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 bcastelino/agent-skills-kit --skill databricks-community-geogit clone --depth 1 https://github.com/bcastelino/agent-skills-kitWrote 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/bcastelino/agent-skills-kit/databricks-community-geo)<a href="https://agentmods.dev/skills/bcastelino/agent-skills-kit/databricks-community-geo"><img src="https://agentmods.dev/badge/skills/bcastelino/agent-skills-kit/databricks-community-geo/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/bcastelino/agent-skills-kit/databricks-community-geo"><img src="https://agentmods.dev/badge/skills/bcastelino/agent-skills-kit/databricks-community-geo.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 | $0.00091 | $0.00809 |
| Opus 5 | $0.00046 | $0.00404 |
| Sonnet 5 | $0.00018 | $0.00162 |
| Haiku 4.5 | $0.00009 | $0.00081 |
Grade A, and why
databricks-community-geo 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 11d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Databricks Community GEO
Overview
This skill applies Generative Engine Optimization (GEO) best practices to Databricks Community content: Community Articles, Technical Blog posts, and Q&A answers. It ensures content is written to be found and correctly cited by Community search, search engines, and AI assistants, while remaining clear and useful to human readers first.
Example Triggers
- "Help me write a Databricks Community article about troubleshooting Unity Catalog permission errors."
- "Review this Q&A answer and make it more discoverable."
- "Score this draft against the Databricks GEO checklist."
- "Is this title specific enough for search and AI assistants?"
When Writing New Content
- Consult
references/geo-best-practices.mdfor the full set of GEO practices before drafting. - Write a specific, searchable title naming the feature, product, or exact error message. Do NOT use generic titles like "Need Help" or "Spark Issue."
- Lead with the answer (BLUF): state the solution or key takeaway in the first paragraph, before any heading. Add context, steps, and code afterward.
- Structure the body with
##/###headings, short paragraphs, bullet or numbered lists, and fenced code blocks (with language) for commands and examples. - Add concrete examples: code snippets, sample output, or a real-world scenario.
- Use Databricks feature/product names and relevant error messages naturally; avoid keyword stuffing.
- Link to official Databricks documentation or related Community articles where they add value.
- State prerequisites, limitations, and version-specific behavior explicitly. Only assert claims that can be supported.
- For Q&A answers, remind the author to mark the correct response as the Accepted Solution.
When Reviewing an Existing Draft
- Save the draft as a Markdown file if it is not already one.
- Run the checklist scorer:
python scripts/score_content.py --input <draft.md>
Add --qa if the draft is a Q&A-style answer, to also check for an Accepted Solution mention:
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 62 lines · 91 tokens per session scan A 319a81067097
databricks-community-geo is a skill published in the GitHub repository bcastelino/agent-skills-kit (2 stars, last pushed 1mo ago), licensed MIT. It adds 91 tokens to every session and 809 once invoked, about $0.0005 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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