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-grantsgit 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-grants)<a href="https://agentmods.dev/skills/deepxiv/deepxiv_sdk/deepxiv-fa-grants"><img src="https://agentmods.dev/badge/skills/deepxiv/deepxiv_sdk/deepxiv-fa-grants/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-grants"><img src="https://agentmods.dev/badge/skills/deepxiv/deepxiv_sdk/deepxiv-fa-grants.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 | $0.00055 | $0.01674 |
| Opus 5.5 | $0.00022 | $0.00670 |
| Sonnet 5.5 | $0.00011 | $0.00335 |
| Haiku 4.5 | $0.00006 | $0.00167 |
Grade A, and why
deepxiv-fa-grants 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DeepXiv · Grants (grants)
~1.31M research awards: ~637k NSF awards (one per award id), ~570k NIH RePORTER projects (multi-year funding merged per core project number, with per-year amounts) and ~107k EU CORDIS projects (FP5 to Horizon Europe, amounts in EUR). Synced daily; exact counts are in corpus (live). Organisation / country / PI / directorate / activity code / dates / amounts come from the source; topics, methods, domain and one-line summaries are model-generated (title-only where no abstract exists — see _enrich.basis).
Corpus: 1,313,241 documents, updated 2026-10.
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 grants "single-cell transcriptomics" -F agency=nih -F "fy>=2020" -k 5
deepxiv fa search grants "quantum computing" -F agency=nsf -F "amount_total>=1000000" -k 5
deepxiv fa read grants nih:R25HG007515 -l brief
deepxiv fa ask "Which NIH institutes fund single-cell atlas projects, and how much?" -d grants
Free samples: ids nih:R25HG007515; queries single cell transcriptomics.
Search
deepxiv fa search grants "query" [-F FILTER]... [-k N] [--offset N] [--mode M] [--head] [--json]
Modes: hybrid, dense, bm25. 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.
| filter | type | -F syntax |
meaning |
|---|---|---|---|
agency |
keyword | k=v, k=a,b |
Funding agency Values: nih, nsf, cordis. |
research_domain |
keyword | k=v, k=a,b |
Research domain (model-assigned, closed set of 13) Values: biomedical, life_sciences, clinical, public_health, engineering, physical_sciences, chemistry, math_stats …. |
ic_or_directorate |
keyword | k=v, k=a,b |
NIH institute, NSF directorate or CORDIS framework programme (FP7 / H2020 / HORIZON …, see facets) |
activity_code |
keyword | k=v, k=a,b |
Funding mechanism: NIH activity code (R01 / R21 / F32 …), NSF award type or CORDIS funding scheme |
fy |
integer | k=v, k>=n, k=n..m |
Fiscal year, range |
start_year |
integer | k=v, k>=n, k=n..m |
Project start year, range |
end_year |
integer | k=v, k>=n, k=n..m |
Project end year, range |
amount_total |
number | k=v, k>=n, k=n..m |
Total amount, range (USD for NIH / NSF; EU contribution in EUR for CORDIS — pair with agency when filtering across agencies) |
org_country |
keyword | k=v, k=a,b |
Organisation country (source casing is inconsistent — see notes) |
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 · 97 lines · 0 tokens per session scan A 97f720afb4b4
deepxiv-fa-grants is a skill published in the GitHub repository DeepXiv/deepxiv_sdk (838 stars, last pushed 6d ago), licensed MIT. It adds 55 tokens to every session and 1,674 once invoked, about $0.0002 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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