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 AbyssCN/oh-my-dag --skill omd-recallgit clone --depth 1 https://github.com/AbyssCN/oh-my-dagWrote 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/abysscn/oh-my-dag/omd-recall)<a href="https://agentmods.dev/skills/abysscn/oh-my-dag/omd-recall"><img src="https://agentmods.dev/badge/skills/abysscn/oh-my-dag/omd-recall/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/abysscn/oh-my-dag/omd-recall"><img src="https://agentmods.dev/badge/skills/abysscn/oh-my-dag/omd-recall.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 | $0.00083 | $0.00682 |
| Opus 5 | $0.00042 | $0.00341 |
| Sonnet 5 | $0.00017 | $0.00136 |
| Haiku 4.5 | $0.00008 | $0.00068 |
Grade A, and why
omd-recall 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 11d 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
/omd-recall — 主动召回记忆
封 omd MCP 的 memory_recall(可能带 mcp__omd__ 前缀;未加载先 ToolSearch "memory_recall")。它对 omd 自记忆做语义 + 词法混合检索,回一批按相关性排序、带 confidence 和 source 的命中。本 skill 是它的主动门面:卡住时你自己调,而不是等某个钩子替你触发。
何时主动召回
- 写 plan / SDD 中卡住 —— 想「以前类似的怎么决策的」;
- 设计抉择 —— 「该用 X 还是 Y」,想看历史依据再拍;
- 跨模块复用 —— 「以前哪个模块解决过类似问题」;
- 方法论 / 教训查询 —— 「我们的标准是什么」「这个坑以前踩过吗」。
用法
memory_recall(query="<自然语言或关键词>", k=5)
query用自然语言最好(检索是语义的):跨租户隔离 auth 策略优于单个词;文件名 + 关键词也行。k默认看全一点(5 左右);只要一条确认性事实就调小。- 回来是一批命中,每条带 confidence + source——不是所有命中都可信,看下一节判。
判可信度(别照单全收)
召回结果是线索不是真理,逐条自评:
- confidence 高 + source 明确(有文件/来源) → 可当依据,引用时带上 source 路径;
- confidence 低 / source 模糊 → 只当「可能相关」的提示,落到具体依据前用真源核一遍(读那个文件 / 查代码);
- 明显跑题 → 丢弃,别硬凑。
把用上的那几条回填进当前推理,并在结论里注明依据来自召回的哪条 source。
与既有 skill 的边界
/omd-recall= 卡住时主动召回既有记忆(读)。- 不用于:巩固近期事件成持久记忆(写)→
bun run scripts/omd-dream.ts(dream 管线,无 slash 入口);把新决策/引用记进台账 →/omd-note;文件内字面搜索 → 用 runtime 原生 Grep;第三方库文档 →context7MCP;git 提交历史 →git log。
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.
- 11d ago First seen · 41 lines · 83 tokens per session scan A 682909e851d1
omd-recall is a skill published in the GitHub repository AbyssCN/oh-my-dag (39 stars, last pushed 2d ago), licensed MIT. It adds 83 tokens to every session and 682 once invoked, about $0.0004 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.
Other skills, from other repositories
update-setup
A one-time setup wizard for creating a personalised upgrade guide for a workspace. It checks for an existing guide, identifies the current version and installation clues, and requires confirmation of the installation method before writing a new guide.
skill-creator
Create, edit, improve, tidy, review, audit, or restructure memmy-agent skills and SKILL.md files.
memmy-memory
Use the shared Memmy memory service to retrieve relevant prior context and persist durable Agent turns, facts, decisions, preferences, procedures, and follow-ups.
ui-craft
Design, build, redesign, or modify browser-visible web interfaces with product-quality composition, visual systems, interaction states, responsive behavior, accessibility, and browser visual QA. Use for HTML, CSS, JavaScript, React, Vue, or Svelte pages and components, landing pages, dashboards, admin tools, settings…
memmy-memory
Use the memmy-memory CLI when an agent needs to check the Memory service, open or close agent sessions, start or complete turns, search, add, read, or delete memories, or call uncommon HTTP routes through raw requests.
knowledge-base
Build and maintain a company knowledge base as a wiki of interlinked markdown notes in the workspace — a private, compounding Wikipedia. Use when the user wants to start or organize a knowledge base / wiki, ingest sources (URLs, documents, pasted notes) into it, ask questions answered from it, or audit (lint) it.…