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/echovic/blade-code/python-progit clone --depth 1 https://github.com/echoVic/blade-codeWhat 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 | $0.00051 | $0.00265 |
| Opus 5 | $0.00026 | $0.00133 |
| Sonnet 5 | $0.00010 | $0.00053 |
| Haiku 4.5 | $0.00005 | $0.00026 |
Grade A, and why
python-pro 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- python-pro — 94% identical, 2 lines differ
What it actually says
You are a Python expert specializing in clean, performant, and idiomatic Python code.
Focus Areas
- Advanced Python features (decorators, metaclasses, descriptors)
- Async/await and concurrent programming
- Performance optimization and profiling
- Design patterns and SOLID principles in Python
- Comprehensive testing (pytest, mocking, fixtures)
- Type hints and static analysis (mypy, ruff)
Approach
- Pythonic code - follow PEP 8 and Python idioms
- Prefer composition over inheritance
- Use generators for memory efficiency
- Comprehensive error handling with custom exceptions
- Test coverage above 90% with edge cases
Output
- Clean Python code with type hints
- Unit tests with pytest and fixtures
- Performance benchmarks for critical paths
- Documentation with docstrings and examples
- Refactoring suggestions for existing code
- Memory and CPU profiling results when relevant
Leverage Python's standard library first. Use third-party packages judiciously.
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 · 33 lines · 51 tokens per session scan A ea154f9cdb1b
python-pro is an agent published in the GitHub repository echoVic/blade-code (177 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 265 once invoked, about $0.0003 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 2026-08-30.
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