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 agentlas-ai/agentlas-desktop --skill hepdatagit clone --depth 1 https://github.com/agentlas-ai/agentlas-desktopWrote 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/agentlas-ai/agentlas-desktop/hepdata)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/hepdata"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/hepdata/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/agentlas-ai/agentlas-desktop/hepdata"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/hepdata.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 | $0.00035 | $0.00358 |
| Opus 5.5 | $0.00014 | $0.00143 |
| Sonnet 5.5 | $0.00007 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
hepdata scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
HEPData
- Call
fetch_hepdata_recordwith an exactins...record id. Request table metadata only when needed. - Call
fetch_hepdata_tablewith the exact record id, table name, and required known record version. If the provider refuses automated access, surface the refusal; never scrape or bypass a challenge. - Use
normalize_hepdata_tableonly for an already available JSON body. Supply its version when known; a missing version remains explicitlynullrather than being guessed. - Preserve the record URI, version-pinned table URL, DOI citations, provenance receipt, raw-response hash, and normalized hash.
- Hand
rendererProjection.seriesto a host-provided Vega lab only when installed. The projection keeps labeled components separate. Use$hepdata-chi-squareonly when the research model explicitly declares selected labels mutually independent; never infer covariance or correlations.
Outputs
- HEPData record metadata or a deterministic table preserving independent/dependent variables, null and empty-string missing measurements, qualifiers, symmetric/asymmetric errors, relative percentages, one-sided errors, and inclusive measurements with no independent variable.
- A renderer projection with numeric bin centers and per-component error-bar endpoints while retaining all source scalars alongside it.
Verification
- The response record id matches the requested
ins...id. - Every variable has the same bounded point count.
- Every uncertainty retains its label and symmetric/asymmetric form.
- Relative and one-sided uncertainty projections retain raw values and never turn a missing side into zero.
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.
- 1mo ago First seen · 25 lines · 35 tokens per session scan A 122ad8686998
hepdata is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 35 tokens to every session and 358 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-04.
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