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.feedbacknpx skills add gaooooosh/limem-agent-plugin --skill limem.feedbackgit 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.feedback)<a href="https://agentmods.dev/skills/gaooooosh/limem-agent-plugin/limem.feedback"><img src="https://agentmods.dev/badge/skills/gaooooosh/limem-agent-plugin/limem.feedback.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 5.1 | $0.00059 | $0.00257 |
| Opus 5 | $0.00030 | $0.00129 |
| Sonnet 5 | $0.00012 | $0.00051 |
| Haiku 4.5 | $0.00006 | $0.00026 |
Grade A, and why
limem.feedback 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.
What it actually says
/limem.feedback — 把"用户对刚才回答的纠正"固化
与 /limem.remember 几乎相同，区别：
mem_type固定为"feedback"- 默认 scope=project（feedback 通常是项目内的纠正）
- 模型应在 entities 里至少给出1 个 forbidden 实体（描述"不要这么做的事"），尽量也给 1 个 preferred（"应该改成什么"）
调用 MCP limem_write 时把 mem_type="feedback"、importance=0.85、detail 字段填上 "对上一次回答的纠正" 提示。
调用语法
- Claude Code:
/limem.feedback <text> - Codex:
$limem.feedback <text>
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 · 23 lines · 59 tokens per session scan A 522f082edae6
limem.feedback is a skill published in the GitHub repository gaooooosh/limem-agent-plugin (2 stars, last pushed 3mo ago), licensed MIT. It adds 59 tokens to every session and 257 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.
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