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/open-agent-tools/general-oat-skills/publish-pythonnpx skills add Open-Agent-Tools/General-OAT-Skills --skill publish-pythongit clone --depth 1 https://github.com/Open-Agent-Tools/General-OAT-SkillsWrote 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/open-agent-tools/general-oat-skills/publish-python)<a href="https://agentmods.dev/skills/open-agent-tools/general-oat-skills/publish-python"><img src="https://agentmods.dev/badge/skills/open-agent-tools/general-oat-skills/publish-python.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 | $0.00077 | $0.00473 |
| Opus 5 | $0.00039 | $0.00236 |
| Sonnet 5 | $0.00015 | $0.00095 |
| Haiku 4.5 | $0.00008 | $0.00047 |
Grade A, and why
publish-python 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.
What it actually says
Prepare and trigger a new release for version: $ARGUMENTS
Follow these steps:
Output Format: Use clear section headers, timestamps for each step, and progress indicators for release operations.
Tool Validation: First verify that required tools are installed (uv, gh, git) and the project has proper release configuration.
Version Validation: Validate that the provided version follows semantic versioning format (e.g., 1.2.3, 1.0.0-alpha.1).
- Run cleanup first: Execute all cleanup steps (linting, formatting, type checking)
- Version increment options: Support auto-increment with 'patch', 'minor', or 'major' keywords instead of explicit version numbers
- Update pyproject.toml: Update the version field in pyproject.toml with the new version number
- Update version in docs: Update all references to the next version based on the provided version number
- Check version: Verify version in pyproject.toml and init.py match the target version and are greater than the current version
- Build test: Run
uv buildto ensure the package builds correctly - Create release: Use
gh release createwith the appropriate version tag and release notes - Monitor: Track the publishing workflow with
gh run listto ensure it completes successfully
Error Handling: If any step fails, attempt to fix the issue automatically. If unable to fix, report the specific error and suggested solutions before proceeding.
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 · 40 lines · 77 tokens per session scan A 3fdfeae5af3d
publish-python is a skill published in the GitHub repository Open-Agent-Tools/General-OAT-Skills (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 77 tokens to every session and 473 once invoked, about $0.0004 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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