Genkit is an open-source framework for building AI-powered applications with JavaScript, Go, Python, and Dart. Developers use it to connect language models and other AI providers while implementing chatbots, automations, recommendations, multimodal features, structured outputs, tools, and agent workflows. The catalogue skills support development with Genkit.
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 genkit-ai/genkit --skill python-expertgit clone --depth 1 https://github.com/genkit-ai/genkitWrote 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/genkit-ai/genkit/python-expert)<a href="https://agentmods.dev/skills/genkit-ai/genkit/python-expert"><img src="https://agentmods.dev/badge/skills/genkit-ai/genkit/python-expert/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/genkit-ai/genkit/python-expert"><img src="https://agentmods.dev/badge/skills/genkit-ai/genkit/python-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00026 | $0.00221 |
| Opus 5.5 | $0.00010 | $0.00088 |
| Sonnet 5.5 | $0.00005 | $0.00044 |
| Haiku 4.5 | $0.00003 | $0.00022 |
Grade A, and why
python-expert 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
Python expert
When working with Python in this workspace, follow these conventions:
- Type-hint everything. Parameters, returns, attributes, locals where the type isn't obvious.
- Prefer dataclasses for simple data containers over hand-written
__init__s. - Raise specific exceptions (
ValueError,KeyError,LookupError) with informative messages. Avoid bareException. - Don't swallow errors. Don't
except Exception: pass. Let unexpected errors propagate. - Match the surrounding style. If the file uses single quotes and 4-space indent, match it. Don't reformat unrelated lines.
- Comments explain why, not what. Skip narration like
# loop over items; only comment non-obvious intent. - Small, focused edits. When fixing a bug, change only what's necessary. Leave the rest of the file untouched so the diff stays readable.
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 · 17 lines · 26 tokens per session scan A 1260a0c3cb15
python-expert is a skill published in the GitHub repository genkit-ai/genkit (6,523 stars, last pushed yesterday), licensed Apache-2.0. It adds 26 tokens to every session and 221 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 2026-08-30.
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