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 find-skillgit 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/find-skill)<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/find-skill"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/find-skill/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/find-skill"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/find-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00062 | $0.01251 |
| Opus 5 | $0.00031 | $0.00626 |
| Sonnet 5 | $0.00012 | $0.00250 |
| Haiku 4.5 | $0.00006 | $0.00125 |
Grade A, and why
find-skill 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
技能搜索 (find-skill)
智能搜索可用技能：当用户需要某个分析功能但不确定有没有现成技能时，自动搜索239个内置技能+外部蓝图，找到最匹配的并推荐安装。
适用场景
- 用户说"有没有XXX的技能/方法/分析"时，自动触发
- 用户在做分析时需要某个特定方法，但不确定技能库里有没有
- 用户想浏览某个研究方向有哪些可用技能
- agent 在执行任务时发现需要某个未安装的技能
触发条件
当用户消息包含以下模式时自动触发：
- "有没有XXX的技能"
- "找XXX技能"
- "需要XXX技能"
- "有没有XXX分析"
- "什么技能可以用"
- "find skill" / "skill search"
工作流程
- 搜索：调用
search_skills工具，输入用户关键词，搜索内置239个技能 + 外部蓝图 - 展示：将搜索结果按相关度排序，展示给用户
- 推荐：如果找到高度匹配的技能，用
ask_choice让用户选择是否安装 - 安装：用户确认后调用
install_skill自动安装
使用示例
用户主动触发
用户: 有没有做细胞通讯的技能？
→ find-skill 搜索 "细胞通讯"
→ 找到: cellchat, nichenet, liana 等3个技能
→ 推荐最匹配的 cellchat，询问是否安装
→ 用户确认 → 自动安装
Agent 内部触发
用户: 帮我做轨迹分析
→ agent 执行分析时需要 monocle3
→ find-skill 搜索 "monocle3"
→ 找到: monocle3 技能
→ 自动安装并继续分析
与其他技能的链路
- chains_to:
install_skill,search_skills,skill_hub - 安装完成后，技能自动注册到 agent 的可用技能列表
Proven Scripts
| Species | Tissue | Condition | Date | Score |
|---|---|---|---|---|
| (none yet) |
🗣️ 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 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（如分辨率 0.4 vs 0.6 vs 0.8）
- 结果可能受方法选择影响时（如不同注释方法给出不同结果）
- 生物结论需要验证可靠性时
- QC 阈值不确定时（如 MT% 阈值 10% vs 15% vs 20%）
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
1 file 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 · 110 lines · 62 tokens per session scan A 7cc32454696d
find-skill is a skill published in the GitHub repository GGbond-bo/MemOmics-Agent (19 stars, last pushed 2d ago), licensed MIT. It adds 62 tokens to every session and 1,251 once invoked, about $0.0003 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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