Remembering Conversations

作者 obra7e0651935777无许可证487 个星标收录于 2026年10月8日更新于 2026年10月8日仓库4周前更新

You MUST invoke this skill before saying "I don't know," guessing, or treating any topic as new, no matter how trivial the question seems. It supplements other memory systems, which only hold partial records. Searching past conversations is the only way to recover what was actually said.

仅含说明AI & Agents
AI 生成的概览

引导智能体在不确定作答或重复以往工作前,先检索过去的对话记忆。

功能
这是一个仅含说明的技能,要求智能体在猜测、表示不知道或将话题视为全新之前,先检索历史对话记忆。它说明了如何派发 search-conversations 子代理,或直接调用 episodic-memory 的 search 与 read 工具,然后综合结果并附上来源指引。它还列出了适合检索的情形,以及应先查看当前代码库或当前对话的情形。
适用场景
当任务可能依赖以往工作中的决策、模式、解决方案、易错点或项目背景时使用。也适用于用户提及过去讨论、询问某项做法的原因,以及在不确定时作答之前。
运行要求
需要具备对话记忆检索能力:search-conversations 子代理,或 episodic-memory MCP 的 search 与 read 工具。该技能不附带脚本,另含可选的 MCP-TOOLS.md 参考文档。

Remembering Conversations

Core principle: Search before reinventing. Searching costs nothing; reinventing or repeating mistakes costs everything.

Mandatory: Search Historical Memory

YOU MUST search historical memory for any historical search.

Announce: "Searching past conversations for [topic]."

Claude Code

Use the Task tool with subagent_type: "search-conversations":

Task tool:  description: "Search past conversations for [topic]"  prompt: "Search for [specific query or topic]. Focus on [what you're looking for - e.g., decisions, patterns, gotchas, code examples]."  subagent_type: "search-conversations"

Codex

If a search-conversations agent is available, dispatch it with the same prompt. If not, use the MCP tools directly:

  1. Search with the episodic-memory search tool
  2. Read the top 2-5 results with the episodic-memory read tool
  3. Synthesize findings in your response
  4. Include source pointers so the user can inspect the original conversations

The search workflow will:

  1. Search with the search tool
  2. Read top 2-5 results with the read tool
  3. Synthesize findings (200-1000 words)
  4. Return actionable insights + sources

Saves 50-100x context vs. loading raw conversations.

opencode

Use the MCP tools directly unless a local search agent is available:

  1. Search with the episodic-memory search tool
  2. Read the top 2-5 results with the episodic-memory read tool
  3. Synthesize findings in your response
  4. Include source pointers so the user can inspect the original conversations

When to Use

Use this whenever the current task would benefit from information you may have learned before, even if the user did not explicitly ask you to search.

When past experience may help:

  • You need to recall decisions, rationale, patterns, solutions, pitfalls, or project context from earlier work
  • A task resembles something you've solved, debugged, reviewed, released, or planned before
  • You need to repeat a workflow or process that may have prior gotchas or established steps

When you're stuck:

  • You've investigated a problem and can't find the solution
  • Facing a complex problem without obvious solution in current code
  • Need to follow an unfamiliar workflow or process

When historical signals are present:

  • User says "last time", "before", "we discussed", "you implemented"
  • User asks "why did we...", "what was the reason..."
  • User says "do you remember...", "what do we know about..."

Before answering from uncertainty:

  • Before guessing from memory or saying "I don't know" about something that may have been learned in a past conversation, search memory unless the current conversation already answers it

Don't search first:

  • For current codebase structure (use Grep/Read to explore first)
  • For info in current conversation
  • Before understanding what you're being asked to do

Direct MCP Tool Access

Use these directly when a search agent is unavailable or the current harness does not support agent dispatch:

  • mcp__plugin_episodic-memory_episodic-memory__search
  • mcp__plugin_episodic-memory_episodic-memory__read

When using MCP tools directly, keep context small: search first, then read only the top 2-5 relevant conversations or line ranges.

See MCP-TOOLS.md for complete API reference if needed for advanced usage.

来源与署名

来源:obra/episodic-memory位于skills/remembering-conversations提交7e06519

许可证: 无许可证

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