agentmods.dev

memos-cloud

A skill for adding MemOS Cloud, a hosted service for storing and retrieving an app’s long-term memories and knowledge.

In plain words
What is it for?
Use it when adding memories, searching stored knowledge, using the chat interface, handling feedback or deletion, filtering results, or writing MemOS integration code.
Why use it?
It helps developers integrate memory into an app and troubleshoot the service’s API or software library.

Skill for Claude CodeCodex

1 2mo ago A scan 83 tokens original Apache-2.0
View the source file MemTensor/MemOS-Cloud-Skill
Install

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.

agentmods
npx agentmods add skills/memtensor/memos-cloud-skill/memos-cloud
Any agent
npx skills add MemTensor/MemOS-Cloud-Skill --skill memos-cloud
Clone the repo
git clone --depth 1 https://github.com/MemTensor/MemOS-Cloud-Skill

Made for: Claude Code, Codex.

Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,491 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00083 $0.01491
Opus 5 $0.00042 $0.00745
Sonnet 5 $0.00017 $0.00298
Haiku 4.5 $0.00008 $0.00149

Measured 2d ago against content hash 78f629e36494, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

memos-cloud 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/upgrade.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

memos-cloud/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MemOS Cloud

Use this skill to help users integrate MemOS Cloud into real projects. Prefer source-backed code and minimal task-specific docs over broad API summaries.

Required Workflow

  1. Run scripts/upgrade.py from this skill folder before reading resources. If network access is blocked, report that resource sync failed and continue with the bundled resources already present.
  2. Verify this skill is functional: confirm that at least resources/cn/index.md (or resources/en/index.md) exists and is readable. If the file cannot be read, stop and report a broken skill installation.
  3. Read resources/index.md and choose the resource locale:
    • Use resources/cn/index.md for Chinese user requests or Chinese product/docs work.
    • Use resources/en/index.md for English user requests.
    • If the user's language is mixed, prefer the language used for the requested deliverable.
  4. For any broad request such as "integrate MemOS", "add long-term memory", "make my Agent remember", "接入 MemOS", or "长期记忆", read the selected locale's starter-pack.md before any API reference.
  5. Use the selected locale's index.md to choose the smallest necessary resource set. Do not load every resource by default.
  6. Check environment for MEMOS_API_KEY:
    • If present and starts with mpg-: run a quick add + search verification to confirm connectivity. Show the user what was written and what was retrieved.
    • If missing or placeholder: do NOT skip. Tell the user they need to configure a Key to proceed. Provide the steps: go to https://memos-dashboard.openmem.net/cn/quickstart to get a Key, then run export MEMOS_API_KEY="mpg-...". Wait for the user to confirm the Key is set, then run verification.
    • After verification passes, report the result and STOP. Wait for user's next instruction. Do NOT inspect the project, choose integration paths, or generate any code unless the user explicitly asks.

The following steps only execute when the user explicitly requests integration code:

Read the full file on GitHub · 72 lines

Files

What ships with it

45 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.

Changes

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.

  1. 2d ago First seen · 72 lines · 83 tokens per session scan A 78f629e36494

Subscribe to this mod's changes

memos-cloud is a skill published in the GitHub repository MemTensor/MemOS-Cloud-Skill (1 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 83 tokens to every session and 1,491 once invoked, about $0.0004 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 2026-08-31.

Memory and context
Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens