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 search-inspiregit 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/search-inspire)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/search-inspire"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/search-inspire/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/search-inspire"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/search-inspire.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 | $0.00024 | $0.00207 |
| Opus 5.5 | $0.00010 | $0.00083 |
| Sonnet 5.5 | $0.00005 | $0.00041 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
search-inspire 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
INSPIRE literature
- Form one precise INSPIRE query and choose relevance, most recent, or most cited ordering. Keep page size at or below the plugin's 100-record safety bound.
- Call
search_inspire_literaturewith no more than 100 records per page. - Preserve the provenance receipt and distinguish paper metadata/abstract discovery from content verification.
Outputs
- A deterministic
agentlas.physics.inspire-literature/v1result with paper identities, provider total/next-page metadata, and a source receipt.
Verification
- Every paper carries an INSPIRE id and title.
- Duplicate record ids, off-host next-page URLs, and provider results larger than the requested page are rejected.
- The raw-response and normalized hashes are distinct receipt fields.
- No result is described as full-text verified unless a later evidence step verifies it.
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 · 22 lines · 24 tokens per session scan A 9b0cbed3f0a8
search-inspire is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 24 tokens to every session and 207 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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