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-casesgit 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-cases)<a href="https://agentmods.dev/skills/deepxiv/deepxiv_sdk/deepxiv-fa-cases"><img src="https://agentmods.dev/badge/skills/deepxiv/deepxiv_sdk/deepxiv-fa-cases/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-cases"><img src="https://agentmods.dev/badge/skills/deepxiv/deepxiv_sdk/deepxiv-fa-cases.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 | $0.00065 | $0.02453 |
| Opus 5.5 | $0.00026 | $0.00981 |
| Sonnet 5.5 | $0.00013 | $0.00491 |
| Haiku 4.5 | $0.00006 | $0.00245 |
Grade A, and why
deepxiv-fa-cases 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DeepXiv · Law · Judgments (cases)
Court judgments: 17.49M from China (2.65M criminal plus 14.83M civil / administrative / enforcement) and 3.44M US opinions (country=us, tier A). Brief-level hybrid retrieval with LLM-extracted structured fields. Chinese judgment text needs the cases:fulltext grant (the originals carry personal data); US full text waits on the PG store.
Corpus: 27,580,773 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 cases "网络刷单诈骗 未遂" -F province=浙江省 -F "judge_year>=2018" -k 5
deepxiv fa search cases "qualified immunity police" -F country=us -F court_level=scotus -k 5 # US cases filter on year, not judge_year
deepxiv fa read cases us:10316651 -l brief # TikTok v. Garland; the holding comes in English and Chinese
deepxiv fa read cases 8a1c3791-0cce-4094-9b28-a9a600b657c7 # detail: every extracted field, no grant needed
deepxiv fa ask "网络刷单诈骗未遂一般怎么判" -d cases # answers from Chinese judgments only
Free samples: ids 8a1c3791-0cce-4094-9b28-a9a600b657c7, us:577203; queries 网络刷单诈骗 未遂.
Search
deepxiv fa search cases "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.
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 · 119 lines · 0 tokens per session scan A 6558ae68aeee
deepxiv-fa-cases is a skill published in the GitHub repository DeepXiv/deepxiv_sdk (838 stars, last pushed 6d ago), licensed MIT. It adds 65 tokens to every session and 2,453 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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