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 beita6969/ScienceClaw --skill literature-searchgit clone --depth 1 https://github.com/beita6969/ScienceClawWrote 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/beita6969/scienceclaw/literature-search)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/literature-search"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/literature-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/beita6969/scienceclaw/literature-search"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/literature-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Supply Chain · line 31 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 31 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 102 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 106 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 114 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 68 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00090 | $0.01810 |
| Opus 5 | $0.00045 | $0.00905 |
| Sonnet 5 | $0.00018 | $0.00362 |
| Haiku 4.5 | $0.00009 | $0.00181 |
Grade A, and why
literature-search scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://api.semanticscholar.org/graph/v1/paper/search?\ How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Search (Meta Skill)
Orchestrate comprehensive literature searches across multiple databases. Always execute real API calls — never fabricate results or rely on training data.
Priority Order of Databases
- Semantic Scholar (PRIMARY) — best relevance ranking, AI TLDR summaries, citation graph
- OpenAlex (PRIMARY) — 250M+ works, powerful filtering, open access URLs
- arXiv — preprints in physics, math, CS, biology, finance, statistics
- PubMed — biomedical and life sciences (NCBI may be unreachable from some networks)
- CrossRef — DOI resolution and metadata only (NOT for search — poor relevance ranking)
IMPORTANT: CrossRef search results are poorly ranked by relevance. Never use CrossRef as the primary search engine. Use it only for DOI-based lookups and metadata enrichment.
Mandatory Search Protocol
Every literature search MUST follow this protocol:
Step 1: Semantic Scholar Search (always do this first)
# Primary search — returns papers ranked by relevance with AI summaries
curl -s "https://api.semanticscholar.org/graph/v1/paper/search?\
query=YOUR+SEARCH+TERMS&limit=10&\
fields=title,authors,year,abstract,citationCount,influentialCitationCount,\
isOpenAccess,openAccessPdf,url,externalIds,tldr,venue,publicationDate"
Parse results with:
| python3 -c "
import sys, json
data = json.load(sys.stdin)
print(f'Total: {data[\"total\"]} papers')
for i, p in enumerate(data['data']):
authors = ', '.join(a['name'] for a in (p.get('authors') or [])[:3])
if len(p.get('authors') or []) > 3: authors += ' et al.'
tldr = p.get('tldr', {})
tldr_text = tldr['text'][:150] if tldr else 'N/A'
oa = '🔓' if p.get('isOpenAccess') else '🔒'
doi = (p.get('externalIds') or {}).get('DOI', '')
print(f'[{i+1}] {p[\"title\"]}')
print(f' {authors} ({p.get(\"year\",\"?\")}) — {p.get(\"venue\",\"?\")}')
print(f' Cited: {p.get(\"citationCount\",0)} (influential: {p.get(\"influentialCitationCount\",0)}) {oa}')
print(f' TLDR: {tldr_text}')
print(f' DOI: {doi}')
print()
"
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.
- 9d ago First seen · 166 lines · 90 tokens per session scan A 11f635b020eb
literature-search is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 90 tokens to every session and 1,810 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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biomcp
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biomcp-research
Do biomedical literature and variant research with the BioMCP CLI, and file what you learn about the tool itself as issues in the biomcp repo.
biological-expert
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology. Use when the user mentions biology, biotechnology, genetics, bioinformatics, or genomics, or when the task involves Molecular Biology, Genomics & Bioinformatics, Systems Biology, or Data Analysis.