Openclaw Skills Chat Toolkit Free helps AI agents learn and apply user communication preferences from explicit feedback, storing them locally for consistent, reusable responses.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install chat-toolkit-free
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install chat-toolkit-free using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Chat Toolkit Free?
Openclaw Skills Chat Toolkit Free is a lightweight preference-learning skill for AI agents that adapts communication style, tone, formatting, and expression based only on explicit user feedback. It follows an "explicit feedback first" approach, avoiding guesses from silence and reducing the risk of incorrect or overconfident personalization.
By storing preferences in local Markdown files, Openclaw Skills makes preference management transparent, editable, and easy to migrate across environments. The free edition is optimized for individual use cases, with a compact data model, three-stage confirmation workflow, and conflict resolution rules that prioritize the latest explicit statement.
Chat Toolkit Free Use Cases
- Long-term collaboration where an AI agent must maintain a consistent communication style
- Developer workflows that prefer concise, technical, no-fluff responses
- Marketing or operations users who want emojis used in specific contexts only
- Content creation workflows that require direct openings and topic-first responses
- Teams or individuals building a reusable preference baseline for AI-assisted work
- Situations where users want local, auditable, and revocable preference memory
- Projects that need style adaptation without cloud-side personalization
How Chat Toolkit Free Works
- The agent collects explicit user feedback about communication preferences, such as tone, formatting, emoji usage, or opening style.
- The feedback is first written to
experiments.mdas a provisional preference, rather than being immediately treated as permanent. - If the same preference is expressed repeatedly, the agent asks for confirmation before promotion.
- Confirmed preferences are moved into
memory.md, which serves as the canonical approved preference store. - If the user rejects a preference, it is moved to
rejected.mdso the agent does not suggest it again. - When conflicts appear, the most recent explicit statement takes priority, ensuring the preference set stays current and self-correcting.
- The agent reads these local Markdown files on future interactions and applies the approved preferences to response generation.
Chat Toolkit Free Setup
- Create the local preference directory on first use.
mkdir -p ~/chat-toolkit
Initialize the skill in an AI agent that supports SKILL.md-based workflows, such as Claude Code, Cursor, Codex, or Gemini CLI.
Ensure the agent has local file access for
read,write, andexecoperations if supported by your environment.Start by giving the agent an explicit preference statement, for example: "I prefer concise, technical responses without small talk."
Review the generated files to confirm the preference was staged correctly.
cat ~/chat-toolkit/memory.md
- If you want to manage preferences manually, edit the Markdown files with any editor such as VS Code or Obsidian. No API key is required because Openclaw Skills stores data locally.
Chat Toolkit Free Data Schema & Taxonomy
Openclaw Skills Chat Toolkit Free uses a simple local Markdown taxonomy under ~/chat-toolkit/:
| File | Purpose | Lifecycle |
|---|---|---|
memory.md |
Confirmed user preferences | Canonical, approved, and kept compact (recommended under 50 lines) |
experiments.md |
Unconfirmed preferences | Temporary staging area until the preference is repeated enough times and confirmed |
rejected.md |
Explicitly declined preferences | Blacklist of preferences that should not be suggested again |
Metadata and organization rules
- One preference per line for easier auditing and migration.
- Keep entries short, specific, and directly tied to communication behavior.
- Use scenario labels when needed, such as developer mode, operations mode, or content creation mode.
- Prefer explicit phrases like "use project symbols instead of paragraphs" to avoid ambiguity.
- Conflicts are resolved by recency: the latest explicit statement wins.
- The free edition does not include multi-user baseline management, version history, analytics, or automated scene switching.
Chat Toolkit Free Advanced Features
- Explicit-feedback learning that avoids inferring preferences from silence
- Three-stage confirmation flow: experiment, confirm, then store permanently
- Conflict resolution that prioritizes the most recent explicit preference
- Transparent local storage with plain Markdown files for easy inspection and migration
- Rejection memory via
rejected.mdto prevent repeated suggestions - Preference backup and sync through standard file tools such as Git or cloud drives
- Works across AI agent platforms that support local file-based skills, making Openclaw Skills easy to reuse in different environments
SKILL.md
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