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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Use GitHub Actions to run repeatable static-analysis checks on changes and on a schedule, then keep the results available in GitHub code scanning. CodeQL is GitHub’s built-in analysis engine, but GitHub can also display compatible third-party results uploaded in SARIF format. Keep scans, permissions, and pass-or-fail policy in reviewed CI configuration; use agent skills only to guide bounded tasks such as explaining findings or checking a workflow.
Choose default or advanced CodeQL setup
GitHub offers two ways to configure CodeQL. Default setup is the lower-maintenance choice: GitHub selects supported languages, a query suite, and scan events based on the repository. Advanced setup adds or edits a workflow file, giving maintainers control over languages, build steps, events, matrices, and query configuration. See GitHub’s setup type overview and CodeQL code-scanning guide.
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| Choice | Maintenance | Control | Eligibility |
|---|---|---|---|
| Default setup | Less workflow configuration to maintain; GitHub manages the setup. | Less direct control over build behavior, event details, and query customization. | Availability depends on repository ownership and plan. GitHub’s current documentation lists public repositories and qualifying organization-owned repositories with GitHub Code Security enabled. |
| Advanced setup | Team maintains the workflow and its configuration. | More control over languages, builds, event triggers, query suites, packs, and matrices. | Check current GitHub Code Security access rules for the repository before selecting this approach. |
Choose default setup when its automatic language and event choices meet your needs. Choose advanced setup when you need explicit build commands, branch or schedule behavior, a language matrix, or custom query configuration. Product access rules can change, so verify eligibility in GitHub’s current documentation rather than assuming a repository qualifies.
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For advanced setup, keep the workflow in .github/workflows/, where it can be reviewed alongside application changes. The example below runs on pushes, pull requests, and a weekly schedule. It uses JavaScript/TypeScript and Python as example languages; replace them with languages actually present in the repository and supported by CodeQL. The CodeQL action versions shown are major-version references, not immutable pins; teams with stricter supply-chain controls can pin reviewed action references to commit SHAs.
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name: CodeQL
on:
push:
pull_request:
schedule:
- cron: '17 3 * * 1'
workflow_dispatch:
permissions:
contents: read
security-events: write
pull-requests: read
jobs:
analyze:
name: Analyze (${{ matrix.language }})
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
language: [ 'javascript-typescript', 'python' ]
steps:
- name: Check out repository
uses: actions/checkout@v4
- name: Initialize CodeQL
uses: github/codeql-action/init@v3
with:
languages: ${{ matrix.language }}
- name: Perform CodeQL analysis
uses: github/codeql-action/analyze@v3This is a starting point, not a universal build recipe. Set push and pull-request branch filters to match the branches the team protects; an unfiltered trigger scans on all applicable branches. A scheduled workflow runs only when its workflow file exists on the default branch. The example schedule is weekly, at 03:17 UTC on Mondays. GitHub’s workflow configuration reference explains supported triggers and options.
Use pull requests and pushes for timely feedback
Pull-request scans give reviewers and contributors findings while a change is under review. Push scans cover changes that reach the configured branches, including changes made outside the pull-request path. Configure both to reflect how the repository actually merges and protects code; a trigger that watches the wrong branches can leave gaps or produce redundant runs.
Add a schedule for later-discovered issues
A scheduled scan can surface findings after a query or vulnerability-related knowledge change, even if the analyzed code has not changed. GitHub’s default CodeQL analysis workflow scans weekly in addition to scans triggered by configured events. If using advanced setup, add a schedule deliberately and ensure the workflow is present on the default branch.
Verify language and build coverage
A successful workflow run does not, by itself, prove that the intended source was analyzed. For compiled languages, CodeQL creates a database using a language-appropriate build mode. The documented modes are none, autobuild, and manual; which modes apply varies by language. In manual mode, maintainers provide build commands. Consult GitHub’s compiled-language guidance for the language and build system in use.
- Confirm that every relevant language is included in the workflow or selected by default setup.
- For compiled code, verify the database-generation mode and whether the build succeeds in a representative CI run.
- Check the run output and analyzed source to make sure generated, excluded, or otherwise unexpected files have not displaced the code the team intends to cover.
- When changing build steps, test the workflow on a representative branch or pull request before relying on its results as a gate.
Choose query coverage without mistaking volume for value
CodeQL provides a default query suite and an expanded security-extended suite. Advanced setup can also add query packs, query files, suites, and filters. Broader query selection may increase coverage, but it can also increase runtime and alert noise; a larger suite is not automatically a better fit for every team. Compare the findings it produces against the project’s risk priorities and the capacity to triage them.
For custom packs, choose and review a version strategy. GitHub notes that a pack without a specified version resolves to the latest version, which means its contents may change over time. See the CodeQL Actions query documentation for built-in queries and suite information. CodeQL can analyze GitHub Actions workflow files too, so include pipeline configuration in the security review rather than treating CI as outside the application’s attack surface.
Decide whether to add a third-party SARIF scanner
GitHub code scanning is not limited to CodeQL. A compatible third-party static-analysis tool can upload results in SARIF format, allowing teams to use GitHub code scanning to view those results. SARIF compatibility is an interchange mechanism, not evidence that two scanners have the same language coverage, rules, alert behavior, maintenance needs, or licensing. GitHub describes code-scanning options in its code-scanning overview.
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| Decision factor | Questions to answer |
|---|---|
| Language and framework coverage | Does the scanner cover the languages, frameworks, and source patterns the repository uses? |
| Build and source coverage | Does it inspect the source and build configurations that matter, and can the team verify what was analyzed? |
| Rules | Does it provide rules the team needs that are not already covered by the existing setup? |
| GitHub integration | Can it produce SARIF in a form GitHub accepts, and does its result behavior meet the team’s workflow needs? |
| Operations and terms | What runtime, maintenance, licensing, and current commercial terms apply? Verify these with the tool provider. |
Add another scanner when it closes a specific coverage or workflow gap, not simply because it can upload SARIF. Avoid assuming equivalent coverage or alert handling from format compatibility alone.
Reuse security workflows across repositories
When several repositories need the same complete pipeline, a reusable workflow is the appropriate unit: callers can invoke a workflow containing multiple jobs and steps. A composite action instead packages a reusable sequence of steps within a job. GitHub explains the distinction in its workflow reuse documentation.
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- Keep shared workflow inputs and secrets explicit, minimal, and documented.
- Maintain the shared workflow centrally and review changes as security-sensitive code.
- For reusable workflows, GitHub recommends commit-SHA references when callers need a fixed revision. Tags and branches require trust in the version they reference.
- Check each caller’s permissions and triggers; centralizing workflow code does not automatically make every caller safe or appropriately configured.
Harden the workflow that runs the scan
Static analysis is part of a security pipeline, so the pipeline itself needs least-privilege access and careful handling of untrusted changes. GitHub’s secure-use reference warns that third-party actions can access configured secrets and may use repository tokens.
- Grant only the
GITHUB_TOKENpermissions a workflow or job needs, and scope them at the workflow or job level. - Review third-party actions and pin their references to trusted revisions when appropriate for the team’s supply-chain policy.
- Avoid
pull_request_targetwhen privileged context is unnecessary. Do not combine a privileged trigger with checking out or executing untrusted pull-request content. - Keep untrusted values out of generated shell scripts. Treat artifacts produced through privileged workflow paths cautiously.
- Run CodeQL’s Actions queries against workflow files as well as application code, then review findings in context.
Use agent skills for bounded review, not as the scanner
An agent skill is reusable task guidance and supporting resources for an AI coding assistant; it does not itself run CodeQL or guarantee that an analysis result is correct. GitHub’s Copilot documentation describes a skill as a directory with a required SKILL.md and optional supporting Markdown, scripts, or other resources. Project skills can be stored in .github/skills, .claude/skills, or .agents/skills. See GitHub’s agent skills guidance for the documented locations and supported Copilot surfaces.
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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →A narrowly scoped skill can instruct an agent to explain a CodeQL alert using the supplied finding and relevant source context, identify evidence needed to triage it, check a workflow against the team’s CI security checklist, or draft documentation for a reviewed fix. Make the expected inputs, allowed actions, and limits clear. Review skill instructions and supporting files like code because they influence agent behavior.
Best Value
| Static-analysis CI | Skill-guided agent assistance |
|---|---|
| Runs explicit, configured scans and produces results through the workflow. | Applies reusable instructions to a task using the tools and context available to the agent. |
| Provides repeatable checks and reviewable policy gates in workflow configuration. | Can help interpret or document results, but its output needs validation and human review. |
| Permissions are set in the workflow and repository environment. | Must be bounded by the agent’s own available tools and permissions; a skill is not a permissions boundary. |
Keep the division clear: CI determines which scans run and what policy applies; a skill can help a person or agent work through a finding or review the configuration. Do not make an agent response a substitute for an explicit scan, least-privilege access, or a maintainer’s decision.
Keep Agentic Workflows distinct from skills
GitHub Agentic Workflows are a separate feature, not another name for a SKILL.md skill. GitHub documents Agentic Workflows as Markdown files in .github/workflows/ with YAML frontmatter and natural-language instructions; they are compiled to .lock.yml and run through Actions or the GitHub CLI. The cited GitHub documentation identifies the feature as public preview and subject to change, so verify its current status and safeguards before adoption. Its configuration covers triggers, permissions, safe outputs, and engine selection. See Creating GitHub Agentic Workflows.
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