):

yaml
paths:
  - apps/
  - services/
paths-ignore:
  - node_modules/
  - '**/test/**'

Reference it in the workflow:

yaml
- uses: github/codeql-action/init@v4
  with:
    config-file: .github/codeql/codeql-config.yml

Step 7: Manual Build Steps (Compiled Languages)

If autobuild fails or custom build commands are needed:

yaml
- language: c-cpp
  build-mode: manual

Then add explicit build steps between init and analyze:

yaml
- if: matrix.build-mode == 'manual'
  name: Build
  run: |
    make bootstrap
    make release

Core Workflow — CodeQL CLI

Step 1: Install the CodeQL CLI

Download the CodeQL bundle (includes CLI + precompiled queries):

bash
# Download from https://github.com/github/codeql-action/releases
# Extract and add to PATH
export PATH="$HOME/codeql:$PATH"

# Verify installation
codeql resolve packs
codeql resolve languages

Always use the CodeQL bundle, not a standalone CLI download. The bundle ensures query compatibility and provides precompiled queries for better performance.

Step 2: Create a CodeQL Database

bash
# Single language
codeql database create codeql-db \
  --language=javascript-typescript \
  --source-root=src

# Multiple languages (cluster mode)
codeql database create codeql-dbs \
  --db-cluster \
  --language=java,python \
  --command=./build.sh \
  --source-root=src

For compiled languages, provide the build command via --command.

Step 3: Analyze the Database

bash
codeql database analyze codeql-db \
  javascript-code-scanning.qls \
  --format=sarif-latest \
  --sarif-category=javascript \
  --output=results.sarif

Common query suites: <language>-code-scanning.qls, <language>-security-extended.qls, <language>-security-and-quality.qls.

Step 4: Upload Results to GitHub

bash
codeql github upload-results \
  --repository=owner/repo \
  --ref=refs/heads/main \
  --commit=<commit-sha> \
  --sarif=results.sarif

Requires GITHUB_TOKEN environment variable with security-events: write permission.

CLI Server Mode

To avoid repeated JVM initialization when running multiple commands:

bash
codeql execute cli-server

For detailed CLI command reference, search references/cli-commands.md.

Alert Management

Severity Levels

Alerts have two severity dimensions:

  • Standard severity: Error, Warning, Note
  • Security severity: Critical, High, Medium, Low (derived from CVSS scores; takes display precedence)

Copilot Autofix

GitHub Copilot Autofix generates fix suggestions for CodeQL alerts in pull requests automatically — no Copilot subscription required. Review suggestions carefully before committing.

Alert Triage in PRs

  • Alerts appear as check annotations on changed lines
  • Check fails by default for error/critical/high severity alerts
  • Configure merge protection rulesets to customize the threshold
  • Dismiss false positives with a documented reason for audit trail

For detailed alert management guidance, search references/alert-management.md.

Custom Queries and Packs

Using Custom Query Packs

yaml
- uses: github/codeql-action/init@v4
  with:
    packs: |
      my-org/my-security-queries@1.0.0
      codeql/javascript-queries:AlertSuppression.ql

Creating Custom Query Packs

Use the CodeQL CLI to create and publish packs:

bash
# Initialize a new pack
codeql pack init my-org/my-queries

# Install dependencies
codeql pack install

# Publish to GitHub Container Registry
codeql pack publish

CodeQL Configuration File

For advanced query and path configuration, create .github/codeql/codeql-config.yml:

yaml
paths:
  - apps/
  - services/
paths-ignore:
  - '**/test/**'
  - node_modules/
queries:
  - uses: security-extended
packs:
  javascript-typescript:
    - my-org/my-custom-queries

Code Scanning Logs

Summary Metrics

Workflow logs include key metrics:

  • Lines of code in codebase — baseline before extraction
  • Lines extracted — including external libraries and auto-generated files
  • Extraction errors/warnings — files that failed or produced warnings during extraction

Debug Logging

To enable detailed diagnostics:

  • GitHub Actions: re-run the workflow with "Enable debug logging" checked
  • CodeQL CLI: use --verbosity=progress++ and --logdir=codeql-logs

Troubleshooting

Common Issues

ProblemSolution
Workflow not triggeringVerify on: triggers match event; check paths/branches filters; ensure workflow exists on target branch
Resource not accessible errorAdd security-events: write and contents: read permissions
Autobuild failureSwitch to build-mode: manual and add explicit build commands
No source code seenVerify --source-root, build command, and language identifier
C# compiler failureCheck for /p:EmitCompilerGeneratedFiles=true conflicts with .sqlproj or legacy projects
Fewer lines scanned than expectedSwitch from none to autobuild/manual; verify build compiles all source
Kotlin in no-build modeDisable and re-enable default setup to switch to autobuild
Cache miss every runVerify dependency-caching: true on init action
Out of disk/memoryUse larger runners; reduce analysis scope via paths config; use build-mode: none
SARIF upload failsEnsure token has security-events: write; check 10 MB file size limit
SARIF results exceed limitsSplit across multiple uploads with different --sarif-category; reduce query scope
Two CodeQL workflowsDisable default setup if using advanced setup, or remove old workflow file
Slow analysisEnable dependency caching; use --threads=0; reduce query suite scope

For comprehensive troubleshooting with detailed solutions, search references/troubleshooting.md.

Hardware Requirements (Self-Hosted Runners)

Codebase SizeRAMCPU
Small (<100K LOC)8 GB+2 cores
Medium (100K–1M LOC)16 GB+4–8 cores
Large (>1M LOC)64 GB+8 cores

All sizes: SSD with ≥14 GB free disk space.

Action Versioning

Pin CodeQL actions to a specific major version:

yaml
uses: github/codeql-action/init@v4      # Recommended
uses: github/codeql-action/autobuild@v4
uses: github/codeql-action/analyze@v4

For maximum security, pin to a full commit SHA instead of a version tag.

Reference Files

For detailed documentation, load the following reference files as needed:

  • references/workflow-configuration.md — Full workflow trigger, runner, and configuration options
    • Search patterns: trigger, schedule, paths-ignore, db-location, model packs, alert severity, merge protection, concurrency, config file
  • references/cli-commands.md — Complete CodeQL CLI command reference
    • Search patterns: database create, database analyze, upload-results, resolve packs, cli-server, installation, CI integration
  • references/sarif-output.md — SARIF v2.1.0 object model, upload limits, and third-party support
    • Search patterns: sarifLog, result, location, region, codeFlow, fingerprint, suppression, upload limits, third-party, precision, security-severity
  • references/compiled-languages.md — Build modes and autobuild behavior per language
    • Search patterns: C/C++, C#, Java, Go, Rust, Swift, autobuild, build-mode, hardware, dependency caching
  • references/troubleshooting.md — Comprehensive error diagnosis and resolution
    • Search patterns: no source code, out of disk, out of memory, 403, C# compiler, analysis too long, fewer lines, Kotlin, extraction errors, debug logging, SARIF upload, SARIF limits
  • references/alert-management.md — Alert severity, triage, Copilot Autofix, and dismissal
    • Search patterns: severity, security severity, CVSS, Copilot Autofix, dismiss, triage, PR alerts, data flow, merge protection, REST API

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Codeql AI skill do?

Comprehensive guide for setting up and configuring CodeQL code scanning via GitHub Actions workflows and the CodeQL CLI. This skill should be used when users need help with code scanning configuration, CodeQL workflow files, CodeQL CLI commands, SARIF output, security analysis setup, or troubleshooting CodeQL analysis.

Why use Codeql on TypingMind?

Because you install it once and use it with any model. Codeql is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Codeql in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/github/awesome-copilot/tree/main/skills/codeql. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Codeql?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Codeql?

As many as you like. As long as a model supports skills, you can use Codeql with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Codeql AI skill free?

Yes. It is published on GitHub by github under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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