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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/zts212653/clowder-ainpx agentmods add skills/zts212653/clowder-ai/memory-navigationWrote 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/memory-navigation)<a href="https://agentmods.dev/skills/zts212653/clowder-ai/memory-navigation"><img src="https://agentmods.dev/badge/skills/zts212653/clowder-ai/memory-navigation/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/zts212653/clowder-ai/memory-navigation"><img src="https://agentmods.dev/badge/skills/zts212653/clowder-ai/memory-navigation.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 | $0.00125 | $0.01433 |
| Opus 5.5 | $0.00050 | $0.00573 |
| Sonnet 5.5 | $0.00025 | $0.00287 |
| Haiku 4.5 | $0.00013 | $0.00143 |
Grade A, and why
memory-navigation 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 1mo 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memory-navigation
记忆系统三入口路由决策 + 噪音控制 + 加载时机。F188 Phase F (AC-F6) 配套 skill。
单一真相源:
../.cat-cafe-shared-refs/memory-routing-partial.md
When to load
按 cold-start 关键词 + 检索 fallback 信号加载:
- 接到任务感觉"没先验"——不知道找什么 keyword
- 压缩后需要重建上下文(hook 触发"compact"事件)
- "我记得最近讨论过 X" / "好像之前提过" / "最近发生了什么"
search_evidence多次 low_hit 或 no_match 后- 处理新 thread 的 cold-start,需要快速建立上下文
Not for:
- 已经有精确 anchor 想直接 Read 源文件 → 直接 Read
- 代码符号查找 →
Grep/ LSP - 全文匹配 →
Grep
三入口决策树
开工 / 接到任务 / 压缩恢复
↓
我知道精确 anchor (F186/ADR-019 等)?
├─ 是 → graph_resolve(anchor, depth=1)
│ 看 anchor 周边的引用、wikilink、F-ref 关系
│
└─ 否 ↓
我大概知道找什么、有概念关键词?
├─ 是 → search_evidence(query, mode="hybrid")
│ 语义召回;low-hit 时会自动 nudge 你试其他入口(KD-7)
│
└─ 否 ↓
我只是想"扫一眼最近发生什么"?
├─ 是 → list_recent(scope="all", since="7d")
│ 不带 query,按时间倒序看最近活动
│
└─ 否 → 用 cross-cat-handoff 找人问,或问operator澄清需求
噪音控制
graph_resolve 边爆炸防护:
depth: 默认 1,上限 3。深度 ≥2 时 fan-out 容易上百relations: filter 子集- 只看强关系:
["wikilink", "doc_link"] - 只看 F-编号引用:
["feature_ref"] - 只看 frontmatter related:
["related_to"]
- 只看强关系:
- 候选列表 ≥5 项时:先选高 confidence anchor 看一跳,再决定深挖
list_recent 时间窗口选择:
- 压缩恢复 / "最近发生什么":
since="24h"或"7d" - 周回顾 / 找一周前的讨论:
since="7d" - 找最近 PR / merge:
scope="docs"+since="3d" - 完全没头绪:
scope="all"+since="7d"+limit=20
search_evidence mode 速查(详见 CLAUDE.md 「检索策略」段):
- 精确 ID →
lexical - 日常用 →
hybrid - 跨语言 →
semantic
7-tool family 互相 cross-reference
每个工具的 description 互相指向(4.6 review #3 缓解工具数量膨胀):
search_evidence— semantic / fuzzy findgraph_resolve— precise anchor / relationslist_recent— zero-prior / scan recentlist_session_chain— 看完整对话链read_session_digest— 看会话摘要read_session_events— 看会话事件read_invocation_detail— 看单次 invocation 全事件
关键纪律
search_evidence不是默认万能——历史 hook 只提它是 one-trick legacy。三入口按场景选才是 Phase F 设计。- 看到 search_evidence payload 的 🧭 Memory navigation nudge——这是低命中信号,立刻试 graph 或 recent,不要继续盲搜。
- 猫的认知成本来自"工具间互相找"而非"工具总数",cross-reference 直接解决。
- 没有 anchor 就走 recent——比反复构造关键词 prompt search 高效。
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.
- 1mo ago First seen · 128 lines · 125 tokens per session scan A 949d569085ec
memory-navigation is a skill published in the GitHub repository zts212653/clowder-ai (3,471 stars, last pushed today), licensed MIT. It adds 125 tokens to every session and 1,433 once invoked, about $0.0005 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 2026-08-30.
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