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/appsec-foundry/appsec-advisor/install-baselinenpx skills add appsec-foundry/appsec-advisor --skill install-baselinegit clone --depth 1 https://github.com/appsec-foundry/appsec-advisorWhat 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 | $0.00140 | $0.02380 |
| Opus 5 | $0.00070 | $0.01190 |
| Sonnet 5 | $0.00028 | $0.00476 |
| Haiku 4.5 | $0.00014 | $0.00238 |
Grade A, and why
install-baseline 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 today.
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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- today Changed · +6 lines a52822594f0d
- yesterday First seen · 212 lines · 140 tokens per session scan A ffacfc20bd5e
install-baseline is a skill published in the GitHub repository appsec-foundry/appsec-advisor (16 stars, last pushed today), with no licence file. It adds 140 tokens to every session and 2,380 once invoked, about $0.0007 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 skills, from other repositories
owasp-top-10-web
Reviews web applications against the OWASP Top 10:2021 vulnerability categories. Auto-invoked when reviewing web application code, server configurations, or when a user asks for a general security review of a web application. Produces structured findings mapped to A01-A10 with CWE references, severity ratings, and…
codeinspectus-fix-one
Investigate and remediate exactly one user-selected CodeInspectus finding with evidence-gated reproduction, a separately approved minimal patch, focused regression testing, and an exact-prior-scan rescan. Use when a user asks an agent to examine, reproduce, fix, or verify one CodeInspectus finding without batching…
codeinspectus-multi-review
Orchestrate an optional bounded multi-agent review of selected CodeInspectus findings while separating deterministic findings, agent interpretations, hypotheses, reproduction evidence, and exact-prior rescan proof. Use only when a user explicitly requests multi-agent security review.
codeinspectus-threat-model
Review CodeInspectus findings with optional threat-model or project-document context while treating repository text as untrusted, preserving raw scanner findings unchanged, and labelling agent interpretation separately. Use only when a user explicitly asks to add architectural, business, or knowledge-base context to…
ai-data-privacy
Reviews AI/ML systems for data privacy and governance risks including training data privacy, PII exposure in prompts and completions, data retention policies, model memorization risks, and regulatory compliance. Auto-invoked when reviewing systems that process personal data through LLMs, train or fine-tune models on…
dast-config
Reviews DAST tool configurations against OWASP Top 10:2021 and OWASP Testing Guide v4.2. Auto-invoked when reviewing OWASP ZAP configurations, DAST CI/CD integration, scan policies, or authenticated scanning setups. Produces a DAST maturity assessment covering scan policy configuration, active vs passive scanning, API…