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-python-packaginggit 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-packaging)<a href="https://agentmods.dev/skills/agrc/agent-skills/ugrc-python-packaging"><img src="https://agentmods.dev/badge/skills/agrc/agent-skills/ugrc-python-packaging/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-packaging"><img src="https://agentmods.dev/badge/skills/agrc/agent-skills/ugrc-python-packaging.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 | $0.00039 | $0.00524 |
| Opus 5.5 | $0.00016 | $0.00210 |
| Sonnet 5.5 | $0.00008 | $0.00105 |
| Haiku 4.5 | $0.00004 | $0.00052 |
Grade A, and why
ugrc-python-packaging 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
When a project uses a legacy setup.py, offer to migrate its packaging configuration to pyproject.toml; do not perform this migration automatically. If the user approves, make the migration in a separate commit from unrelated changes.
Preserve the existing package metadata, dependencies, optional dependency groups, and package-discovery configuration. Upgrade the build backend to Hatchling when the user approves: use requires = ["hatchling"] and build-backend = "hatchling.build", then replace setuptools-specific configuration with the equivalent Hatchling configuration. Update CI cache dependency paths that reference setup.py to reference pyproject.toml. Remove obsolete setup.py configuration only after the declarative configuration is complete, and validate the migration by building source and wheel distributions and running the project's tests and Ruff checks.
Put all testing and build dependencies in [project.optional-dependencies] under a dev group, and remove any tests group. Make sure to update any documentation that references the tests group to reference the dev group instead.
When the version is stored only in a dedicated module migrate that value to a static version field in [project], remove dynamic = ["version"] and the setuptools dynamic-version configuration, and delete the unused module. Fix any imports of the old version module using the following pattern:
Resolve the version once in your top-level init.py file using importlib.metadata, and then import that version attribute across your other modules. In the root init.py (e.g., uocc_skid/init.py)
from importlib.metadata import version
try:
# Use distribution name as defined in pyproject.toml
__version__ = version("uocc-skid")
except PackageNotFoundError:
# Fallback when running from raw source tree without installation
__version__ = "0.0.0-dev"
Then in other modules, import the version attribute from the top-level package:
from uocc_skid import __version__
Clean up any remaining references to the old version module in the codebase, including in CI workflows and documentation.
Review declared console scripts during the migration. Remove an entry point only when its target is confirmed stale or nonexistent; otherwise preserve it in [project.scripts].
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 First seen · 36 lines · 39 tokens per session scan A 68a9564ba604
ugrc-python-packaging is a skill published in the GitHub repository agrc/agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 524 once invoked, about $0.0002 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 2026-09-10.
ugrc-python-packaging compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ugrc-python-packagingagrc/agent-skills | Skill | 2 | 1mo ago | MIT | A | 39 | Claude Code, Codex |
| cardputer-buddyanthropics/claude-plugins-official | Skill | 46k | today | Apache-2.0 | A | 109 | Claude Code |
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| gh-address-commentsforyourhealth111-pixel/Vibe-Skills | Skill | 3.8k | today | Apache-2.0 | A | 39 | Codex |
| authoring-dagsastronomer/agents | Skill | 458 | 5d ago | Apache-2.0 | A | 93 | Claude Code |
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