Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
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Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Connecting a memory tool does not make an agent use it. Tools register, the session runs, and nothing gets recalled or saved. This skill supplies the missing part: standing rules for when to read memory and when to write it.
It is backend-agnostic. Everything below works the same whether memory is a folder of Markdown files, a local MCP server, or a hosted service.
Read memory before doing any of these, not after:
Do not recall for one-off factual questions, arithmetic, or anything fully specified in the current message. Recall costs a tool call and context; spending it on a self-contained question is waste.
Search with the words the user actually used, plus the project or repository name. If the first search returns nothing useful, try one broader query, then stop and proceed without memory rather than looping.
Write to memory when one of these has just happened:
Do not save: the contents of files you can read again, restatements of the current task, transient state, anything the user marked as temporary, and anything containing secrets, tokens, or personal data.
One memory, one fact. A paragraph containing four decisions cannot be superseded cleanly when one of them changes.
A memory that is useless in three weeks was written wrong. Each entry should carry, in the text if the backend has no fields for it:
Prefer the user's own words over your paraphrase. Paraphrase drifts.
When something changes, the old memory is not wrong. It is closed.
If the project moved from Redux to Zustand, "we use Redux" was true from January to June. Deleting it destroys the explanation for every component written in that window. Mark it superseded, keep its validity window, and write the new one alongside.
This is the single most destructive habit in agent memory, and it is invisible until someone asks a question about old code.
If recall returns two entries that disagree, do not pick the closer match and proceed. Surface both, with their dates, and ask or flag.
A convention that a recent failure contradicts is exactly the situation where the user needs to be told, not smoothed over.
An observation becomes policy when a human confirms it, when it lands in a merged decision record, or when it has worked repeatedly. Never promote a single observation to a rule on your own.
The user says: "stop using npm here, we're on pnpm."
Project uses pnpm, not npm. Stated by the user on 2026-08-11 after a lockfile conflict. Applies to all packages in this repo.Before acting on project-specific work: did I recall? After a decision, correction, or failure: did I save it, in one sentence, with its reason? When something changed: did I close the old entry instead of deleting it?
This skill assumes a memory tool exists. Any of these work:
memory/ folder of Markdown notes, one fact per file. No dependencies, fully greppable, versionable in git.Written and maintained by the team behind Mnemoverse, which is one hosted implementation. The rules above are deliberately backend-neutral and were written to be useful without it.
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Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Pull the ads a competitor is running right now on Meta (Facebook/Instagram) and Google, then extract the hooks, offers, CTAs and landing pages worth modelling. Use when writing ad copy, planning creative tests, choosing a landing page angle, or when the user asks "what is X advertising", "what ads does X run", "find competitor ad hooks". Reads live Ad Library and Ads Transparency data through the Tracetify MCP; falls back to a manual Ad Library walkthrough when the connector is absent.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
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Checks which private files (.env, keys, secrets) Claude Code and its subagents reached in this project, whether a value came into an agent's context, and which key to change, by running the open source agentwhy CLI over the session records Claude Code already keeps on disk. Use when the user asks whether the agent or a subagent read their .env or other secrets, which private files a session touched, whether a key leaked into the conversation, or which key to rotate. Runs locally and never prints a secret value.
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Audit whether a website can be found, crawled, and cited by AI answer engines such as ChatGPT Search, Perplexity, Google AI Overviews, and Microsoft Copilot. Use when someone asks why their brand is missing from AI answers, whether AI crawlers can read their site, how to get cited by ChatGPT or Perplexity, or asks for a GEO or AEO (generative / answer engine optimization) review. Produces a citation baseline across buyer-intent prompts, a crawler-access check, a citability review of named pages, and a ranked fix list. Not for keyword rank tracking, paid search, or pages behind a login.
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