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 adaptyv-apigit 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/adaptyv-api)<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/adaptyv-api"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/adaptyv-api/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/adaptyv-api"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/adaptyv-api.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 194 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 206 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 227 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 247 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00005 | $0.03015 |
| Opus 5 | $0.00003 | $0.01507 |
| Sonnet 5 | $0.00001 | $0.00603 |
| Haiku 4.5 | $0.00001 | $0.00301 |
Grade A, and why
adaptyv-api scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
resp = requests.get(f"{BASE_URL}/targets", headers=HEADERS, params={ How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⛔ MemOmics 强制规则（不可违反，优先级最高）
本 skill 已集成到 MemOmics-Agent 自进化生信分析平台。以下规则覆盖所有 Biomni 默认行为。
规则1: 拿到数据 → 必须调 search_knowledge
- 每个分析步骤写代码前，必须先调
search_knowledge(species=..., tissue=..., direction=..., query="<步骤名> 参数") - 知识库有匹配 → 用知识库的参数和模板
- 知识库无匹配 → 用 web 搜索文献，提取方法和参数，存入知识库
- 绝对不能跳过直接写代码
规则2: 7步循环（每步必须走完整循环）
1. search_knowledge 查本步骤的方法和参数
2. check_env 检查环境
3. rail_review(pre) 前置审查
4. source/import 预写脚本（禁止 inline 代码）
5. terminal 执行（分步执行，禁止 && 连接多步骤）
6. debate_analysis 多方辩论（正方/反方切断上下文独立生成 + LLM裁决）
7. rail_review(post) 后置审查
规则3: 代码分段执行 — 写一步跑一步
- ❌ 禁止一次性写完全部代码用 && 连接执行
- ✅ 必须分步：写一步 → 执行 → 检查结果 → 辩论 → 下一步
规则4: 关键参数多参数尝试 + 辩论
- 涉及数值参数时（如 resolution, n_pcs, min_features, FDR threshold等），至少尝试 2-3 个值
- 每次参数变更后调
debate_analysis辩论"这个参数合理吗？结果有没有变好？" - 辩论格式（多角色对抗 v3）：
- 正方 3 位专业编辑（各自独立，互相不知道）：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，互相不知道，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
- 裁判编辑：看到所有 7 方论点，给出裁决 + 置信度（高/中/低）
- 上下文隔离：每个编辑独立 HTTP API 调用，messages 只有自己的 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
- 不确定的参数就辩论，不要自己拍脑袋
规则5: 执行后审查
规则N: 运行记录只是参考，不能跳过审查
-
skill_evolution(action="query_logs") 返回的历史运行日志仅供参数参考
-
即使有 quality_score=9.0 的历史日志，仍必须执行 rail_review(pre)、debate_analysis、rail_review(post)
-
禁止因"之前跑过"而跳过任何审查步骤
-
禁止直接用历史日志里的脚本运行而不经本次审查
-
运行日志是"参考"不是"免审凭证"
- 图片检查：
- 图有没有生成？没生成 → 强制重新执行
- 图片是否空白（全白/全黑/全单一色）？空白 → 强制重新出图
- 图片是否有 NA/缺失值（>10% 像素是 NA）？有 NA → 强制重新出图
- 图片大小是否过小（<5KB）？过小 → 强制重新出图
- 图片数量是否足够？（每步至少 1 张图，关键步骤至少 2-3 张）
- 代码质量检查：
- 代码行数是否合理？（过短可能偷懒，过长可能未分段）
- 代码是否有注释？
- 代码是否分段执行（禁止 && 连接多步骤）？
- 结果合理性：
- 数值范围是否合理？
- 跟知识库对应吗？
- 参数和结论辩论：
- 有参数的选择 → 必须调 debate_analysis 辩论
- 有结论输出 → 必须调 debate_analysis 辩论
- 不通过 → 修复重跑
- 通过 → 必须调 skill_evolution(action="record_run") 记录成功经验（skill_name/script_name/species/tissue/direction/params_used/result_summary/quality_score/notes） → 创建目录存储(figures/results/scripts/data) → 下一步
- 不通过 → 修复后重跑 → 成功后调 skill_evolution(action="record_run")；如果是脚本报错 → 调 skill_evolution(action="record_error") 记录根因+修复方案
- 图片检查：
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 · 272 lines · 5 tokens per session scan A e6e8e5d3de2c
adaptyv-api is a skill published in the GitHub repository GGbond-bo/MemOmics-Agent (19 stars, last pushed 2d ago), licensed MIT. It adds 5 tokens to every session and 3,015 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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