Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add adriannoes/awesome-agentic-ai --skill performing-sca-dependency-scanning-with-snykgit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/performing-sca-dependency-scanning-with-snyk)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/performing-sca-dependency-scanning-with-snyk"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/performing-sca-dependency-scanning-with-snyk/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/performing-sca-dependency-scanning-with-snyk"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/performing-sca-dependency-scanning-with-snyk.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 117 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00077 | $0.02264 |
| Opus 5 | $0.00039 | $0.01132 |
| Sonnet 5 | $0.00015 | $0.00453 |
| Haiku 4.5 | $0.00008 | $0.00226 |
Grade A, and why
performing-sca-dependency-scanning-with-snyk scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performing SCA Dependency Scanning with Snyk
When to Use
- When applications use open-source packages that may contain known vulnerabilities
- When compliance requires tracking and remediating vulnerable dependencies (PCI DSS, SOC 2)
- When needing automated fix PRs for vulnerable dependencies in CI/CD
- When license compliance requires visibility into open-source license obligations
- When continuous monitoring is needed for newly disclosed vulnerabilities in deployed dependencies
Do not use for scanning proprietary application code for logic vulnerabilities (use SAST), for runtime vulnerability detection (use DAST), or for container OS package scanning alone (use Trivy for a free alternative).
Prerequisites
- Snyk account (free tier covers up to 200 tests per month for open source)
- Snyk CLI installed or Snyk GitHub/GitLab integration configured
- SNYK_TOKEN environment variable set with API authentication token
- Project with supported package manifests: package.json, requirements.txt, pom.xml, go.mod, Gemfile, etc.
Workflow
Step 1: Install and Authenticate Snyk CLI
# Install Snyk CLI
npm install -g snyk
# Authenticate with Snyk
snyk auth $SNYK_TOKEN
# Test the connection
snyk test --json | jq '.summary'
Step 2: Scan Dependencies in CI/CD Pipeline
# .github/workflows/dependency-scan.yml
name: Dependency Security Scan
on:
push:
branches: [main]
pull_request:
branches: [main]
schedule:
- cron: '0 8 * * 1' # Weekly Monday 8am
jobs:
snyk-scan:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: '20'
- name: Install dependencies
run: npm ci
- name: Run Snyk to check for vulnerabilities
uses: snyk/actions/node@master
env:
SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }}
with:
args: >
--severity-threshold=high
--fail-on=upgradable
--json-file-output=snyk-results.json
- name: Upload results to Snyk
if: always()
uses: snyk/actions/node@master
env:
SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }}
with:
command: monitor
args: --project-name=${{ github.repository }}
- name: Upload SARIF
if: always()
run: |
npx snyk-to-html -i snyk-results.json -o snyk-report.html
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 267 lines · 77 tokens per session scan A dfd1a2b52caf
performing-sca-dependency-scanning-with-snyk is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 77 tokens to every session and 2,264 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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