remembering-conversations
obra/episodic-memory
Search past conversations before guessing—recover what was actually said and learned.
What is remembering-conversations?
This skill enables agents to search and retrieve information from historical conversations before claiming ignorance or repeating past mistakes. It supplements other memory systems by providing access to the full record of what was discussed, decided, and solved in prior interactions.
- Search past conversations by topic or query to recover decisions, patterns, and solutions
- Read and synthesize the top relevant results from historical memory
- Avoid repeating mistakes or reinventing solutions already explored
- Include source pointers so users can inspect original conversations
- Reduce context overhead by searching efficiently rather than loading raw conversations
How to install remembering-conversations
npx skills add https://github.com/obra/episodic-memory --skill remembering-conversations- episodic-memory MCP plugin installed and configured
- Access to historical conversation storage
- For Claude Code: Task tool with subagent_type support; for Codex/opencode: direct MCP tool access
How to use remembering-conversations
- 1.Before saying 'I don't know' or guessing, announce: 'Searching past conversations for [topic]'
- 2.For Claude Code: use the Task tool with subagent_type: 'search-conversations' and a specific query
- 3.For Codex/opencode: call the episodic-memory search tool, then read the top 2-5 results
- 4.Synthesize findings from retrieved conversations into your response
- 5.Include source pointers so the user can inspect original conversations if needed
Use cases
- Recalling project decisions and rationale from earlier work sessions
- Finding solutions to problems you've debugged or solved before
- Recovering established workflows or processes with known gotchas
- Answering questions about prior discussions without guessing
- Following up on incomplete tasks by retrieving context from previous conversations
- Agents that need persistent memory across multiple conversations
- Teams working on long-running projects with evolving context
- Developers debugging recurring issues or refining established processes
- Anyone who needs to avoid repeating past mistakes or decisions
remembering-conversations FAQ
Search whenever the current task may benefit from prior information: recalling decisions, finding past solutions, understanding project context, or before saying 'I don't know' about something that may have been discussed before. Don't search for current codebase structure or information already in the current conversation.
Use the Task tool with description 'Search past conversations for [topic]' and subagent_type: 'search-conversations', along with a specific prompt describing what you're looking for.
Use the MCP tools directly: call mcp__plugin_episodic-memory_episodic-memory__search to find relevant conversations, then mcp__plugin_episodic-memory_episodic-memory__read to retrieve the top 2-5 results.
Searching saves 50-100x context compared to loading raw conversations, since you retrieve only the most relevant results and synthesize them rather than loading entire conversation histories.
Synthesize findings into 200-1000 words of actionable insights, and include source pointers so the user can inspect the original conversations if they want to verify or explore further.
Full instructions (SKILL.md)
Source of truth, from obra/episodic-memory.
name: remembering-conversations description: 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.
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:
- Search with the episodic-memory
searchtool - Read the top 2-5 results with the episodic-memory
readtool - Synthesize findings in your response
- Include source pointers so the user can inspect the original conversations
The search workflow will:
- Search with the
searchtool - Read top 2-5 results with the
readtool - Synthesize findings (200-1000 words)
- 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:
- Search with the episodic-memory
searchtool - Read the top 2-5 results with the episodic-memory
readtool - Synthesize findings in your response
- 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__searchmcp__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.
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