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-appraisegit 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-appraise)<a href="https://agentmods.dev/skills/deepxiv/deepxiv_sdk/deepxiv-fa-appraise"><img src="https://agentmods.dev/badge/skills/deepxiv/deepxiv_sdk/deepxiv-fa-appraise/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-appraise"><img src="https://agentmods.dev/badge/skills/deepxiv/deepxiv_sdk/deepxiv-fa-appraise.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 | $0.00073 | $0.02109 |
| Opus 5.5 | $0.00029 | $0.00844 |
| Sonnet 5.5 | $0.00015 | $0.00422 |
| Haiku 4.5 | $0.00007 | $0.00211 |
Grade A, and why
deepxiv-fa-appraise 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DeepXiv · Appraise (appraise)
Academic appraisal: which academicians and society fellows have cited a paper, and what they actually said. 112k arXiv papers authored by 5,427 fellows and academicians (Chinese Academies, US NAS/NAE, Royal Society / RAEng, ACM / IEEE / AAAI / ACL / AAAS / IAPR / CCF), with 5.26M parsed references and 8.3M citing sentences, each classified by type and stance. The id is the paper being appraised (arXiv id / DOI / title). ask turns the matched sentences into a Chinese appraisal paragraph for grant reports and promotion dossiers, with the English original attached to every claim.
Corpus: 284,124 documents.
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 appraise "DeepSeek-R1" -k 3 # → arxiv:2501.12948
deepxiv fa read appraise arxiv:2501.12948 -l brief # counts and stance breakdown
deepxiv fa read appraise arxiv:2501.12948 -p stance=positive -p org=CAS,CAE # positive sentences from Chinese academicians
deepxiv fa ask "DeepSeek-R1 得到了哪些院士的正面评价" -d appraise -p paper=arxiv:2501.12948
Free samples: ids arxiv:2402.03216; queries BGE-M3.
Search
deepxiv fa search appraise "query" [-F FILTER]... [-k N] [--offset N] [--mode M] [--head] [--json]
Modes: hybrid, title. Up to 20 hits. Cost 3 (with --head: 4).
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 · 108 lines · 73 tokens per session scan A 71a4e8fb51b3
deepxiv-fa-appraise is a skill published in the GitHub repository DeepXiv/deepxiv_sdk (838 stars, last pushed 6d ago), licensed MIT. It adds 73 tokens to every session and 2,109 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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