Thoughtprint is a sophisticated metacognitive engine that detects how users process information and reshapes AI responses to achieve perfect cognitive resonance.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install thoughtprint
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 thoughtprint 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 Thoughtprint?
Thoughtprint acts as a transparent lens between raw user input and AI output, functioning as a critical component within the ecosystem of Openclaw Skills. Unlike traditional sentiment analysis, this skill focuses on the structural mechanics of thought—analyzing linguistic signals to determine if a user prefers sequential logic, abstract principles, or rapid, action-oriented data. By identifying these cognitive fingerprints in real-time, it ensures that every response is delivered in a format that the user's mind is already prepared to consume.
This engine is designed to solve the problem of delivery friction. Even when an AI provides the correct answer, it can fail to land if the structure is misaligned with the user's mental model. Thoughtprint eliminates this barrier by serving as a skill multiplier, enhancing the effectiveness of every other tool by wrapping their outputs in a tailored cognitive frame. It creates an experience where the technology seems to inherently understand the user's inner voice without the need for manual prompting or personality typing.
Thoughtprint Use Cases
- Calibrating technical documentation for holistic versus sequential learners.
- Shifting from exploratory brainstorming to surgical debugging during high-pressure coding sessions.
- Tailoring multi-agent responses in group chats based on individual participant cognitive profiles.
- Optimizing information density for rapid decision-makers who require high-velocity insights.
- Enhancing collaborative research by matching the user's preferred level of abstraction and agency.
How Thoughtprint Works
- Scan: The engine performs a silent analysis of every incoming message, noting sentence structure, punctuation density, and specificity.
- Classify: It maps the user across six distinct cognitive axes, including Convergent vs. Divergent and Concrete vs. Abstract processing.
- Detect Drift: The system identifies shifts in the user's context or urgency, allowing the AI to pivot its delivery style mid-conversation.
- Calibrate: Using the detected pattern, Thoughtprint reshapes the response structure, adjusting tone, length, and the order of content.
- Verify: A final pre-delivery check ensures the drafted response resonates naturally with the user's detected thinking style.
Thoughtprint Setup
To integrate Thoughtprint into your existing environment, use the standard installation workflow for Openclaw Skills. This skill is designed to run as a background layer with zero configuration required for basic pattern matching.
# Install the thoughtprint skill to your local instance
openclaw install thoughtprint
# Verify the installation and active status
openclaw list --active
Once installed, the skill automatically intercepts message cycles to begin cognitive profiling without interfering with the logic of your other active tools.
Thoughtprint Data Schema & Taxonomy
Thoughtprint organizes its internal logic around a dynamic spectrum of six cognitive axes. It does not store personal data but tracks transient patterns to optimize the current session.
| Axis | Low End | High End | Primary Metric |
|---|---|---|---|
| Processing | Convergent | Divergent | Question type and choice density |
| Logic | Sequential | Holistic | Linear builds vs. systemic connections |
| Abstraction | Concrete | Abstract | Usage of code/examples vs. principles |
| Velocity | Rapid | Deliberate | Message length and grammatical care |
| Agency | Autonomous | Collaborative | Request for data vs. request for partnership |
| Intent | Builder | Debugger | Scaffolding needs vs. root cause analysis |
Thoughtprint Advanced Features
- Dynamic drift detection that resets the cognitive model when user context shifts suddenly.
- Language-agnostic pattern recognition that identifies cognitive rhythms across different dialects and languages.
- Per-message weighting that prioritizes recent interactions while maintaining a baseline profile for consistency.
- Seamless integration with other Openclaw Skills to provide a resonance-corrected delivery for complex technical outputs.
- Silent verification protocol that prevents the AI from announcing its adaptation, maintaining a natural conversation flow.
SKILL.md
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