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 robhowley/py-pit-skills --skill pydantic-schemasgit clone --depth 1 https://github.com/robhowley/py-pit-skillsWrote 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/robhowley/py-pit-skills/pydantic-schemas)<a href="https://agentmods.dev/skills/robhowley/py-pit-skills/pydantic-schemas"><img src="https://agentmods.dev/badge/skills/robhowley/py-pit-skills/pydantic-schemas/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/robhowley/py-pit-skills/pydantic-schemas"><img src="https://agentmods.dev/badge/skills/robhowley/py-pit-skills/pydantic-schemas.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 | $0.00044 | $0.02816 |
| Opus 5 | $0.00022 | $0.01408 |
| Sonnet 5 | $0.00009 | $0.00563 |
| Haiku 4.5 | $0.00004 | $0.00282 |
Grade A, and why
pydantic-schemas 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 12d 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 — 500 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pydantic-schemas
Opinionated guidance for designing API request/response schemas using Pydantic v2 in new Python backend projects.
This skill is optimized for 0→1 API projects where schema
conventions have not yet been established.
Its purpose is to prevent schema drift, eliminate repeated
architectural decisions, and enforce a consistent API boundary between
domain models and external representations.
This skill does not teach Pydantic basics.
It constrains schema architecture so the model consistently generates
predictable request, response, query, and command structures.
Apply this Skill When
Apply this skill when the user:
- asks how to structure API schemas
- asks for request or response models
- asks about Pydantic models in a FastAPI or API backend
- is creating a new resource schema
- is designing pagination or response envelopes
- is implementing create/update/read models
- is designing command endpoints, search/filter endpoints, batch endpoints, or aggregate/reporting responses
Trigger phrases (user language):
"add a schema for orders", "how should I structure my Pydantic models?", "I need a request body for creating a user", "what's the right way to do partial updates?", "how do I return paginated results?", "should I use the same model for create and update?", "how do I model a cancel order action?", "I need a search endpoint with filters"
Do not apply this skill when:
- working with internal-only DTOs that never cross an API boundary
- using Pydantic for local parsing scripts
- the repository already uses a different schema architecture and the user did not request a refactor
- working on non-API validation tasks
Mission
When this skill is active, the model's job is to produce or extend schema code that follows this taxonomy without deviation, ask no unnecessary questions, and leave the caller with working, importable schema classes.
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.
- 12d ago First seen · 500 lines · 44 tokens per session scan A 2b12d4e0ebc4
pydantic-schemas is a skill published in the GitHub repository robhowley/py-pit-skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 2,816 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 2026-08-31.
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