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/mnemon-dev/mnemon/hermesnpx skills add mnemon-dev/mnemon --skill hermesgit clone --depth 1 https://github.com/mnemon-dev/mnemonWhat 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 | $0.00024 | $0.00446 |
| Opus 5 | $0.00012 | $0.00223 |
| Sonnet 5 | $0.00005 | $0.00089 |
| Haiku 4.5 | $0.00002 | $0.00045 |
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 2d 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.
What it actually says
mnemon
Use mnemon when durable memory can materially improve continuity across
Hermes sessions. Hooks may inject recalled context before an LLM call, but the
agent decides what is worth storing.
Workflow
- Recall when prior decisions, preferences, or facts may affect the current task:
mnemon recall "<query>" --limit 10 - Remember only stable, reusable knowledge:
mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent - Link related memories after reviewing candidates from
remember:mnemon link <id> <candidate> --type <causal|semantic> --weight <0-1>
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>
Guardrails
- Do not store secrets, passwords, tokens, private keys, or short-lived operational noise.
- Prefer concise insights over transcript dumps.
- Categories:
preference·decision·insight·fact·context - Edge types:
temporal·semantic·causal·entity - Max 8,000 chars per insight.
What ships with it
4 files 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.
- 2d ago First seen · 49 lines · 24 tokens per session scan A 12893a10946c
mnemon is a skill published in the GitHub repository mnemon-dev/mnemon (540 stars, last pushed 9d ago), licensed Apache-2.0. It adds 24 tokens to every session and 446 once invoked, about $0.0001 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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