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 racecraft-lab/racecraft-plugins-public --skill typesafe-aigit clone --depth 1 https://github.com/racecraft-lab/racecraft-plugins-publicWrote 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/racecraft-lab/racecraft-plugins-public/typesafe-ai)<a href="https://agentmods.dev/skills/racecraft-lab/racecraft-plugins-public/typesafe-ai"><img src="https://agentmods.dev/badge/skills/racecraft-lab/racecraft-plugins-public/typesafe-ai/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/racecraft-lab/racecraft-plugins-public/typesafe-ai"><img src="https://agentmods.dev/badge/skills/racecraft-lab/racecraft-plugins-public/typesafe-ai.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 | $0.00149 | $0.02989 |
| Opus 5.5 | $0.00060 | $0.01196 |
| Sonnet 5.5 | $0.00030 | $0.00598 |
| Haiku 4.5 | $0.00015 | $0.00299 |
Grade A, and why
typesafe-ai 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 21d 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.
This is a copy
89% identical to typesafe-ai — 77 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build with TypeSafe
TypeSafe makes units of AI intelligence usable like programming primitives: small judgments you can compose into larger capabilities. Its System One models return fast, focused judgments that software can consume directly. Jev is TypeSafe's flagship and first System One model. It understands natural language and returns typed answers and probabilities rather than generating text or reasoning explanations. Code owns the workflow; the model supplies programmable common sense where ordinary code needs semantic understanding.
Make the judgment now, or build an integration
Installed as a plugin, this ships an MCP server exposing one tool,
evaluate, that sends state and typed questions to Jev and returns the
provider's answers. Installed on its own through skills add, it does not:
that path carries skill files and no MCP server. Check that an evaluate
tool is actually available before relying on one.
Decide which of the two jobs you are doing:
- A judgment is needed in this session — classify this ticket, rank these
candidates, check whether this claim holds, decide which branch to take.
Call
evaluatewhen it is there. Do not write a script, add an SDK, or make the judgment yourself from the prose. One call can carry many independent questions. When no such tool exists, say so once and make the judgment in the ordinary way; do not build an integration to stand in for a missing one. Thetypesafe-jevplugin inracecraft-lab/racecraft-plugins-publicis what provides it. - An application needs to call TypeSafe in production — then the rest of
this skill applies. Read the API or SDK page and write the integration. The
evaluatetool is for this session, not a runtime dependency of the user's software.
What ships with it
1 file 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.
- 21d ago First seen · 227 lines · 149 tokens per session scan A 6e30ac3aa226
typesafe-ai is a skill published in the GitHub repository racecraft-lab/racecraft-plugins-public (5 stars, last pushed yesterday), licensed MIT. It adds 149 tokens to every session and 2,989 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to typesafe-ai, differing in 77 lines, and is treated as a copy.
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