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/opendatahub-io/ai-helpers/python-packaging-complexitynpx skills add opendatahub-io/ai-helpers --skill python-packaging-complexitygit clone --depth 1 https://github.com/opendatahub-io/ai-helpersWrote 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/opendatahub-io/ai-helpers/python-packaging-complexity)<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/python-packaging-complexity"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/python-packaging-complexity.svg" alt="Measured on agentmods" 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 | $0.00040 | $0.00939 |
| Opus 5 | $0.00020 | $0.00469 |
| Sonnet 5 | $0.00008 | $0.00188 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
python-packaging-complexity 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Package Build Complexity Analysis
This skill helps you evaluate the build complexity of Python packages by analyzing their PyPI metadata. It determines whether a package likely requires compilation, assesses build complexity, and provides recommendations for wheel building strategies.
Instructions
When a user asks about Python package build complexity, building wheels, or evaluating PyPI packages for compilation requirements:
-
Run the PyPI inspection script using the package name and optional version:
./scripts/pypi_inspect.py <package_name> [version] -
Analyze the output and provide interpretation focusing on:
Build Complexity Assessment
- Compilation Requirements: Whether the package needs C/C++/Rust/Fortran compilation
- Complexity Score: Numerical score indicating build difficulty (0-10+ scale)
- Key Indicators: Specific classifiers, keywords, or dependencies that suggest complexity
Distribution Analysis
- Source Distribution Availability: Whether sdist is available for building
- Existing Wheels: What wheel types already exist (platform-specific, universal)
- Wheel Coverage: Gaps in wheel availability that might need custom builds
Dependency Analysis
- Complex Dependencies: Dependencies that themselves require compilation
- Version Constraints: Python version requirements and compatibility
- Transitive Complexity: How dependencies affect overall build complexity
-
Provide actionable recommendations:
- Whether to build from source or use existing wheels
- Required build tools and dependencies
- Platform-specific considerations
- Estimated build time and resource requirements
Key Complexity Indicators
High Complexity (Score 5+)
- Native extensions (C/C++/Rust/Fortran classifiers)
- CUDA/GPU acceleration keywords
- Known complex packages (torch, tensorflow, numpy, scipy)
- Missing or limited wheel availability
- Many compiled dependencies
What ships with it
1 file 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 · 122 lines · 40 tokens per session scan A e41f3853f430
python-packaging-complexity is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed yesterday), licensed Apache-2.0. It adds 40 tokens to every session and 939 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 2026-09-03.
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