Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/RudyCity/superagentnpx agentmods add skills/rudycity/superagent/sast-configurationWrote 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/rudycity/superagent/sast-configuration)<a href="https://agentmods.dev/skills/rudycity/superagent/sast-configuration"><img src="https://agentmods.dev/badge/skills/rudycity/superagent/sast-configuration/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/rudycity/superagent/sast-configuration"><img src="https://agentmods.dev/badge/skills/rudycity/superagent/sast-configuration.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 63 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
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 | $0.00043 | $0.01221 |
| Opus 5 | $0.00022 | $0.00611 |
| Sonnet 5 | $0.00009 | $0.00244 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
sast-configuration 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 7d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- sast-configuration — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SAST Configuration
Static Application Security Testing (SAST) tool setup, configuration, and custom rule creation for comprehensive security scanning across multiple programming languages.
Overview
This skill provides comprehensive guidance for setting up and configuring SAST tools including Semgrep, SonarQube, and CodeQL. Use this skill when you need to:
- Set up SAST scanning in CI/CD pipelines
- Create custom security rules for your codebase
- Configure quality gates and compliance policies
- Optimize scan performance and reduce false positives
- Integrate multiple SAST tools for defense-in-depth
Core Capabilities
1. Semgrep Configuration
- Custom rule creation with pattern matching
- Language-specific security rules (Python, JavaScript, Go, Java, etc.)
- CI/CD integration (GitHub Actions, GitLab CI, Jenkins)
- False positive tuning and rule optimization
- Organizational policy enforcement
2. SonarQube Setup
- Quality gate configuration
- Security hotspot analysis
- Code coverage and technical debt tracking
- Custom quality profiles for languages
- Enterprise integration with LDAP/SAML
3. CodeQL Analysis
- GitHub Advanced Security integration
- Custom query development
- Vulnerability variant analysis
- Security research workflows
- SARIF result processing
Quick Start
Initial Assessment
- Identify primary programming languages in your codebase
- Determine compliance requirements (PCI-DSS, SOC 2, etc.)
- Choose SAST tool based on language support and integration needs
- Review baseline scan to understand current security posture
Basic Setup
# Semgrep quick start
pip install semgrep
semgrep --config=auto --error
# SonarQube with Docker
docker run -d --name sonarqube -p 9000:9000 sonarqube:10.8-community
# CodeQL CLI setup
gh extension install github/gh-codeql
codeql database create mydb --language=python
Integration Patterns
CI/CD Pipeline Integration
# GitHub Actions example
- name: Run Semgrep
uses: returntocorp/semgrep-action@v1
with:
config: >-
p/security-audit
p/owasp-top-ten
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.
- 7d ago First seen · 193 lines · 43 tokens per session scan A cc31d39b62ed
sast-configuration is a skill published in the GitHub repository RudyCity/superagent (21 stars, last pushed 2d ago), licensed MIT. It adds 43 tokens to every session and 1,221 once invoked, about $0.0002 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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