Audit dependency files across eight language ecosystems for built-in vulnerability patterns, license conflicts, and indirect dependency risks. Generate a prioritized upgrade plan with testing and rollback notes, and pair results with live audit tools for current vulnerability coverage.
中文简介正在准备中。当前显示英语简介。
Audit and manage dependencies across multi-language projects. Identifies vulnerabilities, license conflicts, transitive dependency risks, and safe-upgrade paths. Use when auditing third-party packages before release, investigating a CVE, planning a major version bump, or running a license-compliance review. Examples: 'audit our npm dependencies', 'do we have GPL contamination', 'plan the upgrade to React 19'.
安装前可以查看交给 AI 代理的指令内容。
Skill Type: POWERFUL · Category: Engineering · Domain: Dependency Management & Security
Offline, deterministic dependency auditing across 8+ package ecosystems. The three scripts are pattern-matchers over manifests/lockfiles — they do not call live advisory APIs; pair their findings with npm audit / pip-audit / cargo audit for current CVE coverage.
# 1. Scan for vulnerabilities (built-in offline CVE pattern set; exit non-zero on high severity)
python3 scripts/dep_scanner.py /path/to/project --format json --fail-on-high -o scan.json
# 2. Check license compliance and conflicts
python3 scripts/license_checker.py /path/to/project --policy strict --format json -o licenses.json
# 3. Plan upgrades from the scanner's inventory
python3 scripts/upgrade_planner.py scan.json --risk-threshold medium --timeline 90 --format json -o plan.json
Consume the outputs: scan.json findings drive which packages to pin/patch now; licenses.json conflicts go to the user as a legal-risk list; plan.json orders upgrades by risk with rollback notes. --quick-scan skips transitive deps; --security-only limits the plan to security fixes.
Verification loop: after applying upgrades, re-run step 1 and assert 0 high-severity findings before closing the audit.
| Language | Manifests parsed |
|---|---|
| JavaScript/Node | package.json, package-lock.json, yarn.lock |
| Python | requirements.txt, pyproject.toml, Pipfile.lock, poetry.lock |
| Go | go.mod, go.sum |
| Rust | Cargo.toml, Cargo.lock |
| Ruby | Gemfile, Gemfile.lock |
| Java | pom.xml, gradle.lockfile |
| PHP | composer.json, composer.lock |
| C#/.NET | packages.config, project.assets.json |
The checker analyzes license inheritance through dependency chains and emits conflict pairs with remediation suggestions.
| Risk | Update type | Handling |
|---|---|---|
| Low | Patch, security fixes | Apply immediately |
| Medium | Minor with new features | Batch into scheduled update |
| High | Major version, API changes | Dedicated migration task + tests |
| Critical | Known breaking changes | Planned migration with rollback procedure |
Prioritization: security patches > bug fixes > feature updates > major rewrites; deprecated features get immediate attention.
scripts/dep_scanner.py — multi-format parser; built-in offline vulnerability pattern set (~16 CVE patterns — a smoke layer, not a replacement for live advisories); transitive resolution from lockfiles; JSON + text output.scripts/license_checker.py — license detection from package metadata; compatibility matrix across 20+ license types; --policy permissive|strict; conflict detection with remediation.scripts/upgrade_planner.py — semver-based breaking-change prediction; risk-ordered migration plan with testing checklist and timeline estimation.Sample fixtures: test-project/ and test-inventory.json in this folder; expected shapes in expected_outputs/.
# Security gate in CI
python3 scripts/dep_scanner.py . --format json --fail-on-high
python3 scripts/license_checker.py . --policy strict --format json
See README.md for detailed usage and references/ for the vulnerability/license knowledge bases.
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Audit web applications for accessibility issues against WCAG 2.2 Level A and AA, the web accessibility standards. Get framework-specific code fixes, contrast checks, verification steps, and reports, with options for automated checks in development pipelines.
中文简介正在准备中。当前显示英语简介。
Plan A/B tests that compare page variations, from headlines to pricing layouts. Define a hypothesis, choose success metrics, calculate sample size and duration, and prepare launch checks and results reports to support decisions.
中文简介正在准备中。当前显示英语简介。
Create paid ad headlines and body copy tailored to each platform's character limits. Use existing performance data to develop variations, explore new messaging angles, and check copy for length, quality, and potential rejection risks.
中文简介正在准备中。当前显示英语简介。
Review code changes from three critical perspectives: production failures, maintainability, and security. Get a consolidated report that ranks findings by severity and provides merge guidance, helping examine assumptions that an ordinary self-review may overlook.
中文简介正在准备中。当前显示英语简介。
Audit and improve content intended for citation in AI answers. Review evidence, author information, and structure, generate revised content and structured metadata, and keep a local record of observed citations across AI services.
中文简介正在准备中。当前显示英语简介。
Create signed records for consequential agent actions such as deployments, deletions, and payments. Decide which actions need evidence, record the agent, action, target, and policy, then verify the resulting certificate offline to detect later changes.
中文简介正在准备中。当前显示英语简介。