Borrowing it
Nothing to install: this file belongs to Fuenfgeld/pydantic-ai-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Fuenfgeld/pydantic-ai-skills/main/CLAUDE.mdgit clone --depth 1 https://github.com/Fuenfgeld/pydantic-ai-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/instructions/fuenfgeld/pydantic-ai-skills/claude-md)<a href="https://agentmods.dev/instructions/fuenfgeld/pydantic-ai-skills/claude-md"><img src="https://agentmods.dev/badge/instructions/fuenfgeld/pydantic-ai-skills/claude-md/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/instructions/fuenfgeld/pydantic-ai-skills/claude-md"><img src="https://agentmods.dev/badge/instructions/fuenfgeld/pydantic-ai-skills/claude-md.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 | $0.00856 | $0.00856 |
| Opus 5.5 | $0.00342 | $0.00342 |
| Sonnet 5.5 | $0.00171 | $0.00171 |
| Haiku 4.5 | $0.00086 | $0.00086 |
Grade A, and why
pydantic-ai-skills CLAUDE.md 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 1mo 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Core Principles
- TDD (Test-Driven Development): Write tests before implementation
- KISS (Keep It Simple, Stupid): Start simple, add complexity incrementally
- SOLID Principles: Maintain clean, maintainable architecture
- Evaluation-Driven Development: Treat evaluations as first-class code
Development Workflow
Plan → Document → Test → Implement → Evaluate → Refine
Phase 1: Plan
- Review requirements for the feature/agent
- Design high-level architecture
- Identify evaluation strategies
- Create implementation plan document in
.claude/plan/folder in the project folder - Plan must be updated regularly throughout implementation
Phase 2: Document
- Write detailed specifications
- Define input/output contracts
- Document expected behavior
- Create architecture decision records
Phase 3: Test (Write First!)
- Create Pydantic Evals dataset with test cases
- Implement custom evaluators if needed
- Write traditional unit tests for utilities
- Define success criteria
Phase 4: Implement
- Build Pydantic models
- Implement agent with proper patterns
- Add Logfire instrumentation
- Follow SOLID principles
Phase 5: Evaluate
- Run evaluation suite
- Analyze Logfire traces
- Identify failures and edge cases
- Iterate until tests pass
Phase 6: Refine
- Document learnings
- Update SKILL_IMPROVEMENTS.md
- Refactor for clarity
- Update documentation
Progress Plans
CRITICAL: All implementations MUST have a progress plan that is actively maintained.
Plan Requirements
- Location: All plans must be stored in project directory
.claude/plan/directory - Format: Markdown files named descriptively (e.g.,
user-auth-agent.md,data-pipeline-refactor.md) - Updates: Plans must be updated regularly as implementation progresses
- Content: Include:
- Current status and phase
- Completed tasks (with checkmarks)
- In-progress tasks
- Blockers or challenges
- Next steps
- Decision records
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.
- 1mo ago First seen · 146 lines · 856 tokens per session scan A ebeca397e49b
pydantic-ai-skills CLAUDE.md is an instructions file published in the GitHub repository Fuenfgeld/pydantic-ai-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 856 tokens to every session, about $0.0034 per session on Opus 5.5. 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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