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Agent Memory
Command

/ask

The question to answer

BOOST
From plugin
everos
13k6 skills6 commands
Install
$ npx -y skills add evermind-ai/everos --agent claude-code

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/ask

Context preview

What this command does when you run it.

The question to answer

Command definition

ask.md
description: Ask a question about past work. Searches memories and combines with current context to answer.
arguments:
  - name: question
    description: The question to answer
    required: true

EverMem Ask

Answer a question using **both** memory search results **and** current conversation context.

Question

{{question}}

Instructions

1. **Search memories** using `evermem_search` MCP tool with relevant keywords. Start with 10 results.

2. **Evaluate results**:

  • If memories provide useful context, note what you learned
  • If more detail needed, search again with different keywords (up to 3 searches)
  • If no relevant memories found, that's OK - proceed with what you know

3. **Combine sources** to answer:

  • Memory search results (past sessions)
  • Current conversation context (this session)
  • Your general knowledge (when applicable)

4. **Be honest about sources**:

  • "Based on our discussion on [date]..." - when citing memory
  • "From our current session..." - when citing current context
  • "I don't have any recorded information about this" - when memories don't help
  • "Based on general best practices..." - when using general knowledge

5. **Admit uncertainty**:

  • If memories are incomplete or unclear, say so
  • If you're inferring rather than recalling, make that clear
  • It's better to say "I don't know" than to guess

Response Format

Start with a direct answer, then provide supporting context:

[Direct answer to the question]

**From memories:**
- [Relevant points from past sessions, with dates]

**Current context:**
- [Relevant points from this session, if any]

**Note:** [Any caveats or gaps in knowledge]

Now answer the user's question.

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One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.

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Python
Language
Apache-2.0
License
1d ago
Last commit
11mo ago
Created
11h ago
Added

Repo: evermind-ai/everos

Other commands on everos.