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 datahub-project/datahub-skills --skill datahub-evalsgit 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/skills/datahub-project/datahub-skills/datahub-evals)<a href="https://agentmods.dev/skills/datahub-project/datahub-skills/datahub-evals"><img src="https://agentmods.dev/badge/skills/datahub-project/datahub-skills/datahub-evals/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/datahub-project/datahub-skills/datahub-evals"><img src="https://agentmods.dev/badge/skills/datahub-project/datahub-skills/datahub-evals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 95 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 95 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00127 | $0.03515 |
| Opus 5 | $0.00063 | $0.01758 |
| Sonnet 5 | $0.00025 | $0.00703 |
| Haiku 4.5 | $0.00013 | $0.00351 |
Grade B, and why
datahub-evals scanned grade B with 1 finding 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.
Enumerates other installed skillsmediumAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
ls ~/.claude/skills/datahub-sql-workflow/SKILL.md How it starts
The opening of the file, as written. The whole thing — 315 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DataHub Evals
Run DataHub's saved evals, and report answers — yours or another agent's — for DataHub to judge.
You are the runner. There is no script: you fetch the evals, answer each one in a fresh
agent, and report the answers. Every call to DataHub is one evals subcommand, so the queries
and the payload live in the CLI.
acryl-datahub-cloud evals --agent-context # the CLI's own guide to its commands
Use acryl-datahub-cloud evals. A datahub evals form exists in the CLI's own help text and
in some notes, but the group is not wired into the datahub CLI in any shipped release — that
name answers No such command 'evals', and this skill does not use it.
Never simulate the judge
If DataHub's judge cannot be reached, say so and stop. Do not score the answer yourself, do not ask a subagent to render a verdict "the way DataHub would", and do not present any locally-produced score as a verdict.
A simulated verdict written in the house style reads as authoritative, gets pasted into a comparison table, and is comparable with nothing. A model is also not a fair judge of an answer it or a sibling produced.
That is why --type is never passed to evals report: omitting it routes the answer
through the same judge a native run gets, which is the only thing that makes two runs
comparable.
Before you run anything
The CLI is installed.
acryl-datahub-cloud evals --help
If that does not resolve, install the cloud CLI with its evals extra. It pins its own
acryl-datahub, so give it its own environment:
python3 -m venv .venv && source .venv/bin/activate
pip install 'acryl-datahub-cloud[datahub-evals]==2.1.4rc1'
Pin a release that has the commands. The eval commands are still pre-release: the latest
stable (2.1.3) carries neither the datahub-evals extra nor the cli module, so an unpinned
install resolves it, warns that the extra does not exist, and leaves you with no evals at
all. Pin the version, or pass --pre.
What ships with it
1 file 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 · 315 lines · 127 tokens per session scan B d4ab24b2f056
datahub-evals is a skill published in the GitHub repository datahub-project/datahub-skills (38 stars, last pushed 13d ago), licensed Apache-2.0. It adds 127 tokens to every session and 3,515 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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