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 dkharlanau/agent-ready-web-profile --skill arwp-dataset-publicationgit clone --depth 1 https://github.com/dkharlanau/agent-ready-web-profileWrote 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/dkharlanau/agent-ready-web-profile/arwp-dataset-publication)<a href="https://agentmods.dev/skills/dkharlanau/agent-ready-web-profile/arwp-dataset-publication"><img src="https://agentmods.dev/badge/skills/dkharlanau/agent-ready-web-profile/arwp-dataset-publication/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/dkharlanau/agent-ready-web-profile/arwp-dataset-publication"><img src="https://agentmods.dev/badge/skills/dkharlanau/agent-ready-web-profile/arwp-dataset-publication.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 | $0.00038 | $0.00740 |
| Opus 5 | $0.00019 | $0.00370 |
| Sonnet 5 | $0.00008 | $0.00148 |
| Haiku 4.5 | $0.00004 | $0.00074 |
Grade A, and why
arwp-dataset-publication 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 2d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ARWP Dataset Publication
Use this skill when a target website contains a substantial reusable corpus: knowledge records, cards, annotations, research observations, evaluation cases, exercises, benchmarks or other structured data with independent reuse value.
Do not activate this workflow merely to create an SEO artifact.
Outcome
Turn an existing mutable website corpus into a deliberately scoped, versioned, reproducible and externally citable dataset release.
Workflow
- Inspect the repository and public site before creating files.
- Decide whether a genuine reusable dataset exists. If not, mark the module not applicable and stop.
- Identify the canonical corpus and exclude private, operational, generated-noise and unsafe-to-release files.
- Run
node bin/arwp-dataset.mjs <canonical-site-url> --jsonwhen the public site is available. - Ensure a human dataset/research landing surface exists.
- Publish canonical Schema.org
Datasetmetadata. Use Croissant/DCAT in addition only when the dataset shape/catalog justifies them. - Publish methodology, provenance, limitations, schema/data dictionary and explicit reuse rights.
- Choose a dataset release version and freeze the distributions intended for citation.
- Compute SHA-256 checksums for the exact release bytes.
- Prepare accurate
CITATION.cffmetadata for the dataset release. - Publish the frozen release through Zenodo or another appropriate external persistent archive using owner-authorized access.
- Only after the archive issues the identifier, verify that the DOI resolves to the intended release and then add the exact DOI to Dataset metadata,
CITATION.cff, the human citation surface and relevant trust metadata. - Preserve prior version DOI identity when a later corpus release changes cited bytes.
- Re-run the ARWP dataset audit and keep missing or externally blocked work explicit.
Required state model
Before external archival issuance, use an explicit state such as:
{
"publicationState": "doi-not-issued",
"persistentIdentifier": {
"type": "DOI",
"state": "not-issued",
"value": null
}
}
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.
- 2d ago Changed · +2 lines f24fbd1bfd7c
- 3d ago First seen · 68 lines · 38 tokens per session scan A 46ec463ed6d7
arwp-dataset-publication is a skill published in the GitHub repository dkharlanau/agent-ready-web-profile (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 38 tokens to every session and 740 once invoked, about $0.0002 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 2026-09-08.
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