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 agrc/agent-skills --skill ugrc-pythongit clone --depth 1 https://github.com/agrc/agent-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/agrc/agent-skills/ugrc-python)<a href="https://agentmods.dev/skills/agrc/agent-skills/ugrc-python"><img src="https://agentmods.dev/badge/skills/agrc/agent-skills/ugrc-python/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/agrc/agent-skills/ugrc-python"><img src="https://agentmods.dev/badge/skills/agrc/agent-skills/ugrc-python.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 | $0.00015 | $0.00237 |
| Opus 5.5 | $0.00006 | $0.00095 |
| Sonnet 5.5 | $0.00003 | $0.00047 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
ugrc-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 1mo 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
Prefer the pathlib library over the older os.path module for handling filesystem paths. Be aware that the arcpy library does not support pathlib.Path objects directly prior to version 3.7; you will need to convert them to strings using str(path). In version 3.7 and later, arcpy can handle pathlib.Path objects directly and can even be set to return them by default using this ArcPy environment setting:
arcpy.env.returnPathlib = True
Linting and Formatting
Use ruff for linting and formatting with the following configuration:
[tool.ruff.lint]
extend-select = ["I"]
If the current project does not implement this exact configuration, offer to migrate it and fix any resulting issues.
Test Coverage
For Python test coverage and Codecov CI guidance, use ugrc-python-code-coverage.
Packaging
For Python packaging migration guidance, use ugrc-python-packaging.
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.
- 1mo ago Changed · -8 lines 6f75ae0f947d
- 1mo ago First seen · 38 lines · 15 tokens per session scan A 8a49dcedb69f
ugrc-python is a skill published in the GitHub repository agrc/agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 237 once invoked, about $0.0001 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 2026-08-31.
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