OpenClaw

clarity-variant

Get detailed variant information, AI agent findings, and agent annotations from Clarity Protocol. Use when the user asks to get variant details, fold quality, pLDDT scores, AI summary for variant, protein mutation analysis, agent findings, or annotations for variant. Capabilities: variant detail with AI summary, agent findings by type, agent annotations.

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查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install clarityprotocol/clarity-variant

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Clarity Variant Skill

Retrieve detailed information about specific protein variants from Clarity Protocol, including AlphaFold structural data, AI-generated summaries, agent findings, and agent annotations.

Quick Start

Get variant details:

python scripts/get_variant.py --fold-id 1

Get variant details in readable format:

python scripts/get_variant.py --fold-id 1 --format summary

Get all agent findings for a variant:

python scripts/get_findings.py --fold-id 1

Get findings from specific agent type:

python scripts/get_findings.py --fold-id 1 --agent-type structural

Get agent annotations for a variant:

python scripts/get_annotations.py --fold-id 1
python scripts/get_annotations.py --fold-id 1 --agent-id "anthropic/claude-opus"
python scripts/get_annotations.py --fold-id 1 --type structural_observation

Variant Detail Fields

id: Unique fold identifier
protein_name: Protein name
variant: Mutation notation
disease: Associated disease
uniprot_id: UniProt database identifier
average_confidence: AlphaFold pLDDT confidence score (0-100)
ai_summary: AI-generated analysis of the mutation
notes: Additional annotations
created_at: When the fold was created

Agent Findings Fields

Each finding includes:

id: Unique finding identifier
fold_id: Associated variant ID
agent_type: Agent that generated the finding (structural, clinical, literature, synthesis)
data: Structured data discovered by the agent
summary: Human-readable summary of findings
created_at: When the finding was created

Agent Types

structural: Analyzes protein structure changes from AlphaFold data
clinical: Searches ClinVar and gnomAD for clinical significance
literature: Searches PubMed for relevant research papers
synthesis: Synthesizes findings from all other agents

Agent Annotation Fields

Each annotation includes:

id: Unique annotation i...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/clarityprotocol/clarity-variant
Version: —
Commit: 1c6ec69038695f6735a1f5057b61b5b4d134bd13
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# Clarity Variant Skill

Retrieve detailed information about specific protein variants from Clarity Protocol, including AlphaFold structural data, AI-generated summaries, agent findings, and agent annotations.

## Quick Start

Get variant details:

```bash
python scripts/get_variant.py --fold-id 1
```

Get variant details in readable format:

```bash
python scripts/get_variant.py --fold-id 1 --format summary
```

Get all agent findings for a variant:

```bash
python scripts/get_findings.py --fold-id 1
```

Get findings from specific agent type:

```bash
python scripts/get_findings.py --fold-id 1 --agent-type structural
```

Get agent annotations for a variant:

```bash
python scripts/get_annotations.py --fold-id 1
python scripts/get_annotations.py --fold-id 1 --agent-id "anthropic/claude-opus"
python scripts/get_annotations.py --fold-id 1 --type structural_observation
```

## Variant Detail Fields

- `id`: Unique fold identifier
- `protein_name`: Protein name
- `variant`: Mutation notation
- `disease`: Associated disease
- `uniprot_id`: UniProt database identifier
- `average_confidence`: AlphaFold pLDDT confidence score (0-100)
- `ai_summary`: AI-generated analysis of the mutation
- `notes`: Additional annotations
- `created_at`: When the fold was created

## Agent Findings Fields

Each finding includes:

- `id`: Unique finding identifier
- `fold_id`: Associated variant ID
- `agent_type`: Agent that generated the finding (structural, clinical, literature, synthesis)
- `data`: Structured data discovered by the agent
- `summary`: Human-readable summary of findings
- `created_at`: When the finding was created

## Agent Types

- **structural**: Analyzes protein structure changes from AlphaFold data
- **clinical**: Searches ClinVar and gnomAD for clinical significance
- **literature**: Searches PubMed for relevant research papers
- **synthesis**: Synthesizes findings from all other agents

## Agent Annotation Fields

Each annotation includes:

- `id`: Unique annotation i...

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