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tooluniverse-protein-structure-retrievaltooluniverse 蛋白质结构检索

Agent Skill

用于搭建或维护带检索增强的 RAG 工作流,适合让 Agent 处理知识库问答、向量检索、来源引用和事实核查。它可以辅助整理数据接入、Embedding、向量库、召回参数和回答生成流程。使用时需要确认数据来源、更新频率、召回阈值和引用展示方式,避免把未命中的资料或过期内容包装成确定事实。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:tooluniverse-protein-structure-retrieval(tooluniverse 蛋白质结构检索)
来源仓库:https://github.com/mims-harvard/tooluniverse
仓库路径:skills/tooluniverse-protein-structure-retrieval
安装命令:
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-protein-structure-retrieval
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-protein-structure-retrieval

简介

用于搭建或维护带检索增强的 RAG 工作流,适合处理知识库问答、向量检索、来源引用和事实核查。

  • 可辅助整理数据接入、Embedding、向量库、召回参数和回答生成流程。
  • 使用时需确认数据来源、更新频率、召回阈值和引用展示方式,避免将未命中资料包装成确定事实。
  • 通过 GitHub 安装,支持 Codex、Claude、Cursor、Gemini CLI 等宿主环境。
  • 建议结合原始 README 核验具体用法,并检查权限范围和维护状态。

SKILL.md

Protein Structure Data Retrieval

Retrieve protein structures with disambiguation, quality assessment, and comprehensive metadata.

IMPORTANT: Always use English terms in tool calls. Respond in the user's language.

LOOK UP DON'T GUESS: Never assume PDB IDs, resolution, or availability. Always query RCSB/PDBe and AlphaFold to confirm.

Domain Reasoning

Not all structures are equal. X-ray <2 A is high-quality for drug design. Cryo-EM 3-4 A is good for fold but not side chains. AlphaFold is excellent for well-folded domains but unreliable for disordered regions. Always check pLDDT (AlphaFold) or resolution (experimental) before drawing conclusions.

Workflow

Phase 0: Clarify (if needed) → Phase 1: Disambiguate Protein → Phase 2: Retrieve Structures → Phase 3: Report

Phase 0: Clarification (When Needed)

Ask ONLY if: protein name ambiguous (e.g., "kinase"), organism not specified, unclear if experimental vs AlphaFold needed. Skip for: specific PDB IDs, UniProt accessions, unambiguous protein+organism.


Phase 1: Protein Disambiguation

# By PDB ID: direct retrieval
# By UniProt: get AlphaFold + search experimental structures
af_structure = tu.tools.alphafold_get_prediction(uniprot_id=uniprot_id)
# By protein name: search
result = tu.tools.PDBeSearch_search_structures(protein_name=protein_name)

Identity Checklist

  • Protein name/gene identified, organism confirmed
  • UniProt accession (if available), isoform/variant specified (if relevant)

Phase 2: Data Retrieval (Internal)

Retrieve silently. Do NOT narrate the process.

pdb_id = "4INS"

# Search, metadata, quality, ligands, similar structures
result = tu.tools.PDBeSearch_search_structures(protein_name=name)
metadata = tu.tools.get_protein_metadata_by_pdb_id(pdb_id=pdb_id)
exp = tu.tools.RCSBData_get_entry(pdb_id=pdb_id)
quality = tu.tools.PDBeValidation_get_quality_scores(pdb_id=pdb_id)
ligands = tu.tools.PDBe_KB_get_ligand_sites(pdb_id=pdb_id)
similar = tu.tools.PDBeSIFTS_get_all_structures(pdb_id=pdb_id, cutoff=2.0)

# PDBe additional data
summary = tu.tools.pdbe_get_entry_summary(pdb_id=pdb_id)
molecules = tu.tools.pdbe_get_entry_molecules(pdb_id=pdb_id)

# AlphaFold (when no experimental structure, or for comparison)
af = tu.tools.alphafold_get_prediction(uniprot_id=uniprot_id)

Fallback Chains

PrimaryFallback
RCSB searchPDBe search
get_protein_metadatapdbe_get_entry_summary
Experimental structureAlphaFold prediction
get_protein_ligandsPDBe_KB_get_ligand_sites

Phase 3: Report Structure Profile

Present as a Structure Profile Report. Hide search process. Include:

  1. Search Summary: query, organism, experimental + AlphaFold structure counts
  2. Best Structure: PDB ID, UniProt, organism, method, resolution, date, quality assessment
  3. Experimental Details: method, resolution, R-factor, R-free, space group
  4. Composition: chains, residues (coverage%), ligands, waters, metals
  5. Bound Ligands: ligand ID, name, type, binding site
  6. Binding Site Details (for drug discovery): location, key residues, druggability
  7. Alternative Structures: ranked by quality with resolution, method, ligands
  8. AlphaFold Prediction: UniProt, model version, pLDDT confidence distribution, use cases
  9. Structure Comparison: resolution, completeness, ligands across structures
  10. Download Links: PDB/mmCIF/AlphaFold formats, database URLs

Quality Assessment

Experimental Structures

TierCriteria
ExcellentX-ray <1.5A, complete, R-free <0.22
HighX-ray <2.0A OR Cryo-EM <3.0A
GoodX-ray 2.0-3.0A OR Cryo-EM 3.0-4.0A
ModerateX-ray >3.0A OR NMR ensemble
Low>4.0A, incomplete, or problematic

Resolution Use Cases

<1.5A: atomic detail, H-bond analysis. 1.5-2.0A: drug design. 2.0-2.5A: structure-based design. 2.5-3.5A: overall architecture. >3.5A: domain arrangement only.

AlphaFold Confidence (pLDDT)

90: very high, experimental-like. 70-90: good backbone. 50-70: uncertain/flexible. <50: likely disordered.

Error Handling

ErrorResponse
"PDB ID not found"Verify 4-char format, check if obsoleted
"No structures"Offer AlphaFold, suggest similar proteins
"Download failed"Retry once, provide alternative link
"Resolution unavailable"Likely NMR/model, note in assessment

Tool Reference

RCSB PDB: PDBeSearch_search_structures (search), get_protein_metadata_by_pdb_id (basic info), RCSBData_get_entry (details), PDBeValidation_get_quality_scores (quality), PDBe_KB_get_ligand_sites (ligands), PDBeSIFTS_get_all_structures (homologs)

PDBe: pdbe_get_entry_summary (overview), pdbe_get_entry_molecules (entities), pdbe_get_experiment_info (experimental), PDBe_KB_get_ligand_sites (pockets)

AlphaFold: alphafold_get_prediction (get prediction), alphafold_get_summary (search)

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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