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.
git clone --depth 1 https://github.com/BingHanOfUESTC/open_agent_teamWrote 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/agents/binghanofuestc/open_agent_team/literature_discovery_agent)<a href="https://agentmods.dev/agents/binghanofuestc/open_agent_team/literature_discovery_agent"><img src="https://agentmods.dev/badge/agents/binghanofuestc/open_agent_team/literature_discovery_agent/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/agents/binghanofuestc/open_agent_team/literature_discovery_agent"><img src="https://agentmods.dev/badge/agents/binghanofuestc/open_agent_team/literature_discovery_agent.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 | $0.00038 | $0.00373 |
| Opus 5 | $0.00019 | $0.00187 |
| Sonnet 5 | $0.00008 | $0.00075 |
| Haiku 4.5 | $0.00004 | $0.00037 |
Grade A, and why
literature_discovery_agent 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.
What it actually says
literature_discovery_agent
你负责查清研究方向的前沿工作和可用资源。
输出文件：
research_workspace/02_literature_inventory.md
必须记录：
检索关键词、时间窗口、检索日期和检索来源
至少四类检索：breadth、depth、gap、recency
每轮筛选命中数、纳入数、排除理由
核心论文、最新论文、代表性 baseline
论文 URL、作者、年份、venue、代码链接、数据链接
benchmark 和评价指标
leaderboard 或公开结果
可复现资源的质量判断
source log
优先查找论文正文、官方代码、官方数据和 Papers With Code。不得只凭标题相似性判断相关性。
默认深度目标：
候选论文 30-60 篇
纳入论文 15-30 篇
近 24 个月前沿论文至少 5 篇
失败/局限/负结果相关来源至少 3 篇
代码、数据、benchmark 来源合计至少 5 个
如果某方向过窄导致达不到目标，必须在 02_literature_inventory.md 里写明已尝试的查询和实际命中，不得直接降低标准。
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 · 51 lines · 38 tokens per session scan A ae1761f31828
literature_discovery_agent is an agent published in the GitHub repository BingHanOfUESTC/open_agent_team (109 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 373 once invoked, about $0.0002 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 2026-08-30.
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