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 searchgit 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)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/search"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/search/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"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/search.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 | $0.00027 | $0.00311 |
| Opus 5.5 | $0.00011 | $0.00124 |
| Sonnet 5.5 | $0.00005 | $0.00062 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
academic-search 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
Search Academic Literature
- Turn the research question into one precise scholarly query. Add a domain hint and year range only when the user or project makes them meaningful.
- Call
search_academic_literaturewithproviders: "auto". Override providers only for a concrete coverage reason. - Inspect
coverage, every provider receipt, warnings, retraction flags, and each returnedsourceId. - Summarize convergence, disagreement, missing coverage, and promising research gaps. Prefer records seen by multiple providers, but never treat provider count as scientific validation.
- When a claim depends on findings rather than metadata, retrieve and verify the abstract or full text in a later evidence step before calling the claim supported.
Outputs
- A deduplicated list of project Source records with DOI, PMID, or arXiv identity when available.
- Provider-level request and response hashes, coverage, partial-failure warnings, and deterministic ranking metadata.
- A clear boundary between discovered metadata and content-verified evidence.
Verification
- At least one provider receipt must have
status: "ok". - Every cited search result must carry a non-null
sourceIdandsourceVersionId. - A result with
isRetracted: truemay be discussed only as retracted literature. - Never claim full-text verification from this search workflow alone.
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 · 26 lines · 27 tokens per session scan A 1f97b6eac9d2
academic-search is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 27 tokens to every session and 311 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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