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Developer Tools

Dory-Proof Memory System skill for OpenClaw

⬇ 3.3K downloads ★ 4 stars Version 1.0.0 Rank #3017 of 10,000+

What this skill does

File-based memory system for AI agents that forget between sessions. Implements the "Dory-Proof" pattern for continuity across context resets. Use when setting up agent memory, building workspace structure, implementing task tracking, or preventing context-loss errors. Triggers on "memory system", "remember between sessions", "Dory pattern", "agent continuity", or "workspace setup".

The Dory-Proof Memory System skill is part of the Developer Tools category — developer tools that help your agent write, review, debug, and ship code. You can install it on its own or alongside other developer tools skills from the OpenClaw catalog.

The Dory-Proof Memory System skill is ranked #3017 by downloads in the OpenClaw skill catalog (3.3K total downloads, 4 stars). It belongs to the Developer Tools category alongside 3540 other top-10000 skills.

How to install the Dory-Proof Memory System skill

The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:

  1. Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
  2. Open the in-app Skills panel.
  3. Search for dory-memory and click Install.
  4. The skill activates automatically when an incoming message matches its description.

Install from the command line

If you already run the OpenClaw CLI, add the Dory-Proof Memory System skill with a single command:

openclaw skills add dory-memory

This pulls dory-memory from ClawHub and installs it into ~/.openclaw/skills/dory-memory/. Restart the OpenClaw gateway afterwards so the new skill is discovered.

How to use the Dory-Proof Memory System skill

Once installed, the Dory-Proof Memory System skill activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.

Manual install (advanced)

If you prefer manual installation:

  1. Click the Download skill .zip button above to grab dory-memory-1.0.0.zip directly from our S3 mirror.
  2. Unzip into ~/.openclaw/skills/dory-memory/ (create the directory if it does not exist).
  3. Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.

Frequently asked questions

How do I install Dory-Proof Memory System?

Install Dory-Proof Memory System in the OpenClaw Easy desktop app by opening the Skills panel, searching for dory-memory, and clicking Install. From a terminal you can run: openclaw skills add dory-memory. Either way the skill is placed in ~/.openclaw/skills/dory-memory/.

Is the Dory-Proof Memory System skill free?

Yes. It is free to download and run through ClawHub, with no account or payment required. Each skill is published by its own author under its own licence — see its ClawHub page for the licence and source.

What does Dory-Proof Memory System do?

File-based memory system for AI agents that forget between sessions. Implements the "Dory-Proof" pattern for continuity across context resets. Use when setting up agent memory, building workspace structure, implementing task tracking, or preventing context-loss errors.

Related: more developer tools skills

If the Dory-Proof Memory System skill looks useful, you may also want to check out other developer tools skills in the OpenClaw catalog:

Skills in this catalog are community-contributed integrations published on ClawHub and distributed under their own open-source licences. Product and company names, and any third-party service a skill connects to, are trademarks of their respective owners; a listing here does not imply affiliation with, sponsorship by, or endorsement from them. This page does not distribute any third-party application. Rights holders can reach us at hello@openclaw-easy.com.

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Free, open-source · Apache-2.0 · Works with Claude, ChatGPT, Gemini, or local Ollama models