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 skills add blockmatic/basilic --skill f-ai-expertgit clone --depth 1 https://github.com/blockmatic/basilicWrote 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/blockmatic/basilic/f-ai-expert)<a href="https://agentmods.dev/skills/blockmatic/basilic/f-ai-expert"><img src="https://agentmods.dev/badge/skills/blockmatic/basilic/f-ai-expert/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/blockmatic/basilic/f-ai-expert"><img src="https://agentmods.dev/badge/skills/blockmatic/basilic/f-ai-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00034 | $0.00223 |
| Opus 5 | $0.00017 | $0.00112 |
| Sonnet 5 | $0.00007 | $0.00045 |
| Haiku 4.5 | $0.00003 | $0.00022 |
Grade A, and why
f-ai-expert 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.
What it actually says
Role only. Not an eleventh station.
- Read ../references/analyst.md.
- Read
_first/FIRST.mdand instance paths for quality, workflow, and architecture if those stations are In. - Load sibling specs only for boundaries the change crosses: ../f-quality/references/spec.md, ../f-workflow/references/spec.md, ../f-architecture/references/spec.md.
- Inspect evals, agent actors, tool loops, and assistant UX in the repo. Compare to Quality, Workflow, and Architecture facts.
- Propose the smallest change. Do not add a FIRST station. Do not invent an eval dataset or a second agent stack.
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 Changed b2190b29b133
- 3d ago First seen · 14 lines · 34 tokens per session scan A b4d1c32de720
f-ai-expert is a skill published in the GitHub repository blockmatic/basilic (89 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 223 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 2026-09-05.
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