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 GGbond-bo/MemOmics-Agent --skill deep-researchgit clone --depth 1 https://github.com/GGbond-bo/MemOmics-AgentWrote 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/ggbond-bo/memomics-agent/deep-research)<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/deep-research"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/deep-research/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/ggbond-bo/memomics-agent/deep-research"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/deep-research.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 | $0.00024 | $0.01085 |
| Opus 5 | $0.00012 | $0.00543 |
| Sonnet 5 | $0.00005 | $0.00217 |
| Haiku 4.5 | $0.00002 | $0.00109 |
Grade A, and why
deep-research 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
深度研究
13-agent深度研究团队，系统性文献检索+综述+PRISMA。支持方法专利 prior-art 调研。
适用场景: 深度文献研究, 系统性综述, 方法专利调研, 专利空白分析
难度: advanced
触发提示: "深度调研" / "系统调研" / "专利调研" / "prior art" / "方法专利" / "可专利性"
别名: 深度研究, 文献综述, 系统性回顾, 专利调研
When to Use
适用于:
- 深度文献研究, 系统性综述
- 方法专利/软著 prior-art 调研 (跨物种比较、组学方法、可代替性评估)
- 专利空白分析 (从文献格局推断专利机会)
- 毕业/课题相关的系统性 method landscape 调研
方法专利调研流程
详见 references/patent-method-research.md。
核心策略:
- Round 1 (6-8 并行): search_knowledge + search_papers_by_context + 多角度 search_papers — 同时发出
- Round 2: download_pdf(top-5) + search_papers(refined)
- Round 3: 结构化报告 (优先级分层 + 空白分析 + 可视化总结)
专利 API 不可达时的回退: 走"文献→专利空白推断"路线 — 从论文格局识别未覆盖的方法专利机会。
Support Files
references/patent-method-research.md— 生信方法专利 prior-art 调研完整方法论scripts/run.py— 执行脚本
Proven Scripts
| Species | Tissue | Condition | Date | Score |
|---|---|---|---|---|
| (none yet) |
Common Issues
| Error | Cause | Solution |
|---|---|---|
| 专利数据库 API 全部不可达 | Google Patents/Espacenet/WIPO 限制服务器访问 | 走文献→专利空白推断路线；给用户手动检索策略 |
| Nature 系列 PDF 下载失败 | Cloudflare 反爬虫 | bioRxiv PDF 通常可下载；告知用户手动获取 |
| (accumulated from runs) |
References
- Source: MemOmics built-in
- Category: literature
- Language: Python
🗣️ 辩论机制（debate_analysis）
本 skill 在执行后，如果涉及参数选择、方法决策、结果判断等不确定环节，必须调用 debate_analysis 工具进行多角色辩论。
辩论规则
- 正方 3 位专业编辑（各自独立，互相看不到）：生物学编辑 / 统计学编辑 / 生信编辑
- 反方 4 位专业编辑（各自独立，互相看不到，也看不到正方）：生物学编辑 / 统计学编辑 / 生信编辑 / 历史经验编辑
- 裁判：看到所有 7 方论点后给出裁决 + 置信度（高/中/低）
- 上下文隔离：每个编辑是独立的 LLM API 调用，messages 只包含自己的 prompt
- 分科知识库：生物学编辑用 biology_kb / 统计学编辑用 statistics_kb / 生信编辑用 bioinfo_kb / 历史经验编辑用 history_errors
- 辩论结果自动归档到 results/.../log/debate_*.json
触发场景
- 参数选择有多个合理选项时
- 结果可能受方法选择影响时
- 生物结论需要验证可靠性时
- QC 阈值不确定时
不触发场景
- 参数有明确知识库推荐且无争议时
- 纯计算步骤（如保存文件、读取数据）
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 97 lines · 24 tokens per session scan A a8fa7bc3247c
deep-research is a skill published in the GitHub repository GGbond-bo/MemOmics-Agent (19 stars, last pushed 2d ago), licensed MIT. It adds 24 tokens to every session and 1,085 once invoked, about $0.0001 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 2026-09-03.
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