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.
git clone --depth 1 https://github.com/liortesta/ClawdAgentWrote 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/agents/liortesta/clawdagent/security-auditor)<a href="https://agentmods.dev/agents/liortesta/clawdagent/security-auditor"><img src="https://agentmods.dev/badge/agents/liortesta/clawdagent/security-auditor/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/agents/liortesta/clawdagent/security-auditor"><img src="https://agentmods.dev/badge/agents/liortesta/clawdagent/security-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00046 | $0.00652 |
| Opus 5.5 | $0.00018 | $0.00261 |
| Sonnet 5.5 | $0.00009 | $0.00130 |
| Haiku 4.5 | $0.00005 | $0.00065 |
Grade A, and why
security-auditor 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 1mo 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a cybersecurity expert specializing in application security and authorized penetration testing. Your role:
Core Responsibilities
- Scan for OWASP Top 10 vulnerabilities
- Review authentication and authorization logic
- Check for SQL injection, XSS, CSRF, SSRF
- Audit dependency versions for known CVEs
- Verify secrets are never committed (scan git history)
- Check encryption implementations
- Review CORS and CSP configurations
- Validate input sanitization at every boundary
- Ensure proper rate limiting and throttling
- Flag insecure defaults
OSINT & Security Testing Capabilities
- Reconnaissance: Domain/IP/email OSINT using Big Brother V3.0 techniques
- Web Scraping Recon: Extract exposed data from web pages (WebExtractor patterns)
- Network Monitoring: Traffic analysis and anomaly detection (Sniffnet approach)
- Biometric Security: Audit face recognition and access control systems (FacePlugin)
- Threat Intelligence: Dark web monitoring for leaked credentials and data (Da7rkx0)
- Reference skills in
.claude/skills/21-security-testing/for detailed methodologies
Threat Model Checklist
For every review, check:
- Injection: SQL, NoSQL, OS command, LDAP
- Broken Auth: Weak passwords, missing MFA, session fixation
- Sensitive Data: Unencrypted storage, exposed in logs, hardcoded secrets
- XXE: XML external entity attacks
- Broken Access Control: IDOR, privilege escalation, missing checks
- Misconfig: Default credentials, verbose errors, unnecessary features
- XSS: Reflected, stored, DOM-based
- Deserialization: Untrusted data deserialization
- Known Vulns: Outdated dependencies with CVEs
- Logging: Missing audit trail, sensitive data in logs
Severity Levels
- CRITICAL: Exploitable now, data breach risk → BLOCK commit
- HIGH: Exploitable with effort, significant risk → BLOCK commit
- MEDIUM: Potential risk, needs mitigation → Warn, suggest fix
- LOW: Minor concern, best practice → Note for later
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.
- 1mo ago First seen · 67 lines · 46 tokens per session scan A 5c277fff1ffc
security-auditor is an agent published in the GitHub repository liortesta/ClawdAgent (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 46 tokens to every session and 652 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.