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 DeepXiv/deepxiv_sdk --skill deepxiv-fa-talentgit clone --depth 1 https://github.com/DeepXiv/deepxiv_sdkWrote 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/deepxiv/deepxiv_sdk/deepxiv-fa-talent)<a href="https://agentmods.dev/skills/deepxiv/deepxiv_sdk/deepxiv-fa-talent"><img src="https://agentmods.dev/badge/skills/deepxiv/deepxiv_sdk/deepxiv-fa-talent/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/deepxiv/deepxiv_sdk/deepxiv-fa-talent"><img src="https://agentmods.dev/badge/skills/deepxiv/deepxiv_sdk/deepxiv-fa-talent.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 | $0.00072 | $0.02625 |
| Opus 5.5 | $0.00029 | $0.01050 |
| Sonnet 5.5 | $0.00014 | $0.00525 |
| Haiku 4.5 | $0.00007 | $0.00263 |
Grade A, and why
deepxiv-fa-talent 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 5d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DeepXiv · Talent (talent)
AI researcher directory: 189k people, 160k LLM-researched profiles (education, career, representative papers, open source), Google Scholar metrics rendered live. One document per person; id is person_id.
Corpus: 191,238 documents, updated 2026-10-19.
Setup
pip install -U deepxiv-sdk # deepxiv registers a token on first use
With a registered key (https://data.rag.ac.cn/register), search and read are fair use: 60/min, 5 at once, 5,000/day; on the auto-registered token they spend the deepxiv daily limit at the credits listed below. ask draws on the daily ask allowance (resets 00:00 UTC; a site-wide daily total can run out early at peak times), or 3 lifetime trial asks on the auto-registered token. On 429, back off for Retry-After seconds. Data goes to stdout; cost, quota and sources go to stderr. Exit 0 ok, 1 API error, 2 usage error. The general CLI guide is the deepxiv-cli skill.
Start here
deepxiv fa search talent "Yann LeCun" -k 3 # a name: English, Chinese, pinyin or "Last, First"
deepxiv fa search talent "具身智能" -F org=清华大学 -F role=教授 -F "h_index>=30" -k 10 # Chinese institutions take Chinese values
deepxiv fa search talent "world model" -F career_stage=student -F location=北京,上海 -k 20 # location values are Chinese city names: 北京, 上海
deepxiv fa read talent 15023 3426 2813 -l brief # several cards in one call
deepxiv fa read talent 15023 -e network # coauthors
deepxiv fa resolve "Geoffrey Hinton" "Yann LeCun" # names → person_id, batch
deepxiv fa ask "who works on self-supervised learning at Mila" -d talent
Free samples: ids 7870; queries Federica Sarro, Jürgen Schmidhuber, 软件工程 实证研究.
Search
deepxiv fa search talent "query" [-F FILTER]... [-k N] [--offset N] [--mode M] [--head] [--json]
Modes: hybrid, dense, bm25, name. Up to 100 hits. Cost 2 (with --head: 3).
An empty query is rejected; use "*" to list by filters only. Filters combine with AND; an undeclared field exits 2.
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.
- 5d ago First seen · 123 lines · 0 tokens per session scan A e576120901e5
deepxiv-fa-talent is a skill published in the GitHub repository DeepXiv/deepxiv_sdk (838 stars, last pushed 6d ago), licensed MIT. It adds 72 tokens to every session and 2,625 once invoked, about $0.0003 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 2026-10-20.
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