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 agentmods add skills/brevdev/workshop-build-an-agent/dataset_profilernpx skills add brevdev/workshop-build-an-agent --skill dataset_profilergit clone --depth 1 https://github.com/brevdev/workshop-build-an-agentWrote 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/brevdev/workshop-build-an-agent/dataset_profiler)<a href="https://agentmods.dev/skills/brevdev/workshop-build-an-agent/dataset_profiler"><img src="https://agentmods.dev/badge/skills/brevdev/workshop-build-an-agent/dataset_profiler.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.00395 |
| Opus 5 | $0.00011 | $0.00198 |
| Sonnet 5 | $0.00004 | $0.00079 |
| Haiku 4.5 | $0.00002 | $0.00040 |
Grade A, and why
dataset_profiler 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 4d 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
Dataset Profiler Skill
You are profiling an unfamiliar dataset. Follow this procedure in order and report findings in the output format below. Prefer running small scripts over guessing; never describe data you have not inspected.
Procedure
- Shape & size — row count, column count, file size on disk.
- Schema — every column with its dtype; flag columns whose dtype looks wrong for the name (e.g. numeric IDs parsed as float, dates as object).
- Nulls — per-column null counts; call out any column over 5% null.
- Duplicates — count of fully duplicated rows.
- Numeric distributions — min / max / mean / std for numeric columns; flag impossible values (negative ages, future dates, sentinel -999s).
- Cardinality — unique-value counts for object columns; identify likely categorical columns (low cardinality) vs identifiers (cardinality ≈ rows).
- Three surprising facts — the three most decision-relevant things a human should know before using this data.
Output format
## Dataset Profile: <path>
- Shape: <rows> x <cols> (<size>)
- Schema: <table or list>
- Quality: <nulls, duplicates, suspicious values>
- Highlights:
1. ...
2. ...
3. ...
Notes
- For datasets over 100,000 rows on GPU-equipped machines, prefer
GPU-accelerated profiling (e.g.
cudf.pandas) and keep intermediate results on the GPU. - If the file fails to parse, report the first malformed line rather than silently switching parsers.
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.
- 4d ago First seen · 46 lines · 22 tokens per session scan A 5b97cc2ded4f
dataset_profiler is a skill published in the GitHub repository brevdev/workshop-build-an-agent (133 stars, last pushed 16d ago), licensed Apache-2.0. It adds 22 tokens to every session and 395 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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