mnemon

mnemon is a skill for Claude Code, Codex from mnemon-dev/mnemon. It costs 29 tokens per session (1,165 once invoked), scanned A, original, Apache-2.0.

A persistent memory tool that stores and recalls project context, decisions, and useful insights across conversations.

In plain words
What is it for?
It is for recalling relevant past context before answering and saving durable decisions or observations afterward.
Why use it?
It reduces the need to repeat important background when work continues in a later session.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for recalling relevant past context before answering and saving durable decisions or observations afterward.

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Install with agentmods
npx agentmods add skills/mnemon-dev/mnemon/container
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.

Any agent
npx skills add mnemon-dev/mnemon --skill container
Clone the repo
git clone --depth 1 https://github.com/mnemon-dev/mnemon

Made for: Claude Code, Codex.

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 mnemon

README.md
[![agentmods](https://agentmods.dev/badge/skills/mnemon-dev/mnemon/container/github.svg)](https://agentmods.dev/skills/mnemon-dev/mnemon/container)
Your own site
<a href="https://agentmods.dev/skills/mnemon-dev/mnemon/container"><img src="https://agentmods.dev/badge/skills/mnemon-dev/mnemon/container/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for mnemon

Your own site · 80×15
<a href="https://agentmods.dev/skills/mnemon-dev/mnemon/container"><img src="https://agentmods.dev/badge/skills/mnemon-dev/mnemon/container.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,165 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00029 $0.01165
Opus 5.5 $0.00012 $0.00466
Sonnet 5.5 $0.00006 $0.00233
Haiku 4.5 $0.00003 $0.00117

Measured 1mo ago against content hash 6a41a8125d85, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

mnemon 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 1mo 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.

internal/memory/setup/assets/nanoclaw/container-skill.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

mnemon — Persistent Memory

Memory Stores

  • Private (default): Per-group, read-write. All writes go here.
  • Global: Shared across all groups, read-only. Use --store global --readonly to query.

Recall — before responding

Default: recall on every new user message, unless ALL of these apply:

  • Direct follow-up within a topic already fully in context
  • No reference to past sessions, decisions, or preferences
  • No knowledge dependency beyond the current conversation

To recall:

mnemon recall "<query>" --limit 5
# Also check shared knowledge:
mnemon recall "<query>" --store global --readonly --limit 5

Craft a focused, keyword-rich query — do not pass the raw user prompt.

Remember — after responding

Run this decision tree after every substantive response:

Step 1 — Does this exchange contain any of these? a) User directive — preference, decision, correction, explicit "remember this" b) Reasoning conclusion — non-trivial judgment from multi-source synthesis c) Durable observed state — system fact, environment detail, architectural finding → No to all → STOP.

Step 2 — Does a highly overlapping memory already exist? → Yes, incremental new info → STORE the new content; review the existing memory separately → Yes, but contradicts/supersedes → STORE and verify the new fact; explicitly forget the old ID only if superseded → No significant overlap → CREATE

Step 3 — Is it worth storing? Rebuilding from scratch costs more than storing + recalling?

  • Single-query public facts → No
  • Multi-source synthesis with non-obvious conclusions → Yes
  • User-specific context no search engine can recover → Yes → No → STOP.

What to store: conclusions and user-specific context, not raw facts.

Workflow

  1. Remember: mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent
    • Only exact content repeats are skipped; distinct content is stored and diff suggestions are advisory.
    • To retire a superseded memory, store and verify the new fact, then explicitly run mnemon forget <old-id>.
    • Output includes action (added/skipped), semantic_candidates, causal_candidates.
  2. Link (evaluate candidates from step 1 — use judgment, not mechanical rules):
    • Review causal_candidates: does a genuine cause-effect relationship exist? causal_signal is regex-based and prone to false positives — only link if the memories are truly causally related.
    • Review semantic_candidates: are these memories meaningfully related? High similarity alone is not sufficient — skip candidates that share keywords but discuss unrelated topics.
    • Syntax: mnemon link <id> <candidate> --type <causal|semantic> --weight <0-1> [--meta '<json>']
  3. Recall: mnemon recall "<query>" --limit 10

Read the full file on GitHub · 105 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. 1mo ago Changed · +18 lines 6a41a8125d85
  2. 1mo ago First seen · 87 lines · 29 tokens per session scan A 9dd3a80a36a5

Subscribe to this mod's changes

mnemon is a skill published in the GitHub repository mnemon-dev/mnemon (641 stars, last pushed today), licensed Apache-2.0. It adds 29 tokens to every session and 1,165 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.

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