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Agent skill

Mnemosyne Context

by mnemosyne-oss in mnemosyne-oss/mnemosyne

Load this when working on the mnemosyne memory system — its repo, sync server, memory databases, or CI.

MITAuto-check passedDevelopment

Install Mnemosyne Context

skills CLI
$ npx skills add mnemosyne-oss/mnemosyne --skill mnemosyne-context -a claude-code

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

GitHub CLI
$ gh skill install mnemosyne-oss/mnemosyne mnemosyne-context --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/mnemosyne-oss/mnemosyne.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/mnemosyne-context .claude/skills/mnemosyne-context && 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
mnemosyne-context
GitHub stars
3.4k
Token cost
~2.6k tokens
SKILL.md length
1,203 words
Files
1
Skills in repo
4
Repo updated
First seen
Licence
MIT

At a glance

Load this when working on the mnemosyne memory system — its repo, sync server, memory databases, or CI.

  • Any mnemosyne dev
  • SKILL.md covers Voice & conduct when acting…, Verify before trusting, Architecture (mental model) and Sync / surface model — the #1…, plus 7 more sections
  • Calls pipx, gh and git
  • A sync/import/recall behaves unexpectedly

What it does

Mnemosyne Context is an agent skill from mnemosyne-oss/mnemosyne. Load this when working on the mnemosyne memory system — its repo, sync server, memory databases, or CI. Covers architecture, the surface/sync data model, dev workflow (tests/ruff/CI matrix), release policy, and known gotchas that are easy to get wrong. Use for any "mnemosyne" dev or devops task, or when a sync/import/recall behaves unexpectedly.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Linting and formatting. It works with Ruff and GitHub. The repository describes itself as: Zero-cloud AI memory that works everywhere. SQLite-backed. One pure-Python dependency. The licence is MIT.

When your agent uses it

  • Any mnemosyne dev
  • A sync/import/recall behaves unexpectedly

Example prompts

  • “mnemosyne”
  • “/mnemosyne-context”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit bf22366. 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:

    • pipx
    • gh
    • git
    • python

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

  • Network

    No URLs in SKILL.md. Its commands use pipx, gh and git, which can reach the network depending on how they are called.

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

  • Credentials

    Names no API keys, tokens, secrets or passwords.

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

Context cost

Mnemosyne Context loads about 2.6k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 1,203 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

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 passed

The automated check found no risky patterns in SKILL.md.

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 mnemosyne-oss/mnemosyne at commit bf22366, republished under its MIT licence (© mnemosyne-oss). 1,203 words, ~2,576 tokens.

Download SKILL.mdSave it as .claude/skills/mnemosyne-context/SKILL.md (or your agent's skills folder).
name
mnemosyne-context
description
Load this when working on the mnemosyne memory system — its repo, sync server, memory databases, or CI. Covers architecture, the surface/sync data model, dev workflow (tests/ruff/CI matrix), release policy, and known gotchas that are easy to get wrong. Use for any "mnemosyne" dev or devops task, or when a sync/import/recall behaves unexpectedly.

Mnemosyne context

Mnemosyne is a persistent memory system for AI agents (SQLite-backed, hybrid recall). Repo: github.com/mnemosyne-oss/mnemosyne, owned by the user (Abdias / AxDSan). It is their repo — not a third-party fork.

Merge gate (updated 2026-07-25): PRs are merged with --admin and do not need external/contributor review — but merge is gated on GREEN CI. Never merge with failing or pending required checks; re-run flaky jobs (e.g. the temporal-recall perf gate) until green, then merge.

Voice & conduct when acting for the owner

  • On GitHub, you ARE AxDSan (the owner). Speak first-person with direct authority — "LGTM, merging.", "This breaks X, fix Y." Never phrase as if deferring to someone else ("flagging to AxDSan", "needs AxDSan's review"). There is no one above you to escalate to on this repo.
  • Verify before asserting (importance 0.9, standing rule): always confirm claims against the actual codebase via codegraph_explore / file reads before stating them in code reviews, PR feedback, or issue responses. Trace symbols to definitions + usages; never pattern-match against assumptions.
  • Architecture-first, and ship DONE work. Ask "does this need a version bump / is this the right layer?" before implementing. Deliver tested, complete implementations — not partial work.
  • Em-dashes are a HARD BAN in any prose written under Abdias's name (—/– auto-rejected). This is a personal quality standard, not a style suggestion. (Terminal/code output is exempt; this is about public-facing text.)
  • "Draft" means preview, do not send. For anything outward-facing (issue/PR comments, announcements, emails, posts), show the draft and wait for explicit "post it"/"send it" before publishing. Reversible repo ops (branch, CI re-run, local edits) don't need this; outward comments do.
  • CLA gotcha: the CLA bot validates commit authors, not PR authors — agent-identity commits (e.g. Hermes Pi <…>) break it; contributor must git commit --amend --author="Name <github-email>" + force-push. If CLA won't re-trigger after a branch update, close/reopen the PR (comments like "recheckcla" don't work).

Verify before trusting

Any point-in-time fact here (open issues/PRs, endpoints, versions) may be stale — confirm with gh, mnemosyne, or a fresh mnemosyne_recall before acting on it. The durable model + conventions below change slowly.

Architecture (mental model)

  • BEAM is the core store. Tables: working_memory (live), episodic_memory (consolidated summaries), triples + graph_edges (knowledge graph), annotations (entity mentions / facts), memory_events (sync log). Plus memoria_* tables for structured recall.
  • Recall is hybrid: vector + FTS5 + importance (+ optional temporal boost). Weights tunable per-query / via env.
  • Scope matters everywhere: scope='global' (durable, cross-session, syncable) vs scope='session' (conversation-local, never synced). Most memories are session-scoped.
  • Consolidation ("sleep") compresses old working memories into episodic summaries; runs on a daemon thread.

Sync / surface model — the #1 thing people get wrong

mnemosyne sync does NOT replicate the private DB. It replicates a shared surface: a separate, dedicated DB containing only scope='global' rows tagged with a sync_surface_id. Consequences:

  • Pointing sync at a private mnemosyne.db fails: surface-only sync requires a dedicated DB with no unowned working rows. Use a dedicated relay DB (sync-init / sync-serve --initialize-surface).
  • An empty surface → every sync reports 0. That's correct, not a bug.
  • Push is reconciliation: _discover_local_mutations() diffs the surface's working_memory against sync_memory_state → emits create/update/delete events. It does not send a hand-written event log.
  • Dedup is by event identity (event_id) + a content-hash integrity guard; INSERT OR IGNORE on the event PK + known_states check make pull/push idempotent (retry after failure re-processes the same events safely — no duplicate memories). It does NOT dedup two different events with identical text.
  • Conflicts: last-writer-wins by (timestamp → importance → device_id), with v2 causal-chain resolution via parent_event_ids.
  • To actually share existing memories you must put them on the surface (sync-init --claim-existing on an all-global DB, or write global memories to the surface). To mirror an entire DB (incl. session memories) use export/import, not sync.

Dev workflow

  • Local mnemosyne CLI + MCP server run from the pipx install (~/.local/share/pipx/venvs/mnemosyne-memory), NOT the repo. Editing the repo does not affect them unless installed editable. (Some operator deployments install it editable instead, in which case repo edits do take effect; check before assuming either.)
  • Tests: use the repo venv — .venv/bin/python -m pytest tests/<file> -q. Running from the repo dir makes import mnemosyne resolve to the repo source (shadows pipx). pytest lives in .venv, not pipx.
  • Set MNEMOSYNE_NO_EMBEDDINGS=1 for fast test runs; embedding-dependent tests are flaky because Hugging Face rate-limits (429) the BAAI/bge-small-en-v1.5 download. CI defaults to this and caches ~/.hermes/cache/fastembed.
  • tests/test_temporal_recall.py::...::test_performance_overhead is a flaky wall-clock gate (<10ms). A single-version red on it is almost always load noise — re-run the job.
  • Ruff: pinned ruff==0.15.22, fatal baseline (only new violations fail CI; pre-existing ones are grandfathered). Lint changed files ephemerally: pipx run ruff==0.15.22 check <files>.
  • CI matrix: test (3.10/3.11/3.12/3.13) + lint + build + docs-check + CodeRabbit + license/cla.
  • Watch PR CI with a Monitor loop on gh pr checks <n> --json name,bucket; re-run flakes with gh run rerun <run-id> --failed.
Show full SKILL.md (432 more words)Show less

Release policy

  • Strict SemVer from v3.1.2 onward (MAJOR=breaking, MINOR=feature, PATCH=bugfix). RELEASING.md documents it; .githooks/pre-push enforces tag format + version bump.
  • Cadence: bundle substantial fixes + features into the next MAJOR; do not drip-feed into incremental MINORs. Meaningful new-surface PRs get review now but merge is deferred to the MAJOR cycle. MINORs ship only when enough additive opt-in features accumulate.
  • Local pipx installs track PyPI releases — a merged fix isn't in your local CLI until a release ships (or you reinstall from source). Don't pipx reinstall from PyPI expecting an unreleased fix; it silently reverts it.

DevOps

The deployment topology (sync server, dashboard, bot, and the host they run on) is operator-specific and is not documented in this public repository. Hosts, addresses, service definitions and credential paths live in the operator's private runbook.

What is safe to know here: the sync server is mnemosyne sync-serve bound to loopback and reverse-proxied; it serves /sync/pull|push|status and /healthz, and it requires a dedicated relay DB rather than a private mnemosyne.db. The dashboard is a read-only UI on a separate port and is not a sync server, so pointing sync_remote at it 404s on every /sync/* route.

Contributor norms

Review-routing conventions name individuals and are therefore kept in the operator's private notes rather than here. What is safe to state publicly: the merge gate is green CI, external review is not required, and the CLA bot validates commit authors rather than PR authors.

Known gotchas / decided designs

  • Config precedence (#482): config.yaml > env > default. Runtime reads MnemosyneConfig.get() directly — no YAML→env bridge / apply_to_env(). Many config keys need a process restart to take effect.
  • No schema-level FKs (#503 closed): PRAGMA foreign_keys=ON broke 22 tests that intentionally create orphan rows. Do orphan cleanup at app level during sleep/consolidation instead.
  • Beam access is lock-serialized (#498/#520): _beam_access_lock guards Beam/SQLite between main thread and the auto_sleep daemon (a WAL checkpoint mid-statement caused a SEGV). Don't introduce unguarded cross-thread Beam access.
  • Import idempotency (#538, merged): AnnotationStore.import_all now skips (memory_id,kind,value) UNIQUE collisions instead of aborting the whole import — mnemosyne import is safely re-runnable.
  • Security: sync auth is bearer API key or JWT; a past JWT-signature-bypass was fixed — signatures are verified with hmac.compare_digest, alg pinned HS256. Sync HTTP server is off by default in the Hermes plugin.

CLI cheat-sheet

mnemosyne export [file.json] [--include-sync-events]      # read-only dump (runs on ANY arg — no --help!)
mnemosyne import <file.json> [--force]                    # merge into local DB (idempotent for memories)
mnemosyne sync --db-path <surface.db> --remote <url> --api-key-file <f> --mode bidirectional
mnemosyne sync-init --db-path <surface.db> [--claim-existing --yes]
mnemosyne sync-serve --db-path <relay.db> --host 127.0.0.1 --port <p> --api-key-file <f> [--initialize-surface]
mnemosyne sync-status --db-path <surface.db> [--remote <url>] [--api-key-file <f>] [--json]
mnemosyne config set <key> <value>                        # note: many keys need a restart

⚠️ export/remember treat --help as a positional arg (dumps / stores it). Use mnemosyne --help for the top-level list.

Code navigation

This repo is CodeGraph-indexed (.codegraph/) — prefer codegraph_explore "<symbols or question>" over grep/read for understanding or before editing; one call returns verbatim source + call paths + blast radius. Sync internals live in mnemosyne/core/sync.py, server in sync_server.py, store in beam.py, annotations/triples in core/annotations.py + core/triples.py.

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

Files

Just SKILL.md in .claude/skills/mnemosyne-context of mnemosyne-oss/mnemosyne.

Open the folder on GitHubat commit bf22366

Compare with similar skills

Mnemosyne Context 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.

Mnemosyne Context compared with similar skills
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Mnemosyne Context this skillmnemosyne-oss/mnemosyne3.4k—~2.6kAutomated safety check: PassMIT
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Minimizing Ty Ecosystem Changesastral-sh/ruff50k—~4.6kAutomated safety check: PassMIT
Kedro Babysitkedro-org/kedro11k—~4kAutomated safety check: PassCustom licence
Add Opik Code Quality Hookcomet-ml/opik22k—~2.3kAutomated safety check: PassApache-2.0
Saleor Commit Workflowsaleor/saleor23k—~575Automated safety check: PassBSD-3-Clause

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Works with

Categories

Questions about Mnemosyne Context

What does Mnemosyne Context do?

Load this when working on the mnemosyne memory system — its repo, sync server, memory databases, or CI. Mnemosyne Context is an agent skill from mnemosyne-oss/mnemosyne. Load this when working on the mnemosyne memory system — its repo, sync server, memory databases, or CI.

When should I use Mnemosyne Context?

Mnemosyne Context fits situations like: any mnemosyne dev; A sync/import/recall behaves unexpectedly.

How do I install Mnemosyne Context in Claude Code?

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

How do I install Mnemosyne Context in Codex?

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

Can I use Mnemosyne Context 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 mnemosyne-oss/mnemosyne --skill mnemosyne-context -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mnemosyne-context, .gemini/skills/mnemosyne-context, .github/skills/mnemosyne-context and .opencode/skills/mnemosyne-context in your project.

What does Mnemosyne Context need to run?

Going by SKILL.md and its folder, Mnemosyne Context needs the command-line tools its instructions call (pipx, gh, git and python). Our summary lists: Python 3.

Does Mnemosyne Context access the network?

SKILL.md contains no URLs. Its commands use gh and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Mnemosyne Context safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Mnemosyne Context use?

Mnemosyne Context 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 Mnemosyne Context use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Mnemosyne Context?

Skills that share tags, products or a category with Mnemosyne Context: Summarise Ecosystem Results (astral-sh/ruff, 50k stars), Minimizing Ty Ecosystem Changes (astral-sh/ruff, 50k stars), Kedro Babysit (kedro-org/kedro, 11k stars) and Add Opik Code Quality Hook (comet-ml/opik, 22k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mnemosyne Context?

mnemosyne-oss (a GitHub organization) maintains it in mnemosyne-oss/mnemosyne, which has 3,375 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 10, 2026.

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