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.
git clone --depth 1 https://github.com/datahub-project/datahub-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/commands/datahub-project/datahub-skills/catalog-enrich)<a href="https://agentmods.dev/commands/datahub-project/datahub-skills/catalog-enrich"><img src="https://agentmods.dev/badge/commands/datahub-project/datahub-skills/catalog-enrich/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/commands/datahub-project/datahub-skills/catalog-enrich"><img src="https://agentmods.dev/badge/commands/datahub-project/datahub-skills/catalog-enrich.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 | $0.00020 | $0.00166 |
| Opus 5 | $0.00010 | $0.00083 |
| Sonnet 5 | $0.00004 | $0.00033 |
| Haiku 4.5 | $0.00002 | $0.00017 |
Grade A, and why
catalog-enrich 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 10d 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
DataHub Enrich
Use the Skill tool to invoke the full datahub-enrich skill:
Skill tool:
skill: "datahub-skills:datahub-enrich"
User's request: $ARGUMENTS
This skill manages metadata in DataHub:
- Understand the enrichment intent (add tag, update description, set owner, etc.)
- Resolve target entities and show current state
- Build an enrichment plan with before/after comparison
- Get your approval before making any changes
- Execute updates and verify
If no arguments provided, ask what metadata to update.
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.
- 10d ago First seen · 27 lines · 20 tokens per session scan A bd69e1d99e52
catalog-enrich is a command published in the GitHub repository datahub-project/datahub-skills (38 stars, last pushed 12d ago), licensed Apache-2.0. It adds 20 tokens to every session and 166 once invoked, about $0.0001 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 2026-08-30.
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