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/gaooooosh/limem-agent-plugin/limem.pausenpx skills add gaooooosh/limem-agent-plugin --skill limem.pausegit clone --depth 1 https://github.com/gaooooosh/limem-agent-pluginWrote 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/gaooooosh/limem-agent-plugin/limem.pause)<a href="https://agentmods.dev/skills/gaooooosh/limem-agent-plugin/limem.pause"><img src="https://agentmods.dev/badge/skills/gaooooosh/limem-agent-plugin/limem.pause.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 | $0.00058 | $0.00407 |
| Opus 5 | $0.00029 | $0.00204 |
| Sonnet 5 | $0.00012 | $0.00081 |
| Haiku 4.5 | $0.00006 | $0.00041 |
Grade A, and why
limem.pause 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 3d 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
/limem.pause — 暂停 LiMem 召回与采集
何时调用
- 用户明确说"暂停 LiMem"、"关掉记忆 30 分钟"、"先别召回了"
- 用户在做大量实验性输入，不希望污染被动学习采集
- 默认 duration 为 60m；支持
30m/2h/until-session-end（后者传 0）
处理步骤
- 解析 duration（args[0] 或 "$1"）：
- 形如
30m/2h→ 转为秒 until-session-end→ 传 0- 缺省 → 3600（1 小时）
- 形如
- 调 MCP
limem_pause工具，参数：{"duration_seconds": <计算后秒数>, "scope": "project", "session_id": "<当前 session 若知>"} - 回执：
⏸ LiMem 已暂停 30 分钟。期间所有 hook 不再注入记忆，也不会写 events.ndjson。 恢复：等过期 / 或 `/limem.resume`
注意
- 暂停期间用户输入完全不会被被动学习器采集（events.ndjson 也不写）
- 暂停状态写在
~/.cache/limem/pause.json，daemon 死透时 hook 仍能读到
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.
- 3d ago First seen · 36 lines · 58 tokens per session scan A ff2ca57e8356
limem.pause is a skill published in the GitHub repository gaooooosh/limem-agent-plugin (2 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 407 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…