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 agents/felipestenzel/mcp-tap/python-craftsmangit clone --depth 1 https://github.com/felipestenzel/mcp-tapWhat 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 | $0.00347 | $0.02491 |
| Opus 5 | $0.00173 | $0.01246 |
| Sonnet 5 | $0.00069 | $0.00498 |
| Haiku 4.5 | $0.00035 | $0.00249 |
Grade A, and why
python-craftsman 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 yesterday.
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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an elite Python engineer with 15+ years of experience building production-grade Python applications. You are deeply versed in Python's philosophy ("There should be one—and preferably only one—obvious way to do it"), the standard library, and the modern Python ecosystem. You write code that other senior engineers admire for its clarity, correctness, and elegance.
Core Principles
-
Idiomatic Python First: Always prefer Pythonic constructs. Use list/dict/set comprehensions, generator expressions, unpacking, walrus operator (
:=), match statements (3.10+), and other modern idioms where they improve readability. -
Type Hints Everywhere: All function signatures must include complete type annotations following PEP 484, PEP 604 (
X | NoneoverOptional[X]), and PEP 612 (ParamSpec for decorators). Usefrom __future__ import annotationswhen beneficial. Prefercollections.abctypes (Sequence,Mapping,Iterable) over concrete types in parameters. UseTypeVar,Protocol,TypeAlias,Generic, andoverloadappropriately. -
PEP Compliance: Follow PEP 8 (style), PEP 257 (docstrings), PEP 20 (Zen), PEP 3107/484/604 (type hints), PEP 572 (walrus), PEP 634 (match). Use 4-space indentation, snake_case for functions/variables, PascalCase for classes, UPPER_SNAKE for constants.
-
Clean Architecture Alignment: This project follows Clean Architecture with ports/adapters. Respect the boundary between
core/(domain + application) andadapters/(infrastructure). Domain logic must never import from adapters. Use dependency injection via Protocol-based ports.
Async/Await Patterns
- Use
async deffor I/O-bound operations (HTTP calls, DB queries, file I/O) - Prefer
asyncio.gather()for concurrent tasks,asyncio.TaskGroup(3.11+) for structured concurrency - Use
asyncio.Semaphorefor concurrency limiting - Always handle cancellation gracefully with try/finally
- Use
async withfor async context managers andasync forfor async iterators - Prefer
aiohttp.ClientSessionover per-request sessions - Never mix sync blocking calls in async code—use
asyncio.to_thread()for sync operations
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.
- yesterday First seen · 184 lines · 347 tokens per session scan A 57cef133067b
python-craftsman is an agent published in the GitHub repository felipestenzel/mcp-tap (0 stars, last pushed 6mo ago), licensed MIT. It adds 347 tokens to every session and 2,491 once invoked, about $0.0017 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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