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 debate-coregit 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/debate-core)<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/debate-core"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/debate-core/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/debate-core"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/debate-core.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 | $0.00258 | $0.03582 |
| Opus 5.5 | $0.00103 | $0.01433 |
| Sonnet 5.5 | $0.00052 | $0.00716 |
| Haiku 4.5 | $0.00026 | $0.00358 |
Grade A, and why
debate-core 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 14d 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debate Core: 何时辩、怎么辩、怎么回流
辩论是 MemOmics 的质量内核：结论、参数、可入库知识都必须过辩论。 但不是每次都辩——全量辩论有害（iMAD, AAAI 2026 Oral：选择性触发省 92% token 且准确率反升 13.5%）。用门控决定何时辩。
1. 什么时候该辩论（debate_gate 三级门控）
enforcement.py 的 debate_gate(es, stage, signals) 自动判定，返回
(level, reasons, force)：
| 级别 | 含义 | 成本 |
|---|---|---|
| L0 | 跳过（chat/lightweight 级，无分析对象） | 0 |
| L1 | 轻量（单对正反+裁判 / 3 采样投票） | ≈1/4 |
| L2 | 完整 8 角色（正方3+反方4+裁判） | 全量 |
五类触发信号（命中即升级）：
- 高影响（high_impact）：入库/报告/结论产物工具（generate_report、 save_knowledge、add_figure 等）→ 强制 L2，不可降级
- 失败（failed_retries≥2 或 last_error）：同命令重试≥2 次 → L2
- 冲突（conflict）：rail_review(post) 未通过 / 与上次结果差异大 → L2
- 不确定性（uncertainty）：候选参数≥2、措辞犹豫、自评低置信 → 结论前 L2
- 阶段（stage）：analysis 级结论合成前默认 L2；脚本设计/执行后默认 L1
级别默认值：chat/lightweight → L0（不辩）；statistical → L1； analysis → 结论前 L2、其余 L1。
1.1 P1 分情况矩阵：什么时候不值得辩（2026-09-22，反"为辩论而辩论"）
辩论的准绳只有一条：辩完必须能改变下一步动作。改变不了 → 不辩（系统会打印
执行前不辩论：<原因>，这是正常的跳过，不是失败）。_debate_worthiness(signals)
在门控前先过一层"值不值"，命中的跳过原因：
| 跳过原因 | 判据 | 为什么不懂 |
|---|---|---|
no_debate |
调用方显式 debate=False |
用户/引擎说不用辩 |
n_options<2 |
活选项 < 2（只有一个可行路径） | 没有分歧点，辩不出东西 |
fact_lookup |
事实查询（版本号/包名/路径/是什么） | 事实问题查文档，不靠投票 |
readonly |
只读操作（ls/cat/head/status/jobs/logs…） | 读一眼就知道结果 |
repeat_topic |
本会话已辩过同一 topic | 重复辩论 = 烧 token |
linear |
线性命令执行（单行 shell、无参数选择） | 没有可选方案 |
但硬信号优先于跳过（high_impact / failed_retries≥2 / last_error / conflict
四条一出，跳过规则全部让路，按强制 L2 处理）——因为这些场景里"不辩"的代价更高。
分级判据（分情况，不要一刀切）：
| 场景 | 级别 | 判据 |
|---|---|---|
| 只读 / 事实查询 / 线性执行 / 重复议题 / 活选项<2 | L0 | 辩了也改不了动作 |
| 脚本设计（首次，且脚本含可争议参数：resolution、阈值、分组列、方法选择） | L1 | 有选择但影响面小 |
| 结论合成有 ≥2 个活选项或存在不确定性 | L2 | 结论会进报告/知识库，错了代价大 |
| 结论合成无分歧（数据已指向唯一解释） | L1 | 走个证据校验 |
| 高影响（入库/报告/产物）/ 失败重试≥2 / rail_review(post) 未通过 | L2 强制，不可降级 | 硬信号 |
预算护栏：单会话辩论次数 ≥ config debate.budget（默认 3）后，
非强制 L2 自动降 L1。topic 级去重：同一主题只辩一次
（debated_topics 集合，替代旧的 debate_done 布尔）。
L2 裁判 confidence=low 且要入库 → 自动升级重辩（不可用低置信结论入库）。
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.
- 14d ago Changed · +63 lines · +120 tokens per session 6a14a2adeb51
- 1mo ago First seen · 118 lines · 138 tokens per session scan A 2195bb1c2f19
debate-core is a skill published in the GitHub repository GGbond-bo/MemOmics-Agent (30 stars, last pushed yesterday), licensed MIT. It adds 258 tokens to every session and 3,582 once invoked, about $0.0010 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 2026-09-03.
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