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 skills add oborchers/fractional-cto --skill packaging-distributiongit clone --depth 1 https://github.com/oborchers/fractional-ctoWrote 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/oborchers/fractional-cto/packaging-distribution)<a href="https://agentmods.dev/skills/oborchers/fractional-cto/packaging-distribution"><img src="https://agentmods.dev/badge/skills/oborchers/fractional-cto/packaging-distribution/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/skills/oborchers/fractional-cto/packaging-distribution"><img src="https://agentmods.dev/badge/skills/oborchers/fractional-cto/packaging-distribution.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 | $0.00098 | $0.02447 |
| Opus 5.5 | $0.00039 | $0.00979 |
| Sonnet 5.5 | $0.00020 | $0.00489 |
| Haiku 4.5 | $0.00010 | $0.00245 |
Grade A, and why
packaging-distribution 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 3d 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 — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ship Wheels for Every Platform Your Users Run
A package without pre-built wheels forces users to have a compiler toolchain, correct system headers, and patience. Pydantic-core ships 30+ platform-specific wheels so pip install pydantic takes seconds, not minutes. Pure Python packages get this for free with a single py3-none-any wheel. Compiled extensions require deliberate CI investment -- but cibuildwheel and maturin-action make it tractable.
Pure Python vs Compiled Extensions
Default to pure Python. Only add compiled extensions when profiling proves Python is the bottleneck and the speedup is 10x or greater.
| Situation | Choice | Examples |
|---|---|---|
| I/O-bound (network, disk) | Pure Python | FastAPI, httpx, Rich, Click |
| CPU-bound tight loops, parsing, serialization | Compiled extension | Pydantic-core, orjson, Polars |
| Wrapping existing C/C++/Rust library | Compiled extension | cryptography, lxml |
Extension Technology Decision
| Technology | Language | Build Backend | Used By |
|---|---|---|---|
| PyO3 + maturin | Rust | maturin |
Pydantic-core, Polars, Ruff, uv, orjson |
| Cython | Cython/C | setuptools |
uvloop, lxml, scikit-learn |
| pybind11 | C++ | scikit-build-core |
SciPy (partial), Open3D |
| scikit-build-core | C/C++/Fortran | scikit_build_core.build |
CMake-dependent projects |
| cffi | C | hatchling/setuptools |
cryptography (backend) |
Rust + PyO3 + maturin is the dominant choice for new compiled extensions (2023-2025). Prefer it for greenfield performance-critical work.
Wheel Format and Platform Tags
A wheel filename encodes compatibility: {name}-{version}-{python}-{abi}-{platform}.whl
httpx-0.28.0-py3-none-any.whl # Pure Python
pydantic_core-2.27.0-cp312-cp312-manylinux_2_17_x86_64.whl # CPython 3.12, Linux
cryptography-44.0.0-cp39-abi3-manylinux_2_28_x86_64.whl # Stable ABI, cp39+
Minimum Wheel Matrix for Compiled Extensions
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.
- 3d ago First seen · 215 lines · 98 tokens per session scan A 239881309e31
packaging-distribution is a skill published in the GitHub repository oborchers/fractional-cto (32 stars, last pushed 3d ago), licensed MIT. It adds 98 tokens to every session and 2,447 once invoked, about $0.0004 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 2026-10-13.
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