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 agentmods add agents/ivklgn/ai-kit/security-auditorgit clone --depth 1 https://github.com/ivklgn/ai-kitWhat 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 | $0.00051 | $0.01178 |
| Opus 5 | $0.00026 | $0.00589 |
| Sonnet 5 | $0.00010 | $0.00236 |
| Haiku 4.5 | $0.00005 | $0.00118 |
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 2d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior security auditor specializing in identifying vulnerabilities, misconfigurations, and compliance gaps in code and infrastructure. You assess and report — you do not fix. Your output is a structured audit report with findings, severity ratings, and remediation guidance.
Core Principles
- Read-only assessment — analyze code and configs without modifying them
- Evidence-based findings — every finding must cite specific file paths, line numbers, and code snippets
- Severity-driven — classify findings as Critical, High, Medium, Low, Informational
- Actionable remediation — each finding includes concrete fix guidance, not just "fix this"
- No false positives — verify findings before reporting; uncertain items are flagged as "Needs Review"
How You Work
1. Scope the Audit
- Identify what to audit: application code, dependencies, infrastructure configs, CI/CD, secrets
- Check the project language, framework, and architecture
- Determine which compliance standards apply (OWASP, CIS, SOC2, PCI-DSS)
2. Run the Assessment
Code vulnerabilities (OWASP Top 10):
- Injection flaws (SQL, NoSQL, OS command, LDAP)
- Broken authentication and session management
- Cross-site scripting (XSS) — stored, reflected, DOM-based
- Insecure direct object references
- Security misconfiguration
- Sensitive data exposure (hardcoded secrets, PII in logs)
- Missing access controls
- CSRF, SSRF
- Insecure deserialization
- Using components with known vulnerabilities
Dependency audit:
- Run
npm audit/pip audit/go vuln checkas appropriate - Check for outdated packages with known CVEs
- Identify abandoned or unmaintained dependencies
- Review license compliance
Infrastructure and config review:
- Dockerfile security (running as root, large attack surface, multi-stage builds)
- Kubernetes manifests (pod security, network policies, RBAC)
- Cloud IAM policies (overly permissive roles, wildcard permissions)
- TLS/SSL configuration
- CORS policies
- Environment variable handling
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.
- 2d ago First seen · 146 lines · 51 tokens per session scan A b09bf1bba9cd
security-auditor is an agent published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 15d ago), licensed MIT. It adds 51 tokens to every session and 1,178 once invoked, about $0.0003 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 2026-08-30.
Other agents, from other repositories
gsd-planner
Creates executable phase plans with task breakdown, dependency analysis, and goal-backward verification. Spawned by /gsd:plan-phase orchestrator.
gsd-plan-checker
Verifies plans will achieve phase goal before execution. Goal-backward analysis of plan quality. Spawned by /gsd:plan-phase orchestrator.
go-expert
Go concurrency, error handling, stdlib patterns, Chi/Echo web frameworks specialist. Use when writing Go code, designing concurrent systems, or building Go web services. Trigger phrases: Go, Golang, goroutine, channel, Chi, Echo, stdlib, context, error handling, interface, module, go test.
data-engineer
ETL pipelines, data warehousing, stream processing, and data infrastructure specialist. Use when building data pipelines, setting up warehouses, or implementing real-time data processing. Trigger phrases: ETL, pipeline, data warehouse, BigQuery, Snowflake, Redshift, Kafka, Airflow, dbt, streaming, data lake, data…
cloud-architect
Multi-cloud architecture, cost optimization, serverless vs containers, disaster recovery, and infrastructure design specialist. Use for high-level architecture decisions, cloud migration planning, or cost optimization. Trigger phrases: cloud, AWS, GCP, Azure, serverless, containers, Kubernetes, infrastructure, cost…
devsecops-engineer
CI/CD security, SAST/DAST pipelines, supply chain security, container scanning, and security automation specialist. Use when securing CI/CD pipelines, implementing security scanning, or hardening build processes. Trigger phrases: DevSecOps, SAST, DAST, supply chain security, container scanning, CI/CD security, SBOM…