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 pantheon-org/tekhne --skill semantic-scholar-searchgit clone --depth 1 https://github.com/pantheon-org/tekhneWrote 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/pantheon-org/tekhne/semantic-scholar-search)<a href="https://agentmods.dev/skills/pantheon-org/tekhne/semantic-scholar-search"><img src="https://agentmods.dev/badge/skills/pantheon-org/tekhne/semantic-scholar-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/pantheon-org/tekhne/semantic-scholar-search"><img src="https://agentmods.dev/badge/skills/pantheon-org/tekhne/semantic-scholar-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00081 | $0.01719 |
| Opus 5 | $0.00041 | $0.00860 |
| Sonnet 5 | $0.00016 | $0.00344 |
| Haiku 4.5 | $0.00008 | $0.00172 |
Grade A, and why
semantic-scholar-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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Semantic Scholar Search
Search Semantic Scholar for papers, fetch structured metadata by paper ID or DOI, profile authors, and traverse citation graphs. Uses the official Semantic Scholar API — no scraping, structured results, free to use.
When to Use
- Discovering papers on a topic before running
triage-paper - Resolving an arxiv ID or DOI to full metadata during
triage-paperstep 1 - Fetching papers that cite or are cited by a known paper
- Profiling an author to find their key publications
- Preferred over
google-scholar-searchwhenever both are available
When Not to Use
- The
semantic-scholarMCP server is configured — optionally prefer it over this script; the MCP returns the same data with less setup - The paper is in a biomedical domain not covered by Semantic Scholar — consider PubMed instead
- You need Google Scholar–exclusive sources (patents, grey literature) — use
google-scholar-search
Mindset
This is a structured API, not a search engine — treat it accordingly.
- IDs over titles: a gotcha is using a paper title as the
--paper-idflag. Thepapersubcommand requires a Semantic Scholar paper ID, arxiv ID (prefixarXiv:), or DOI. Titles go tosearch. - Author IDs, not names: the
authorsubcommand requires a Semantic Scholar author ID. A common pitfall is passing a name and getting "not found". Usesearchfirst to locate the author ID. - Rate limits apply without a key: 100 requests per 5 minutes without an API key. NEVER issue search loops that exhaust the quota; optionally set
SEMANTIC_SCHOLAR_API_KEYto increase limits.
Workflow
1. Choose the right subcommand
| Goal | Subcommand | Key flag |
|---|---|---|
| Keyword discovery | search |
--query |
| Full metadata for a known paper | paper |
--paper-id (SS ID, arXiv:NNNN, or DOI) |
| Author publications and h-index | author |
--author-id (Semantic Scholar ID) |
| Papers citing or cited by a paper | citations |
--paper-id + --type |
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .audits/2026-04-10/analysis.md 1.2 KB
- .audits/2026-04-10/audit.json 508 B
- .audits/latest 10 B
- evals/instructions.json 646 B
- evals/scenario-01.md 2.1 KB
- evals/scenario-02.md 2.3 KB
- evals/scenario-03.md 2.0 KB
- evals/summary.json 69 B
- references/setup-and-troubleshooting.md 1.9 KB
- requirements.txt 41 B
- scripts/semantic-scholar-search.py 14 KB runs code
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 · 144 lines · 81 tokens per session scan A 73149e49615f
semantic-scholar-search is a skill published in the GitHub repository pantheon-org/tekhne (10 stars, last pushed yesterday), licensed MIT. It adds 81 tokens to every session and 1,719 once invoked, about $0.0004 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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