Clowder AI is a self-hosted workspace where AI agents from different model families work together as a persistent team, retaining identities, shared evidence, and memory across tasks. It is for people who want to coordinate multiple AI agents without repeatedly rebuilding their context.
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 agentmods add skills/zts212653/clowder-ai/proactive-memory-judgmentnpx skills add zts212653/clowder-ai --skill proactive-memory-judgmentgit clone --depth 1 https://github.com/zts212653/clowder-aiWrote 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/zts212653/clowder-ai/proactive-memory-judgment)<a href="https://agentmods.dev/skills/zts212653/clowder-ai/proactive-memory-judgment"><img src="https://agentmods.dev/badge/skills/zts212653/clowder-ai/proactive-memory-judgment.svg" alt="Measured on agentmods" 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 | $0.00069 | $0.01391 |
| Opus 5 | $0.00034 | $0.00696 |
| Sonnet 5 | $0.00014 | $0.00278 |
| Haiku 4.5 | $0.00007 | $0.00139 |
Grade A, and why
proactive-memory-judgment 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 5d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proactive Memory Judgment
这是一道语义判断门,不是词频分类器。单次合格线索足以进入判断,不要求重复;Phase A 频率 nudge 只说明“跨 thread 出现过”,不证明重要性,也不决定 memory lane。
五道门
按顺序判断;任一道不通过,都不要把不确定内容升级成更深的 intervention。
1. 甜甜圈资格
主体必须是可命名或可消歧的第三方人物,并且当轮至少出现一种 continuity value:
- 稳定身份或 owner↔person 关系;
- 对既有记忆的纠正;
- 未来对话确实可能用到的事实;
- 值得保留的重要互动或明确 owner assessment。
裸人名 / proper noun alone、taste、背景 corpus 扫描都不是机会。workspace name、handle 或 alias 只属于 Entity;若同一句同时包含 workspace alias 与 owner-private 事实,分别走 Entity 与 F276,分别审批。
2. 证据
使用 F282 typed source bundle 与 assertion role。只让证据支持它真正能证明的字段:
- owner message 可支持
reported_fact或user_assessment; - third-party quote 保持
quoted_third_party,不得洗成 event fact; - agent inference 不得 materialize;
- 时间、headline、duration 等 interaction fields 必须有对应 typed evidence。
证据不足时不猜、不补写 owner 没说过的话;若本轮已形成 opportunity exposure,记录
cat_cafe_record_proactive_memory_abstention({ reasonCode: "insufficient_owner_evidence" })。
3. 时机
只在自然回复边界行动;同一轮至多一张 person-memory card。已有 pending 时不要制造重复卡;
需要纠正 pending 时按 F276 immutable replacement 契约提交完整新快照。人物已登记不等于没有
新关系/互动:若当前任务适合,立即提完整 delta 卡;若提卡会打断主任务且 exact owner sources
已经明确,调用 cat_cafe_defer_person_memory_delta,只传 subject、source coordinates 与稳定
clientRequestId。defer 不存正文,daily clerk 也不会扫描对话,只会把 exact refs 转回普通审批卡。
4. 授权
只能创建可拒绝的 F276 提案,不得静默物化或静默写入 canonical memory。owner 选择 exact items 后才 materialize;隐私、source scope 或权限不清时 fail closed。
5. 降档表达
不确定性越高,intervention 越浅。defer 是“证据足、人物已登记、只是当前不宜打断”,不是 证据不足的垃圾桶。确认不应 proposal/defer 时,只记录一条 enum-only abstention,不写解释、 原文、坐标或自定义 reason:
| 情形 | reasonCode |
|---|---|
| 没有 continuity value | not_continuity_valued |
| owner 证据不足 | insufficient_owner_evidence |
| 当前时机不自然且不是可安全 defer 的 known-person delta,或本轮已有卡 | bad_timing |
| 需要的授权不存在 | authorization_boundary |
| 已有 pending,或当前内容只重复既有人物事实、没有新 delta | already_registered_or_pending |
| privacy / source scope 不可确认 | privacy_boundary |
调用形式:
cat_cafe_record_proactive_memory_abstention({ reasonCode })
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.
- 5d ago First seen · 119 lines · 69 tokens per session scan A 0e3f93b6957e
proactive-memory-judgment is a skill published in the GitHub repository zts212653/clowder-ai (2,894 stars, last pushed today), licensed MIT. It adds 69 tokens to every session and 1,391 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 2026-08-30.
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