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 skills/inho-team/qe-mcp/qpython-pronpx skills add inho-team/qe-mcp --skill qpython-progit clone --depth 1 https://github.com/inho-team/qe-mcpWhat 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 | $0.00084 | $0.01686 |
| Opus 5 | $0.00042 | $0.00843 |
| Sonnet 5 | $0.00017 | $0.00337 |
| Haiku 4.5 | $0.00008 | $0.00169 |
Grade A, and why
Qpython-pro scanned grade A with 1 finding 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- **subprocess shell=True** — Always pass arguments as list: `subprocess.run(["process", filename], check=True)` How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Pro
Modern Python 3.11+ specialist focused on type-safe, async-first, production-ready code.
When to Use This Skill
- Writing type-safe Python with complete type coverage
- Implementing async/await patterns for I/O operations
- Setting up pytest test suites with fixtures and mocking
- Creating Pythonic code with comprehensions, generators, context managers
- Building packages with Poetry and proper project structure
- Performance optimization and profiling
Core Workflow
- Analyze codebase — Review structure, dependencies, type coverage, test suite
- Design interfaces — Define protocols, dataclasses, type aliases
- Implement — Write Pythonic code with full type hints and error handling
- Test — Create comprehensive pytest suite with >90% coverage
- Validate — Run
mypy --strict,black,ruff- If mypy fails: fix type errors reported and re-run before proceeding
- If tests fail: debug assertions, update fixtures, and iterate until green
- If ruff/black reports issues: apply auto-fixes, then re-validate
Reference Guide
Load detailed guidance based on context:
| Topic | Reference | Load When |
|---|---|---|
| Code Patterns | references/code-patterns.md |
Functions, error handling, dataclasses, async patterns |
| Anti-patterns | references/anti-patterns.md |
Mutable defaults, bare except, globals, string loops, file handling |
| Type System | references/type-system.md |
Type hints, mypy, generics, Protocol |
| Testing | references/testing.md |
pytest, fixtures, mocking, parametrize |
| Async Patterns | references/async-patterns.md |
async/await, asyncio, task groups, context managers |
Constraints
MUST DO
- Type hints for all function signatures and class attributes
- PEP 8 compliance with black formatting
- Comprehensive docstrings (Google style)
- Test coverage exceeding 90% with pytest
- Use
X | Noneinstead ofOptional[X](Python 3.10+) - Async/await for I/O-bound operations
- Dataclasses over manual init methods
- Context managers for resource handling
What ships with it
7 files 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.
- yesterday First seen · 221 lines · 84 tokens per session scan A 73234d5cfcca
Qpython-pro is a skill published in the GitHub repository inho-team/qe-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 84 tokens to every session and 1,686 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-01.
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