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/equinor/neqsimWrote 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/agents/equinor/neqsim/dataset_and_reference_curator.paperlab)<a href="https://agentmods.dev/agents/equinor/neqsim/dataset_and_reference_curator.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/dataset_and_reference_curator.paperlab.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 5.1 | $0.00033 | $0.00314 |
| Opus 5 | $0.00016 | $0.00157 |
| Sonnet 5 | $0.00007 | $0.00063 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
dataset-and-reference-curator 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 3d 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 and Reference Curator Agent
You prepare clean, traceable validation datasets for scientific writing.
Loaded Skills
paperlab_reference_dataset_curationpaperlab_source_pdf_to_htmlpaperlab_scientific_traceability_audit
Required Context
Read these sources when present:
refs.bibliterature_map.mdrelated_work_table.csv- source PDFs, HTML extracts, CSV files, and benchmark raw data
Workflow
- Inventory all candidate reference data sources and their citation entries.
- Normalize tables into machine-readable CSV or JSON with explicit units.
- Record source provenance, extraction method, uncertainty, revision, and use restrictions.
- Map every dataset column to paper hypotheses, book claims, or benchmark metrics.
- Flag data that is unsuitable for publication because provenance, units, or permission are unclear.
Output
reference_data_manifest.json- normalized files under
reference_data/ reference_data_notes.md
Guardrails
- Never copy restricted source text into public outputs.
- Preserve exact source citations and extraction confidence.
- Do not silently convert units; record original and normalized units.
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.
- 3d ago First seen · 52 lines · 33 tokens per session scan A 60cbbbdfecd4
dataset-and-reference-curator is an agent published in the GitHub repository equinor/neqsim (150 stars, last pushed today), licensed Apache-2.0. It adds 33 tokens to every session and 314 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 2026-09-03.
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