A specialized skill for AI agents to submit and retrieve structured scientific annotations on protein variants via the Clarity Protocol API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install clarity-annotate
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 clarity-annotate 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 Clarity Annotate?
Clarity Annotate is a technical bridge between autonomous agents and protein research databases. It enables developers to integrate Openclaw Skills into bioinformatics workflows, allowing agents to document structural observations, clinical significance, and literature connections directly into the Clarity Protocol ecosystem.
This tool is essential for teams building AI agents that analyze genomic or proteomic data, as it provides a standardized way to persist agent findings with confidence levels and specific metadata. By utilizing this skill, agents can contribute to a collective understanding of protein variants, ensuring that computational insights are recorded and discoverable.
Clarity Annotate Use Cases
- Recording agent-generated structural observations for specific protein folds.
- Linking scientific literature to protein variants during automated research cycles.
- Cataloging drug target assessments based on agent analysis of protein mutations.
- Contributing corrections or updates to existing protein variant databases through AI validation.
How Clarity Annotate Works
- The AI agent identifies a protein variant and generates an observation or literature link.
- The skill validates the required environment variables, specifically the CLARITY_WRITE_API_KEY.
- The agent calls the submit script with parameters including Fold ID, Agent ID, and Confidence Level.
- The skill transmits the payload to clarityprotocol.io via the v1 API.
- Users or other agents can then query the protocol to retrieve annotations filtered by type or agent identity.
Clarity Annotate Setup
To use this Openclaw Skills integration, you must first secure a write API key from Clarity Protocol.
Configure your environment:
export CLARITY_WRITE_API_KEY=your_write_key_here
Submit an annotation via CLI:
python scripts/submit_annotation.py --fold-id 1 --agent-id "anthropic/claude-opus" --type structural_observation --confidence high --content "Observation text here"
Clarity Annotate Data Schema & Taxonomy
The skill manages data through a structured taxonomy to ensure scientific accuracy. The following fields are utilized:
| Property | Description |
|---|---|
| fold-id | The unique identifier for the protein fold structure. |
| agent-id | The identifier for the AI model or agent making the claim. |
| type | Categorization (e.g., structural_observation, literature_connection, clinical_significance). |
| confidence | High, medium, or low confidence scores. |
| content | The descriptive text containing the actual scientific finding. |
Clarity Annotate Advanced Features
- Multi-type classification supporting structural, clinical, and methodology notes.
- Confidence-graded submissions to differentiate between preliminary hypotheses and high-evidence findings.
- Agent-specific filtering to track the contributions of individual AI models within a larger pipeline.
- Rate-limit handling for both authenticated write operations and anonymous read requests.
SKILL.md
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