agent-memory-onboarding

agent-memory-onboarding is a skill for Claude Code, Codex from MemTensor/memmy-agent. It costs 57 tokens per session (3,717 once invoked), scanned A, original, MIT.

A setup guide for connecting a named local software agent to Memmy, a graphical tool for managing agent history and memories. It discovers the agent’s existing history store, installs Memmy’s skill for that agent, and configures automatic syncing.

In plain words
What is it for?
Use it when Memmy needs to onboard a specific local agent. It helps import initial history, install the required extension, define where scanning starts, and confirm that the connection is usable.
Why use it?
It removes the need to add a custom parser for every kind of agent. It also verifies that the existing installation and the saved sync setup are ready for use.

Skill for Claude CodeCodex

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/memmy-agent/agent-memory-onboarding
Any agent
npx skills add MemTensor/memmy-agent --skill agent-memory-onboarding
Clone the repo
git clone --depth 1 https://github.com/MemTensor/memmy-agent

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for agent-memory-onboarding

README.md
[![agentmods](https://agentmods.dev/badge/skills/memtensor/memmy-agent/agent-memory-onboarding.svg)](https://agentmods.dev/skills/memtensor/memmy-agent/agent-memory-onboarding)
Your own site
<a href="https://agentmods.dev/skills/memtensor/memmy-agent/agent-memory-onboarding"><img src="https://agentmods.dev/badge/skills/memtensor/memmy-agent/agent-memory-onboarding.svg" alt="Measured on agentmods" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,717 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 $0.00057 $0.03717
Opus 5 $0.00028 $0.01858
Sonnet 5 $0.00011 $0.00743
Haiku 4.5 $0.00006 $0.00372

Measured 4d ago against content hash 81719d49c228, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-memory-onboarding 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 4d 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.

App/memmy-agent/src/skills/agent-memory-onboarding/SKILL.md · 302 lines

How it starts

The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Memory Onboarding

Provision an unknown local Agent at runtime without adding a framework-specific parser to Memmy. Inspect the installed Agent, install the rendered Memmy Skill through its native extension mechanism, and persist one declarative history recipe that the backend can reuse without another Agent session.

This is a button-triggered guide, not startup initialization. Run it only when the current task explicitly names $agent-memory-onboarding. The Memmy GUI creates the managed source record before launching the task. Preserve that record and its exact source_id; never create a replacement source.

Connect Success Contract

Treat operation="connect" as one provisioning transaction. Imported memories are only bootstrap and validation evidence. They do not prove that automatic scanning was installed.

Declare a connection complete only when all of these are true:

  1. verify_installation confirms an authoritative pre-existing installation, either by normalized discovered identity or by an installation path explicitly supplied by the user.
  2. The rendered Memmy Skill is installed in the active Agent surface and passes content and health checks.
  3. dataPath identifies the verified native conversation store for that same installed product surface.
  4. The initial import returns failed=0 and a non-null syncBoundaryAt.
  5. save_sync_recipe returns syncReady=true.
  6. A final get_status returns the original sourceId, status="skill_installed", the verified dataPath, a non-null syncBoundaryAt, and syncReady=true.

Do not call the task complete, say that the Agent is connected, or treat written>0 as success when any condition is missing.

Required Input

Require:

  • operation: connect, install, or uninstall
  • source_id: the exact Memmy Agent source id
  • agent_name: the framework name entered by the user
  • optional installation_path: accept it as user-provided only when the user explicitly supplied the absolute path in the conversation
  • optional data_path: a candidate only; verify it before use
  • optional WSL distribution: discover and record it when Memmy runs on Windows but the Agent surface lives in WSL

Read the full file on GitHub · 302 lines

Files

What ships with it

3 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. 4d ago First seen · 302 lines · 57 tokens per session scan A 81719d49c228

Subscribe to this mod's changes

agent-memory-onboarding is a skill published in the GitHub repository MemTensor/memmy-agent (1,190 stars, last pushed 6d ago), licensed MIT. It adds 57 tokens to every session and 3,717 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

browserwing-executor

Control browser automation through HTTP API. Supports page navigation, element interaction (click, type, select), data extraction, accessibility snapshot analysis, screenshot, JavaScript execution, and batch operations.

MemTensor/MemOS · 42 tokens

dev-browser

Browser automation with persistent page state. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website"…

MemTensor/MemOS · 84 tokens

ask-user-question

Ask users questions via the UI. Use when you need clarification, user preferences, or confirmation before proceeding. The user CANNOT see CLI output - this tool is the ONLY way to communicate with them.

MemTensor/MemOS · 44 tokens

memos-memory-guide

Use the MemOS Local memory system to search and use the user's past conversations. Use this skill whenever the user refers to past chats, their own preferences or history, or when you need to answer from prior context. When auto-recall returns nothing (long or unclear user query), generate your own short search query…

MemTensor/MemOS · 131 tokens

browserwing-admin

Manage and operate BrowserWing — an intelligent browser automation platform. Install dependencies, configure LLM, create/manage/execute automation scripts, use AI-driven exploration to generate scripts, browse the script marketplace, and troubleshoot issues.

MemTensor/MemOS · 47 tokens

safe-file-deletion

Enforces explicit user permission before any file deletion. Activates when you're about to use rm, unlink, fs.rm, or any operation that removes files from disk. MUST be followed for all delete operations.

MemTensor/MemOS · 46 tokens