Agent skill

Hermes Mnemosyne

by AtlasOmnia in AtlasOmnia/donna-starter

hermes-mnemosyne — Configure, troubleshoot, and operate the Mnemosyne memory provider for Hermes Agent.

MITAuto-check: notes

Install Hermes Mnemosyne

skills CLI
$ npx skills add AtlasOmnia/donna-starter --skill hermes-mnemosyne -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install AtlasOmnia/donna-starter hermes-mnemosyne --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/AtlasOmnia/donna-starter.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hermes/hermes-mnemosyne .claude/skills/hermes-mnemosyne && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hermes-mnemosyne
GitHub stars
126
Token cost
~3.9k tokens
SKILL.md length
1,762 words
Files
5 (incl. references)
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

hermes-mnemosyne — Configure, troubleshoot, and operate the Mnemosyne memory provider for Hermes Agent.

  • Works in 5 steps: hermes memory status reports the… → The adapter imports under the active… → Mnemosyne stats open the expected… → …
  • SKILL.md covers Quick Reference, Architecture, Consolidation (Sleep/Dreaming) and Pitfalls, plus 4 more sections
  • Calls python3; needs MNEMOSYNE_LLM_API_KEY

What it does

Hermes Mnemosyne is an agent skill from AtlasOmnia/donna-starter. hermes-mnemosyne — Configure, troubleshoot, and operate the Mnemosyne memory provider for Hermes Agent.

Its SKILL.md is about 3.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/memory-stack-migration-pilot.md`, `references/memory-tool-selection-mem0-vs-mnemosyne.md` and `references/mnemosyne-architecture.md`).

The repository describes itself as: Donna — a starter Hermes Agent profile: opinionated persona, 73 curated skills, guided first-run orientation, optional Token Router. MIT. The licence is MIT.

Example prompts

  • “/hermes-mnemosyne”

Requirements

  • Python 3
  • A credential in MNEMOSYNE_LLM_API_KEY

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. hermes memory status reports the intended provider and installed plugin.
  2. The adapter imports under the active Hermes Python environment.
  3. Mnemosyne stats open the expected database.
  4. A short memory write/recall smoke succeeds in a disposable or pilot profile.
  5. A long-running gateway is restarted only when it must load the repaired provider immediately.

What it can do on your machine

Read from SKILL.md and the folder at commit a3710bd. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • MNEMOSYNE_LLM_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hermes Mnemosyne loads about 3.9k tokens when it runs, and up to ~7.1k if it reads all its reference files. Until then it costs about 30 tokens; SKILL.md has 1,762 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~3.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:35
    | `MNEMOSYNE_HOST_LLM_ENABLED=true` in `.env` |
  • NoteMentions a .env fileSKILL.md:73
    1. Set this in that profile's `.env` **before the first memory-enabled smoke**:
  • NoteMentions a .env fileSKILL.md:81
    moves, but an absolute path embedded in `.env` does not.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AtlasOmnia/donna-starter at commit a3710bd, republished under its MIT licence (© AtlasOmnia). 1,762 words, ~3,861 tokens.

Download SKILL.mdSave it as .claude/skills/hermes-mnemosyne/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
hermes-mnemosyne
description
hermes-mnemosyne — Configure, troubleshoot, and operate the Mnemosyne memory provider for Hermes Agent.
version
1.0.0
platforms
macos, linux, windows
metadata.tags
hermes, memory, mnemosyne, consolidation, auto-sleep

Hermes Mnemosyne Memory Provider

Mnemosyne is Hermes' primary local-first memory engine — SQLite with vector + FTS5 hybrid search, 19+ tools, auto-consolidation, and a standalone CLI. It's a pip-installed plugin (not a built-in toolset) discovered via $HERMES_HOME/plugins/mnemosyne/.

Quick Reference

When comparing memory stacks for the user, use references/memory-tool-selection-mem0-vs-mnemosyne.md: Mnemosyne is preferred for Hermes local-first profile memory; Mem0 is the safer productized choice for external/customer-facing apps.

For migrations from overlapping stacks such as LCM + built-in memory + gBrain, use references/memory-stack-migration-pilot.md. Prefer a staged simplification: preserve LCM, pilot Mnemosyne as the external memory provider, keep the incumbent system read-only for rollback, and retire redundant writers after measured acceptance.

WhatHow
Check if activehermes memory status or check memory.provider in config.yaml
Memory statsmnemosyne stats (CLI) or mnemosyne_stats (tool)
Manual consolidationmnemosyne sleep (current session) or mnemosyne sleep --all-sessions
Dry-run consolidationmnemosyne sleep --all-sessions --dry-run
Enable auto-consolidationSet memory.auto_sleep: true + memory.sleep_threshold: 50 in config.yaml
Use Hermes' model for compressionMNEMOSYNE_HOST_LLM_ENABLED=true in .env
Check if installedhermes memory status; if the symlink is missing, run ~/.hermes/hermes-agent/venv/bin/mnemosyne-install

Architecture

Mnemosyne is a memory provider, not a toolset. Its tools (mnemosyne_remember, mnemosyne_recall, mnemosyne_sleep, etc.) are injected through the memory manager — they are NOT accessible via enabled_toolsets. Do NOT use enabled_toolsets: ["mnemosyne"] in cron jobs or delegation configs.

Installation path and package split

Treat Mnemosyne as two moving parts:

  • mnemosyne-memory — core memory engine and optional embedding/local-LLM extras.
  • mnemosyne-hermes — Hermes adapter/plugin package used by current upstream installation guidance.

Do not assume an older helper, package name, module path, or symlink layout is still authoritative. Before installing or repairing, check the current mnemosyne-oss/mnemosyne Hermes Plugin instructions and Hermes' live memory-provider documentation. Mnemosyne may remain an external plugin even when Hermes supports its provider interface.

If hermes memory status says Plugin: NOT installed, first inspect the active Hermes environment and plugin path. Repair using the current upstream adapter installation command, then verify.

Current wrapper-installer pitfall (mnemosyne-hermes 0.5.0): mnemosyne-hermes install --mode wrapper --force scans Hermes profiles and may create or replace profiles/*/plugins/mnemosyne links, not only the active/default profile. Before running it, inventory existing profile links and configured memory providers. Treat the profile-wide link changes as cross-profile writes: require user authorization for that scope, or audit/revert unintended links afterward. A pre-existing broken global link causes the installer to fail unless --force is supplied.

  1. hermes memory status reports the intended provider and installed plugin.
  2. The adapter imports under the active Hermes Python environment.
  3. Mnemosyne stats open the expected database.
  4. A short memory write/recall smoke succeeds in a disposable or pilot profile.
  5. A long-running gateway is restarted only when it must load the repaired provider immediately.

Hermes runtime repair or update can rebuild the virtual environment and remove externally installed packages while leaving the database intact. Therefore, verify provider status after every Hermes update rather than assuming persistence.

Database

Default: ~/.hermes/mnemosyne/data/mnemosyne.db (SQLite with vector extensions). Respects MNEMOSYNE_DATA_DIR env var.

Profile isolation must be explicit

Do not assume selecting a Hermes profile automatically gives Mnemosyne a separate database. A user-installed provider may still resolve its default through the real home directory and silently open ~/.hermes/mnemosyne/data/mnemosyne.db, even while Hermes itself uses ~/.hermes/profiles/<name>/.

For every new, cloned, or renamed profile that uses Mnemosyne:

  1. Set this in that profile's .env before the first memory-enabled smoke:
text
MNEMOSYNE_DATA_DIR=/absolute/path/to/.hermes/profiles/<name>/mnemosyne/data

Use an absolute path; dotenv consumers do not consistently expand ~. 2. Create the directory and run one short profile session. 3. Verify hermes --profile <name> mnemosyne stats reports a fresh/small store and that profiles/<name>/mnemosyne/data/mnemosyne.db exists. 4. Compare the profile-local DB path with the primary profile's DB path. Distinct session state.db files do not prove memory-provider isolation. 5. After hermes profile rename old new, rewrite MNEMOSYNE_DATA_DIR; the directory moves, but an absolute path embedded in .env does not.

If a smoke accidentally wrote to the shared store, identify the exact smoke session IDs, remove only rows scoped to those IDs, and verify zero matches remain. Never clear or replace the shared database as a shortcut.

Consolidation (Sleep/Dreaming)

Mnemosyne consolidates old working memories into episodic summaries via mnemosyne_sleep. This requires an LLM for compression. Three LLM paths exist:

  1. Local GGUF model — MiniCPM5-1B by default, cached at ~/.hermes/mnemosyne/models/. Falls back if not downloaded.
  2. Remote API — Configured via MNEMOSYNE_LLM_BASE_URL + MNEMOSYNE_LLM_MODEL + MNEMOSYNE_LLM_API_KEY.
  3. Host LLM — Uses Hermes' own model. Enable with MNEMOSYNE_HOST_LLM_ENABLED=true. This is the recommended path — no separate model needed.
Auto-sleep after validation
Auto-sleep (use only after a recall evaluation)

Current Mnemosyne 3.14.0 has an open ranking defect (mnemosyne-oss/mnemosyne#506): sleep-generated episodic summaries can enter at high tiers and crowd their source memories out of top-k recall. Do not recommend auto-sleep by default until this is fixed or the installation has a measured recall gate and a local mitigation.

Safer pilot posture:

yaml
memory:
 provider: mnemosyne
 auto_sleep: false

Before enabling it:

  1. Build a fixed query set with known expected source memories.
  2. Record top-k recall before sleep.
  3. Run a bounded/manual sleep pass.
  4. Repeat the same recall test and inspect sleep_consolidation tiers and sleep_model_refresh_proposal importance.
  5. Enable auto-sleep only if recall does not regress or a verified ranking mitigation is installed.

Host-LLM configuration remains:

MNEMOSYNE_HOST_LLM_ENABLED=true

Additional known 3.14.0 hazards:

  • #507: regex instruction extraction can turn whenever into never; audit memoria_instructions and treat those rows as session-scoped noise until fixed.
  • #524: the singular mnemosyne_invalidate tool can report success for a nonexistent ID. Prefer mnemosyne_batch invalidation or verify by exact-ID readback.
  • #525: naive local valid_until writes can disagree with SQLite UTC comparisons on non-UTC hosts.
  • #537: a Hermes managed-runtime rebuild can remove the externally installed provider; verify hermes memory status after every update and reinstall if absent.

Restart the relevant runtime after changing provider initialization settings, then verify a completed episodic write—not merely a “consolidation started” log line.

Manual sleep via CLI

The mnemosyne CLI is available in Hermes' venv:

bash
~/.hermes/hermes-agent/venv/bin/mnemosyne sleep # current session
~/.hermes/hermes-agent/venv/bin/mnemosyne sleep --all-sessions # all sessions
~/.hermes/hermes-agent/venv/bin/mnemosyne sleep --all-sessions --dry-run
~/.hermes/hermes-agent/venv/bin/mnemosyne sleep --force # skip age cutoff

Warning: --all-sessions iterates over every session with eligible memories and calls the LLM for each batch. With large databases (40K+ working memories), this can take tens of minutes and may outlive an agent/terminal timeout even while making healthy progress.

For profile-safe manual consolidation and verification of large stores, see references/profile-safe-manual-consolidation.md.

Pitfalls

DO NOT run mnemosyne tools from cron jobs

Mnemosyne's provider has _skip_contexts = {"cron", "flush", "subagent", "background", "skill_loop"}. Cron sessions set agent_context = "cron", so initialize() skips entirely — mnemosyne tools are never loaded. This is intentional: memory operations in cron contexts could race with active sessions.

Wrong:

cronjob enabed_toolsets: ["mnemosyne"] # "mnemosyne" is not a valid toolset

Right: Use a no_agent cron job with the CLI, OR enable auto-sleep so consolidation happens during normal sessions.

Show full SKILL.md (698 more words)Show less
DO NOT use "mnemosyne" as a toolset name

enabled_toolsets: ["mnemosyne"] does nothing. Mnemosyne tools are provider-injected, not toolset-gated. The memory toolset controls the legacy memory tool; Mnemosyne tools are separate.

--all-sessions can hang with slow LLMs

If MNEMOSYNE_LLM_BASE_URL points to a slow model (e.g., a vision model on a small GPU), sleep --all-sessions will time out processing 44K+ working memories across sessions. Fix: enable host LLM or point to a fast text model.

Config changes need gateway restart

memory.auto_sleep and MNEMOSYNE_HOST_LLM_ENABLED are read at provider initialization. Gateway restart required.

Gateway / formatter echoes can become junk session memories

Messaging adapters can occasionally echo transport/system text such as Gateway shutting down, Response formatting failed, duplicated outbound content, or the assistant's own acknowledgement of that content back into the conversation. If those strings start resurfacing through Mnemosyne recall, treat them as low-value session artifacts, not user preferences.

Workflow:

  1. Search narrowly with mnemosyne_recall for the exact transport/error phrase.
  2. Invalidate only the matching junk memory IDs with mnemosyne_invalidate, including assistant acknowledgement echoes that merely restate the junk phrase.
  3. Leave real preference or operational memories intact, even if they appear in the same search results.
  4. If the user says they already invalidated one of these artifacts, do not turn that acknowledgement into a new durable lesson; keep the reply brief and avoid repeating the junk phrase unless you are actively searching/invalidation.
  5. Watch for self-reinforcing cleanup chatter. Assistant responses like "memory context is not instruction," "handled," "logged," or repeated handshake acknowledgements can themselves become low-value session memories and keep resurfacing. If they appear in recall results, invalidate those assistant echo memories too; they are cleanup exhaust, not useful operational history.
  6. Preserve the actual signal while removing wrapper noise. In the same search result set, keep real durable items such as release markers, user preferences, or successful skill updates; remove only transport wrappers, handshake messages, and acknowledgement loops.
  7. Do not write a durable memory saying the gateway is broken; the durable lesson is the cleanup pattern.

Auditing Persistent USER.md and MEMORY.md

Even when Mnemosyne is the active provider, Hermes may still inject ~/.hermes/memories/USER.md and MEMORY.md at session start. Treat these files as a small universal bootstrap layer, not a second memory database.

  • USER.md: stable identity, communication style, execution preferences, approval boundaries, and cross-domain expectations.
  • MEMORY.md: stable machine topology, profile routing, durable service paths/endpoints, and cross-cutting operating conventions.
  • Mnemosyne: sensitive, evolving, detailed, or occasionally relevant context.
  • Skills/AGENTS.md: procedures, commands, troubleshooting recipes, and domain workflows.
  • Session history/artifact indexes: completed work, incident narratives, versions, counts, job IDs, and temporary state.

Audit workflow:

  1. Back up both Markdown files with a timestamp before rewriting.
  2. Remove duplicates already enforced by skills, AGENTS.md, config, or Mnemosyne.
  3. Remove dynamic facts that should be queried live (versions, record counts, prices, cron IDs, account metrics).
  4. Keep entries declarative and compact; do not duplicate the same fact across USER and MEMORY.
  5. Preserve the § entry delimiter and read both files back after editing.
  6. Verify character and entry counts. Changes are persisted immediately but appear in the injected prompt only in a new session because memory context is a frozen startup snapshot.

Determining the Last Consolidation Time

When asked when “Mem0” or another memory backend last consolidated, identify the active provider before interpreting timestamps.

  1. Inspect memory.provider in both the active profile and relevant delegated profile config.
  2. Search logs separately for Mem0 and Mnemosyne; a package refresh/install event is not a consolidation event.
  3. Use mnemosyne_stats or mnemosyne stats to distinguish:
  • working.last: latest working-memory activity, not necessarily consolidation.
  • episodic.last: latest episodic write and the strongest available evidence of completed consolidation.
  • consolidated / unconsolidated: counts, not timestamps.
  1. Treat Mnemosyne session end — running consolidation as an attempt/start marker. It does not prove completion. Timeout/deferred log lines explicitly indicate no completion in that attempt.
  2. Report stored timestamps exactly. If an ISO timestamp lacks an offset, say that the stored value is timezone-naive; report the host timezone separately rather than silently attaching it.
  3. If a requested profile cannot initialize, report that blocker and continue with direct, read-only evidence where possible—do not claim the profile performed the check.

Key Diagnostic Commands

bash
# Check if Mnemosyne is installed for Hermes
hermes memory status

# Repair missing provider symlink if CLI/database exists but Hermes says plugin NOT installed
~/.hermes/hermes-agent/venv/bin/mnemosyne-install

# Memory stats (working vs episodic)
~/.hermes/hermes-agent/venv/bin/mnemosyne stats

# Database size
ls -lh ~/.hermes/mnemosyne/data/mnemosyne.db

# Check env vars without printing secret values
python3 - <<'PY'
import os
print(sorted(k for k in os.environ if k.startswith('MNEMOSYNE')))
PY

# View memory config only
python3 - <<'PY'
import yaml, pathlib, json
cfg=yaml.safe_load((pathlib.Path.home()/'.hermes/config.yaml').read_text()) or {}
print(json.dumps(cfg.get('memory'), indent=2))
PY

Public support files

  • references/memory-stack-migration-pilot.md
  • references/memory-tool-selection-mem0-vs-mnemosyne.md
  • references/mnemosyne-architecture.md
  • references/profile-safe-manual-consolidation.md

© AtlasOmnia, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/hermes/hermes-mnemosyne of AtlasOmnia/donna-starter.

  • SKILL.md
  • references/memory-stack-migration-pilot.md
  • references/memory-tool-selection-mem0-vs-mnemosyne.md
  • references/mnemosyne-architecture.md
  • references/profile-safe-manual-consolidation.md

Open the folder on GitHubat commit a3710bd

Compare with similar skills

Hermes Mnemosyne next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hermes Mnemosyne compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hermes Mnemosyne this skillAtlasOmnia/donna-starter126—~3.9kAutomated safety check: NotesMIT
Hermes Memory Providersmnemosyne-oss/mnemosyne3.4k—~1.8kAutomated safety check: PassMIT
Hermes Importsaffaan-m/ECC277k1 repos~752Automated safety check: PassMIT
Configuration Saml Providersgreenpau/caddy-security2.3k—~1.6kAutomated safety check: PassApache-2.0
Configuration OAuth Providersgreenpau/caddy-security2.3k—~3.2kAutomated safety check: PassApache-2.0
Hermes Importsaffaan-m/ECC276k—~324Automated safety check: PassMIT

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Questions about Hermes Mnemosyne

What does Hermes Mnemosyne do?

hermes-mnemosyne — Configure, troubleshoot, and operate the Mnemosyne memory provider for Hermes Agent. Hermes Mnemosyne is an agent skill from AtlasOmnia/donna-starter. hermes-mnemosyne — Configure, troubleshoot, and operate the Mnemosyne memory provider for Hermes Agent.

How do I install Hermes Mnemosyne in Claude Code?

Run `npx skills add AtlasOmnia/donna-starter --skill hermes-mnemosyne -a claude-code`. Or copy the skill folder (skills/hermes/hermes-mnemosyne in AtlasOmnia/donna-starter) into .claude/skills/hermes-mnemosyne in your project. Claude Code loads it when a task matches its description.

How do I install Hermes Mnemosyne in Codex?

Run `npx skills add AtlasOmnia/donna-starter --skill hermes-mnemosyne -a codex`. Or copy the skill folder (skills/hermes/hermes-mnemosyne in AtlasOmnia/donna-starter) into .agents/skills/hermes-mnemosyne in your project. Codex loads it when a task matches its description.

Can I use Hermes Mnemosyne in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AtlasOmnia/donna-starter --skill hermes-mnemosyne -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hermes-mnemosyne, .gemini/skills/hermes-mnemosyne, .github/skills/hermes-mnemosyne and .opencode/skills/hermes-mnemosyne in your project.

What does Hermes Mnemosyne need to run?

Going by SKILL.md and its folder, Hermes Mnemosyne needs the command-line tools its instructions call (python3) and credentials named MNEMOSYNE_LLM_API_KEY. Our summary lists: Python 3; A credential in MNEMOSYNE_LLM_API_KEY.

Does Hermes Mnemosyne access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Hermes Mnemosyne safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Hermes Mnemosyne use?

Hermes Mnemosyne is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hermes Mnemosyne use?

About 3.9k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.3k tokens, read only when the agent opens those files.

What are the alternatives to Hermes Mnemosyne?

Skills that share tags, products or a category with Hermes Mnemosyne: Hermes Memory Providers (mnemosyne-oss/mnemosyne, 3.4k stars), Hermes Imports (affaan-m/ECC, 277k stars), Configuration Saml Providers (greenpau/caddy-security, 2.3k stars) and Configuration OAuth Providers (greenpau/caddy-security, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hermes Mnemosyne?

AtlasOmnia (a GitHub user) maintains it in AtlasOmnia/donna-starter, which has 126 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on September 19, 2026.

Source: AtlasOmnia/donna-starter on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.