sessionmem AGENTS.md

sessionmem AGENTS.md is an instructions file for Codex, OpenCode from catfish-1234/sessionmem. It costs 870 tokens per session, scanned A, original, MIT.

Project instructions for sessionmem, a persistent memory layer that saves useful context between coding sessions.

In plain words
What is it for?
Use them to start sessions with relevant memory, retrieve context during work, and store important project information afterward.
Why use it?
They describe when to recall prior context and when to save decisions or facts so important information is not lost between sessions.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/catfish-1234/sessionmem/agents-md
Clone the repo
git clone --depth 1 https://github.com/catfish-1234/sessionmem

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for sessionmem AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/catfish-1234/sessionmem/agents-md.svg)](https://agentmods.dev/instructions/catfish-1234/sessionmem/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/catfish-1234/sessionmem/agents-md"><img src="https://agentmods.dev/badge/instructions/catfish-1234/sessionmem/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 870 This file is loaded in full into every session.
When invoked 870 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00870 $0.00870
Opus 5 $0.00435 $0.00435
Sonnet 5 $0.00174 $0.00174
Haiku 4.5 $0.00087 $0.00087

Measured 3d ago against content hash 566decc8c4dc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sessionmem AGENTS.md 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 3d 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.

AGENTS.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

sessionmem: Persistent Memory

sessionmem is an MCP memory layer that persists context across sessions. It is installed and active via the sessionmem MCP server. Use its tools to recall prior context and to store important decisions, facts, and context so they're available in future sessions. The user should never have to ask you to do this. It is part of how you work in this project.

Startup

On Claude Code, prior context is injected automatically at session start by the sessionmem SessionStart hook. You do not need to fetch it yourself. Do NOT call startup_inject_memories on Claude Code: the hook already provides the injection, so calling the tool would duplicate the context (it is not even registered on Claude Code for this reason). If you do NOT see a "Relevant prior context" block at the start of the session AND the startup_inject_memories tool is available (e.g. the hook is not installed, or you are on a host without hook support), call it once before any task work, or call retrieveMemories with the current task as the query. Never inject twice if context was already provided.

When to store memories (storeMemory)

  • User makes an architectural or design decision
  • You discover a non-obvious project constraint or convention
  • A debugging session reveals an important root cause
  • User states a preference about how they want things done
  • A warning or pitfall is discovered that future sessions should know about

When to retrieve memories mid-session (retrieveMemories)

  • Before making architectural decisions (check if prior decisions exist)
  • When the user references something from a previous session
  • When working in an area of the codebase that may have stored warnings or decisions

At session end (RECOMMENDED: do this without being asked)

Before the session ends, persist what was accomplished so the next session starts informed. Store a concise summary memory (importance 7) of the key outcomes, plus any new decisions, facts, or warnings. Use batchStoreMemory to write several at once. This is what makes context survive across sessions and saves tokens later.

Read the full file on GitHub · 73 lines

Changes

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.

  1. 3d ago First seen · 73 lines · 870 tokens per session scan A 566decc8c4dc

Subscribe to this mod's changes

sessionmem AGENTS.md is an instructions file published in the GitHub repository catfish-1234/sessionmem (8 stars, last pushed 19d ago), licensed MIT. It adds 870 tokens to every session, about $0.0043 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 2026-08-31.