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/connector-planning)<a href="https://agentmods.dev/commands/datahub-project/datahub-skills/connector-planning"><img src="https://agentmods.dev/badge/commands/datahub-project/datahub-skills/connector-planning/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/connector-planning"><img src="https://agentmods.dev/badge/commands/datahub-project/datahub-skills/connector-planning.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 | $0.00027 | $0.00198 |
| Opus 5 | $0.00014 | $0.00099 |
| Sonnet 5 | $0.00005 | $0.00040 |
| Haiku 4.5 | $0.00003 | $0.00020 |
Grade A, and why
connector-planning 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 Connector Planning
Use the Skill tool to invoke the full datahub-connector-planning skill:
Skill tool:
skill: "datahub-skills:datahub-connector-planning"
User's request: $ARGUMENTS
This skill guides you through planning a new DataHub connector:
- Classify the source system type (SQL DB, API, etc.)
- Research the source using the
datahub-skills:connector-researcheragent - Gather user requirements (test environment, features, permissions)
- Create a comprehensive
_PLANNING.mddocument with entity mapping, architecture decisions, and implementation order
If no arguments provided, ask which source system to plan a connector for.
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 · 26 lines · 27 tokens per session scan A d1d63a06b59a
connector-planning is a command published in the GitHub repository datahub-project/datahub-skills (38 stars, last pushed 12d ago), licensed Apache-2.0. It adds 27 tokens to every session and 198 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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