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 agentmods add skills/obra/episodic-memory/remembering-conversationsnpx skills add obra/episodic-memory --skill remembering-conversationsgit clone --depth 1 https://github.com/obra/episodic-memoryWrote 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/obra/episodic-memory/remembering-conversations)<a href="https://agentmods.dev/skills/obra/episodic-memory/remembering-conversations"><img src="https://agentmods.dev/badge/skills/obra/episodic-memory/remembering-conversations.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00060 | $0.00739 |
| Opus 5 | $0.00030 | $0.00369 |
| Sonnet 5 | $0.00012 | $0.00148 |
| Haiku 4.5 | $0.00006 | $0.00074 |
Grade A, and why
remembering-conversations 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
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..."
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 80 lines · 60 tokens per session scan A 1bbb41afa737
remembering-conversations is a skill published in the GitHub repository obra/episodic-memory (470 stars, last pushed 3mo ago), licensed MIT. It adds 60 tokens to every session and 739 once invoked, about $0.0003 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.
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