openbio

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

Installation

安装

bash

bunx skills add https://github.com/openbio-ai/skills --skill openbio

bash

bunx skills add https://github.com/openbio-ai/skills --skill openbio

Authentication

身份验证

Required:

OPENBIO_API_KEY

environment variable.

Tell the user to create their API key at: http://openbio.tech/profile#apikeys and securely store it in their environment variables.

If the user has not signed in to OpenBio, tell them to sign in to OpenBio (https://openbio.tech/auth) and create their account first and then create their API key.

bash

export OPENBIO_API_KEY=your_key_here

Base URL:

http://api.openbio.tech/

必填项：需设置

OPENBIO_API_KEY

环境变量。

告知用户前往http://openbio.tech/profile#apikeys创建API密钥，并将其安全存储在环境变量中。

若用户尚未登录OpenBio，请先登录OpenBio（https://openbio.tech/auth）创建账户，再生成API密钥。

bash

export OPENBIO_API_KEY=your_key_here

基础URL：

http://api.openbio.tech/

Version Check (Do This First)

版本检查（请先执行此步骤）

Before using the API, verify your skill is up to date:

bash

curl -s "http://api.openbio.tech/api/v1/tools/skill-version"

This returns

{"skill": "openbio", "version": "X.Y.Z", ...}

. Compare against the

version

field at the top of this file (currently 1.0.0). If the API returns a newer version:

bash

bunx skills update

If that fails, remove and re-install:

bash

bunx skills remove openbio --global -y
bunx skills add openbio-ai/skills --skill openbio --global --agent '*' -y

在使用API前，请确认你的skill是最新版本：

bash

curl -s "http://api.openbio.tech/api/v1/tools/skill-version"

该命令会返回

{"skill": "openbio", "version": "X.Y.Z", ...}

。将返回的版本与本文档顶部标注的版本（当前为1.0.0）进行对比。若API返回的版本更新，请执行：

bash

bunx skills update

若更新失败，请卸载后重新安装：

bash

bunx skills remove openbio --global -y
bunx skills add openbio-ai/skills --skill openbio --global --agent '*' -y

Quick Start

快速开始

bash

undefined

bash

undefined

Health check (no auth required)

健康检查（无需身份验证）

curl -X GET "http://api.openbio.tech/api/v1/tools/health"

List available tools

列出可用工具

curl -X GET "http://api.openbio.tech/api/v1/tools"
-H "X-API-Key: $OPENBIO_API_KEY"

Get tool schema (always do this first!)

获取工具架构（请务必先执行此操作！）

curl -X GET "http://api.openbio.tech/api/v1/tools/{tool_name}"
-H "X-API-Key: $OPENBIO_API_KEY"

Validate parameters before invoking (optional)

调用前验证参数（可选）

curl -X POST "http://api.openbio.tech/api/v1/tools/validate"
-H "X-API-Key: $OPENBIO_API_KEY"
-H "Content-Type: application/json"
-d '{"tool_name": "search_pubmed", "params": {"query": "CRISPR", "max_results": 5}}'

Invoke tool

调用工具

curl -X POST "http://api.openbio.tech/api/v1/tools"
-H "X-API-Key: $OPENBIO_API_KEY"
-F "tool_name=search_pubmed"
-F 'params={"query": "CRISPR", "max_results": 5}'

undefined

curl -X POST "http://api.openbio.tech/api/v1/tools"
-H "X-API-Key: $OPENBIO_API_KEY"
-F "tool_name=search_pubmed"
-F 'params={"query": "CRISPR", "max_results": 5}'

undefined

Decision Tree: Which Tools to Use

决策树：选择合适的工具

What do you need?
│
├─ Protein/structure data?
│   └─ Read rules/protein-structure.md
│       → PDB, AlphaFold, UniProt tools
│
├─ Literature search?
│   └─ Read rules/literature.md
│       → PubMed, arXiv, bioRxiv, OpenAlex
│
├─ Genomics/variants?
│   └─ Read rules/genomics.md
│       → Ensembl, GWAS, VEP, GEO
│
├─ Small molecule analysis?
│   └─ Read rules/cheminformatics.md
│       → RDKit, PubChem, ChEMBL
│
├─ Cloning/PCR/assembly?
│   └─ Read rules/molecular-biology.md
│       → Primers, restriction, Gibson, Golden Gate
│
├─ Structure prediction/design?
│   └─ Read rules/structure-prediction.md
│       → Boltz, Chai, ProteinMPNN, LigandMPNN
│
├─ Pathway analysis?
│   └─ Read rules/pathway-analysis.md
│       → KEGG, Reactome, STRING
│
└─ Clinical/drug data?
    └─ Read rules/clinical-data.md
        → ClinicalTrials, ClinVar, FDA, Open Targets

你需要什么功能？
│
├─ 蛋白质/结构数据？
│   └─ 阅读 rules/protein-structure.md
│       → PDB、AlphaFold、UniProt工具
│
├─ 文献搜索？
│   └─ 阅读 rules/literature.md
│       → PubMed、arXiv、bioRxiv、OpenAlex
│
├─ 基因组学/变异分析？
│   └─ 阅读 rules/genomics.md
│       → Ensembl、GWAS、VEP、GEO
│
├─ 小分子分析？
│   └─ 阅读 rules/cheminformatics.md
│       → RDKit、PubChem、ChEMBL
│
├─ 克隆/PCR/组装？
│   └─ 阅读 rules/molecular-biology.md
│       → 引物设计、限制性酶切、Gibson组装、Golden Gate组装
│
├─ 结构预测/设计？
│   └─ 阅读 rules/structure-prediction.md
│       → Boltz、Chai、ProteinMPNN、LigandMPNN
│
├─ 通路分析？
│   └─ 阅读 rules/pathway-analysis.md
│       → KEGG、Reactome、STRING
│
└─ 临床/药物数据？
    └─ 阅读 rules/clinical-data.md
        → ClinicalTrials、ClinVar、FDA、Open Targets

Critical Rules

重要规则

1. Always Check Tool Schema First

1. 务必先检查工具架构

bash

undefined

bash

undefined

Before invoking ANY tool:

在调用任何工具之前：

curl -X GET "http://api.openbio.tech/api/v1/tools/{tool_name}"
-H "X-API-Key: $OPENBIO_API_KEY"

Parameter names vary (e.g., `pdb_ids` not `pdb_id`). Check schema to avoid errors.

curl -X GET "http://api.openbio.tech/api/v1/tools/{tool_name}"
-H "X-API-Key: $OPENBIO_API_KEY"

参数名称各不相同（例如`pdb_ids`而非`pdb_id`）。请检查架构以避免错误。

2. Long-Running Jobs (submit_* tools)

2. 长时间运行的任务（以submit_*开头的工具）

Prediction tools return a

job_id

. Poll for completion:

bash

undefined

预测工具会返回一个

job_id

。请轮询任务状态以获取结果：

bash

undefined

Check status

检查状态

curl -X GET "http://api.openbio.tech/api/v1/jobs/{job_id}/status"
-H "X-API-Key: $OPENBIO_API_KEY"

Get results with download URLs

获取包含下载链接的结果

curl -X GET "http://api.openbio.tech/api/v1/jobs/{job_id}"
-H "X-API-Key: $OPENBIO_API_KEY"

undefined

curl -X GET "http://api.openbio.tech/api/v1/jobs/{job_id}"
-H "X-API-Key: $OPENBIO_API_KEY"

undefined

3. Quality Thresholds

3. 质量阈值

Don't just retrieve data—interpret it:

AlphaFold pLDDT: > 70 = confident, < 50 = disordered Experimental resolution: < 2.5 Å for binding sites GWAS p-value: < 5×10⁻⁸ = genome-wide significant Tanimoto similarity: > 0.7 = similar compounds

See individual rule files for detailed thresholds.

不要仅获取数据——还要对其进行解读：

AlphaFold pLDDT：>70 = 可信度高，<50 = 无序 实验分辨率：结合位点分析要求<2.5 Å GWAS p值：<5×10⁻⁸ = 全基因组显著 Tanimoto相似度：>0.7 = 相似化合物

请查看各规则文档获取详细阈值。

Rule Files

规则文档

Read these for domain-specific knowledge:

以下文档包含特定领域的知识：

Core API

核心API

File	Description
rules/api.md	Core endpoints, authentication, job management

文件	描述
rules/api.md	核心端点、身份验证、任务管理

Data Access Tools

数据访问工具

File	Tools Covered
rules/protein-structure.md	PDB, PDBe, AlphaFold, UniProt
rules/literature.md	PubMed, arXiv, bioRxiv, OpenAlex
rules/genomics.md	Ensembl, ENA, Gene, GWAS, GEO
rules/cheminformatics.md	RDKit, PubChem, ChEMBL
rules/molecular-biology.md	Primers, PCR, restriction, assembly
rules/pathway-analysis.md	KEGG, Reactome, STRING
rules/clinical-data.md	ClinicalTrials, ClinVar, FDA

文件	涵盖工具
rules/protein-structure.md	PDB、PDBe、AlphaFold、UniProt工具
rules/literature.md	PubMed、arXiv、bioRxiv、OpenAlex
rules/genomics.md	Ensembl、ENA、Gene、GWAS、GEO
rules/cheminformatics.md	RDKit、PubChem、ChEMBL
rules/molecular-biology.md	引物设计、PCR、限制性酶切、组装
rules/pathway-analysis.md	KEGG、Reactome、STRING
rules/clinical-data.md	ClinicalTrials、ClinVar、FDA

ML Prediction Tools (Detailed)

机器学习预测工具（详情）

File	Tool	Use Case
rules/structure-prediction.md	Index	Decision tree for all prediction tools
rules/boltz.md	Boltz-2	Structure + binding affinity
rules/chai.md	Chai-1	Multi-modal (protein+ligand+RNA+glycan)
rules/simplefold.md	SimpleFold	Quick single-protein folding
rules/proteinmpnn.md	ProteinMPNN	Fixed-backbone sequence design
rules/ligandmpnn.md	LigandMPNN	Ligand-aware sequence design
rules/thermompnn.md	ThermoMPNN	Stability (ΔΔG) prediction
rules/geodock.md	GeoDock	Protein-protein docking
rules/pinal.md	Pinal	De novo design from text
rules/boltzgen.md	BoltzGen	End-to-end binder design

文件	工具	使用场景
rules/structure-prediction.md	索引	所有预测工具的决策树
rules/boltz.md	Boltz-2	结构+结合亲和力预测
rules/chai.md	Chai-1	多模态（蛋白质+配体+RNA+聚糖）
rules/simplefold.md	SimpleFold	快速单蛋白质折叠
rules/proteinmpnn.md	ProteinMPNN	固定骨架序列设计
rules/ligandmpnn.md	LigandMPNN	配体感知序列设计
rules/thermompnn.md	ThermoMPNN	稳定性（ΔΔG）预测
rules/geodock.md	GeoDock	蛋白质-蛋白质对接
rules/pinal.md	Pinal	基于文本的从头设计
rules/boltzgen.md	BoltzGen	端到端结合体设计

Tool Categories Summary

工具类别汇总

Category	Count	Examples
Protein structure	23	fetch_pdb_metadata, get_alphafold_prediction
Literature	14	search_pubmed, arxiv_search, biorxiv_search_keywords
Genomics	27	lookup_gene, vep_predict, gwas_search_associations_by_trait
Cheminformatics	20+	calculate_molecular_properties, chembl_similarity_search
Molecular biology	15	design_primers, restriction_digest, assemble_gibson
Structure prediction	15+	submit_boltz_prediction, submit_proteinmpnn_prediction
Pathway analysis	24	analyze_gene_list, get_string_network
Clinical data	22	search_clinical_trials, clinvar_search

类别	数量	示例
蛋白质结构	23	fetch_pdb_metadata、get_alphafold_prediction
文献搜索	14	search_pubmed、arxiv_search、biorxiv_search_keywords
基因组学	27	lookup_gene、vep_predict、gwas_search_associations_by_trait
cheminformatics	20+	calculate_molecular_properties、chembl_similarity_search
分子生物学	15	design_primers、restriction_digest、assemble_gibson
结构预测	15+	submit_boltz_prediction、submit_proteinmpnn_prediction
通路分析	24	analyze_gene_list、get_string_network
临床数据	22	search_clinical_trials、clinvar_search

Troubleshooting: Updating the Skill

故障排除：更新Skill

If the API returns a newer version than the one in this file (see Version Check above), update your skill. See the Version Check section at the top for commands.

若API返回的版本比本文档中标注的版本更新（请参考上方版本检查部分），请更新你的Skill。更新命令请查看顶部的版本检查章节。

Common Mistakes

常见错误

Not checking schemas → Parameter errors. Use
```
POST /api/v1/tools/validate
```
to pre-check params.
Ignoring quality metrics → Using unreliable data
Wrong tool for task → Check decision trees in rule files
Not polling jobs → Missing prediction results
Wrong tool name → 404 responses include "Did you mean?" suggestions with similar tool names

Tip: When in doubt, search for tools:

GET /api/v1/tools/search?q=your_query

未检查架构 → 参数错误。使用
```
POST /api/v1/tools/validate
```
提前验证参数。
忽略质量指标 → 使用不可靠数据
任务与工具不匹配 → 查看规则文档中的决策树
未轮询任务状态 → 遗漏预测结果
工具名称错误 → 404响应会包含“你是否指的是？”的提示，提供相似的工具名称

提示：如有疑问，可搜索工具：

GET /api/v1/tools/search?q=your_query