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 Lolaplex/agents-memory --skill memory-syncgit clone --depth 1 https://github.com/Lolaplex/agents-memoryWrote 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/lolaplex/agents-memory/memory-sync)<a href="https://agentmods.dev/skills/lolaplex/agents-memory/memory-sync"><img src="https://agentmods.dev/badge/skills/lolaplex/agents-memory/memory-sync/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/lolaplex/agents-memory/memory-sync"><img src="https://agentmods.dev/badge/skills/lolaplex/agents-memory/memory-sync.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 | $0.00067 | $0.01963 |
| Opus 5.5 | $0.00027 | $0.00785 |
| Sonnet 5.5 | $0.00013 | $0.00393 |
| Haiku 4.5 | $0.00007 | $0.00196 |
Grade A, and why
memory-sync 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memory-sync
Local markdown memory. Not cloud.
Paths
User memory: ~/.agents/memory. Project memory: <repo>/.agents/memory.
| File | What |
|---|---|
~/.agents/memory/USER.md |
Identity, talk style, stack, ALWAYS/NEVER |
~/.agents/memory/PROJECTS.md |
slug / path / role / stack / status |
~/.agents/memory/concepts/ |
Ideas |
~/.agents/memory/entities/ |
Named things |
~/.agents/memory/workflows/ |
Procedures |
~/.agents/memory/projects/<slug>/ |
Link to a real tree (not a second copy) |
~/.agents/memory/notes/<collection>/ |
Personal notes. Guide: projects, interests, education, finance, family, preferences, programming, work, certifications, scratch — not a closed set |
<repo>/.agents/memory/staging/ |
Inbox only (captured.md, from-chats.md). Distill, then empty. |
<repo>/.agents/memory/ |
research (input); plans/ tasks/ waves/ roadmap/ decisions/ as 001-topic.md; notes/proposed|implemented|rejected/<class>/ |
~/.agents/AGENTS.md |
Canonical always-on (USER + PROJECTS). CLAUDE.md is bound to it. |
~/.agents/memory/chats-index.md |
Chat title catalog |
~/.agents/memory/scan.json |
Roots, ignore list (includes .agents, .cursor), agent rule name |
~/.agents/rules/*.mdc |
Personal always-on rules (canonical). Sync binds them into ~/.cursor/rules/. Example: run-commands.mdc |
MCP server agents-memory: see abi/MCP.md. CLI/injection: python -m agents_memory --help-json.
When this skill fires
- User asks for Bestandaufnahme / inventory / memory sync / Projekte updaten
- User asks about cloud sync, VPS assistant memory, or multi-device status
- User (or you) created a new folder under a
scan.jsonroot - A path in
PROJECTS.mdis wrong or missing - After editing
USER.mdorPROJECTS.mdby hand → alwayspython -m agents_memory sync
Cloud mirror sync
Cloud = source of truth; local files = working copy. All MCP tools run locally; push/pull syncs a mirror bundle — see abi/REMOTE.md.
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.
- 10d ago Changed 86fd8b1fb52b
- 1mo ago Changed · +19 lines f51ddf914121
- 1mo ago Changed f5be61c9623c
- 1mo ago Changed · +1 lines 3441fcc7e076
- 1mo ago First seen · 87 lines · 67 tokens per session scan A 7f632a14a2db
memory-sync is a skill published in the GitHub repository Lolaplex/agents-memory (5 stars, last pushed yesterday), licensed MIT. It adds 67 tokens to every session and 1,963 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
On_Board
Skill "On_Board" from swisspra/On_Board, covering greetings agents!, welcome on board — agent shared memory skill.md, ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━, drop into any project that uses on board mcp and via native instruction file system.
context-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
agent-memory-discipline
Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.
memory
Persist and retrieve agent memory across sessions — recall via the three-stage protocol (structure route → semantic search → navigation fallback), read via memoryload, see the wiki structure via memorybrowse, write well-placed pages via memorywrite (including section-level append/rewrite), maintain via memorycurate.…
memory-dream
Curate the workspace memory wiki as its appointed orchestrator. Trigger on a Cloud-scheduled Dream task or a user's direct curation request. Inspect candidates for orphan leaves, near-duplicates, stale pages, remote conflicts and oversized hubs; browse the graph, cluster leaves into INDEX/hub/leaf structure, maintain…
conversation-compaction
Produce the SESSION PROJECTION of memory for an aging conversation slice. Runs as a single background model call (mirroring the memory extract hook) with NO live memory tools — durable capture to memory is extract's job. You MATCH the slice's durable facts to the memory pages you're handed (recall-found ) and emit…