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 skills/benkapner/claude-code-basecamp/security-checknpx skills add Benkapner/claude-code-basecamp --skill security-checkgit clone --depth 1 https://github.com/Benkapner/claude-code-basecampWhat 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 | $0.00058 | $0.00247 |
| Opus 5 | $0.00029 | $0.00123 |
| Sonnet 5 | $0.00012 | $0.00049 |
| Haiku 4.5 | $0.00006 | $0.00025 |
Grade A, and why
security-check 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 3d 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.
What it actually says
Security Check Skill
Scan for credential leaks, insecure code patterns, and LLM security issues in Python data science projects.
When to Activate
- Before committing changes
- After modifying
.env,.gitignore, or config files - When adding new API integrations or credentials
- When reviewing code that handles tokens, keys, or passwords
- When code sends data to external LLM APIs (Gemini, OpenAI, etc.)
- Periodic security hygiene checks
Check Process
Read skills/scan-process.md for the full 6-step scan process with bash commands.
Pattern Reference
Read skills/pattern-tables.md for API key regex patterns, insecure Python code patterns, and LLM-specific security patterns with severity classifications.
Behavioral Rules
Read guidelines.md for severity classifications, remediation requirements, and escalation rules.
What ships with it
3 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.
- 3d ago First seen · 31 lines · 58 tokens per session scan A 8dffc8debb8e
security-check is a skill published in the GitHub repository Benkapner/claude-code-basecamp (16 stars, last pushed 13d ago), licensed MIT. It adds 58 tokens to every session and 247 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.
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