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 skills add mnemon-dev/mnemon --skill pigit clone --depth 1 https://github.com/mnemon-dev/mnemonWrote 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/mnemon-dev/mnemon/pi)<a href="https://agentmods.dev/skills/mnemon-dev/mnemon/pi"><img src="https://agentmods.dev/badge/skills/mnemon-dev/mnemon/pi/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.
<a href="https://agentmods.dev/skills/mnemon-dev/mnemon/pi"><img src="https://agentmods.dev/badge/skills/mnemon-dev/mnemon/pi.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00025 | $0.00914 |
| Opus 5.5 | $0.00010 | $0.00366 |
| Sonnet 5.5 | $0.00005 | $0.00183 |
| Haiku 4.5 | $0.00003 | $0.00091 |
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.
This is a copy
100% identical to mnemon — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mnemon
Workflow
- 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, andcausal_candidates.
- Link (evaluate candidates from step 1 using judgment):
- Review
causal_candidates: link only when the memories are genuinely causally related. - Review
semantic_candidates: highsimilarityalone is not enough; skip unrelated keyword matches. - Syntax:
mnemon link <id> <candidate> --type <causal|semantic> --weight <0-1> [--meta '<json>']
- Review
- Recall:
mnemon recall "<query>" --limit 10
Recall Intent
Keep focused queries and memories in their original language. When the user's
meaning is clear, choose --intent WHY (reasons), --intent WHEN (timing),
--intent ENTITY (what/who), or --intent GENERAL (neutral retrieval).
For example: mnemon recall "<query>" --intent WHY. The override works in any
language; --verbose reports
meta.intent and meta.intent_source (auto or override).
Automatic cues cover some forms in English, Mandarin Chinese (simplified and traditional), Hindi (Devanagari), Spanish, Modern Standard Arabic, French, Bengali (Bengali script), Portuguese, Indonesian (Latin script), Russian (Cyrillic), and German. Unrecognized forms use GENERAL; conflicting cues involving additional languages also use GENERAL. English/Chinese-only scoring is preserved. This is a lexical heuristic, not full language understanding. See the supported forms, script variants, and limits.
Commands
mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent
mnemon link <id1> <id2> --type <type> --weight <0-1> [--meta '<json>']
mnemon recall "<query>" --limit 10
mnemon search "<query>" --limit 10
mnemon import --dry-run <file>
mnemon import <file>
mnemon forget <id>
mnemon related <id> --edge causal
mnemon gc --threshold 0.4
mnemon gc --keep <id>
mnemon status
mnemon log
mnemon store list
mnemon store create <name>
mnemon store set <name>
mnemon store remove <name>
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.
- 1mo ago Changed · +18 lines 006b71b1602b
- 1mo ago First seen · 58 lines · 25 tokens per session scan A f1e1bf3de817
mnemon is a skill published in the GitHub repository mnemon-dev/mnemon (634 stars, last pushed 5d ago), licensed Apache-2.0. It adds 25 tokens to every session and 914 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to mnemon, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
innate-memory
Innate procedural knowledge layer for coding, debugging, and analysis sessions. ACTIVATE when: (1) user says "remember", "save", "log", "follow this rule", "don't forget", "recall", or "what did we learn"; (2) a non-obvious solution, workaround, constraint, or invariant was discovered during this session; (3) starting…
innate-memory
Innate procedural knowledge layer for coding, debugging, and analysis sessions. ACTIVATE when: (1) user says "remember", "save", "log", "follow this rule", "don't forget", "recall", or "what did we learn"; (2) a non-obvious solution, workaround, constraint, or invariant was discovered during this session; (3) starting…
kayba-ace
This skill ships learnfromtraces.py, a script that reads OpenClaw session transcripts, feeds them through the ACE learning pipeline, and writes an updated skillbook to disk.
brain-page
Operating manual for reading and writing a project's brain — every read and write goes through the bundled zero-dependency brain CLI; never hand-edit brain files. Read it before creating or modifying any page or root page.
brain-setup
Bootstrap the Open Project Brain Standard into the current project — prefer brain init (ensure BRAIN.md, scaffold empty brain brainRoot-aware, default-wire CLAUDE.md + AGENTS.md). Optionally install a pre-commit hook and a Claude Code or Codex SessionStart hook.
brain-bootstrap
Seed a freshly-scaffolded brain with real project knowledge — on an existing (brownfield) project read the code, docs, and git log to draft the six root pages and capture key historical decisions; on a near-empty (greenfield) project interview the user. Every write goes through the brain CLI. Run it after brain-setup.