[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AFHRZQVKVVVM82Q5FVJ1AT":3,"skill-same:01M6AFHRZQVKVVVM82Q5FVJ1AT":79},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":49,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":54,"ownerHtmlUrl":55,"ownerBlogUrl":56,"ownerDescription":57,"updatedAt":58,"install":59,"resources":72},"01M6AFHRZQVKVVVM82Q5FVJ1AT","pdb-database",null,"Access RCSB PDB for 3D protein\u002Fnucleic acid structures. Search by text\u002Fsequence\u002Fstructure, download coordinates (PDB\u002FmmCIF), retrieve metadata, for structural biology and drug discovery.","davila7\u002Fclaude-code-templates","davila7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6216945?v=4","01M6ADEWWFPS191NFM0Y1EX1JH","Daniel Avila","01M6ADJHGM78PHQRD3XZTFDVKK",33481,"MIT","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fpdb-database\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"pdb database","pdb","database","structure","Protein","sequence","for","biology","drug discovery","structural","structural biology","acid","coordinates","text","download","access","discovery","3D","metadata","search","2026-11-10 10:12:30",false,"---\nname: pdb-database\ndescription: \"Access RCSB PDB for 3D protein\u002Fnucleic acid structures. Search by text\u002Fsequence\u002Fstructure, download coordinates (PDB\u002FmmCIF), retrieve metadata, for structural biology and drug discovery.\"\n---\n\n# PDB Database\n\n## Overview\n\nRCSB PDB is the worldwide repository for 3D structural data of biological macromolecules. Search for structures, retrieve coordinates and metadata, perform sequence and structure similarity searches across 200,000+ experimentally determined structures and computed models.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Searching for protein or nucleic acid 3D structures by text, sequence, or structural similarity\n- Downloading coordinate files in PDB, mmCIF, or BinaryCIF formats\n- Retrieving structural metadata, experimental methods, or quality metrics\n- Performing batch operations across multiple structures\n- Integrating PDB data into computational workflows for drug discovery, protein engineering, or structural biology research\n\n## Core Capabilities\n\n### 1. Searching for Structures\n\nFind PDB entries using various search criteria:\n\n**Text Search:** Search by protein name, keywords, or descriptions\n```python\nfrom rcsbapi.search import TextQuery\nquery = TextQuery(\"hemoglobin\")\nresults = list(query())\nprint(f\"Found {len(results)} structures\")\n```\n\n**Attribute Search:** Query specific properties (organism, resolution, method, etc.)\n```python\nfrom rcsbapi.search import AttributeQuery\nfrom rcsbapi.search.attrs import rcsb_entity_source_organism\n\n# Find human protein structures\nquery = AttributeQuery(\n    attribute=rcsb_entity_source_organism.scientific_name,\n    operator=\"exact_match\",\n    value=\"Homo sapiens\"\n)\nresults = list(query())\n```\n\n**Sequence Similarity:** Find structures similar to a given sequence\n```python\nfrom rcsbapi.search import SequenceQuery\n\nquery = SequenceQuery(\n    value=\"MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHHYREQIKRVKDSEDVPMVLVGNKCDLPSRTVDTKQAQDLARSYGIPFIETSAKTRQGVDDAFYTLVREIRKHKEKMSKDGKKKKKKSKTKCVIM\",\n    evalue_cutoff=0.1,\n    identity_cutoff=0.9\n)\nresults = list(query())\n```\n\n**Structure Similarity:** Find structures with similar 3D geometry\n```python\nfrom rcsbapi.search import StructSimilarityQuery\n\nquery = StructSimilarityQuery(\n    structure_search_type=\"entry\",\n    entry_id=\"4HHB\"  # Hemoglobin\n)\nresults = list(query())\n```\n\n**Combining Queries:** Use logical operators to build complex searches\n```python\nfrom rcsbapi.search import TextQuery, AttributeQuery\nfrom rcsbapi.search.attrs import rcsb_entry_info\n\n# High-resolution human proteins\nquery1 = AttributeQuery(\n    attribute=rcsb_entity_source_organism.scientific_name,\n    operator=\"exact_match\",\n    value=\"Homo sapiens\"\n)\nquery2 = AttributeQuery(\n    attribute=rcsb_entry_info.resolution_combined,\n    operator=\"less\",\n    value=2.0\n)\ncombined_query = query1 & query2  # AND operation\nresults = list(combined_query())\n```\n\n### 2. Retrieving Structure Data\n\nAccess detailed information about specific PDB entries:\n\n**Basic Entry Information:**\n```python\nfrom rcsbapi.data import Schema, fetch\n\n# Get entry-level data\nentry_data = fetch(\"4HHB\", schema=Schema.ENTRY)\nprint(entry_data[\"struct\"][\"title\"])\nprint(entry_data[\"exptl\"][0][\"method\"])\n```\n\n**Polymer Entity Information:**\n```python\n# Get protein\u002Fnucleic acid information\nentity_data = fetch(\"4HHB_1\", schema=Schema.POLYMER_ENTITY)\nprint(entity_data[\"entity_poly\"][\"pdbx_seq_one_letter_code\"])\n```\n\n**Using GraphQL for Flexible Queries:**\n```python\nfrom rcsbapi.data import fetch\n\n# Custom GraphQL query\nquery = \"\"\"\n{\n  entry(entry_id: \"4HHB\") {\n    struct {\n      title\n    }\n    exptl {\n      method\n    }\n    rcsb_entry_info {\n      resolution_combined\n      deposited_atom_count\n    }\n  }\n}\n\"\"\"\ndata = fetch(query_type=\"graphql\", query=query)\n```\n\n### 3. Downloading Structure Files\n\nRetrieve coordinate files in various formats:\n\n**Download Methods:**\n- **PDB format** (legacy text format): `https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{PDB_ID}.pdb`\n- **mmCIF format** (modern standard): `https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{PDB_ID}.cif`\n- **BinaryCIF** (compressed binary): Use ModelServer API for efficient access\n- **Biological assembly**: `https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{PDB_ID}.pdb1` (for assembly 1)\n\n**Example Download:**\n```python\nimport requests\n\npdb_id = \"4HHB\"\n\n# Download PDB format\npdb_url = f\"https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{pdb_id}.pdb\"\nresponse = requests.get(pdb_url)\nwith open(f\"{pdb_id}.pdb\", \"w\") as f:\n    f.write(response.text)\n\n# Download mmCIF format\ncif_url = f\"https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{pdb_id}.cif\"\nresponse = requests.get(cif_url)\nwith open(f\"{pdb_id}.cif\", \"w\") as f:\n    f.write(response.text)\n```\n\n### 4. Working with Structure Data\n\nCommon operations with retrieved structures:\n\n**Parse and Analyze Coordinates:**\nUse BioPython or other structural biology libraries to work with downloaded files:\n```python\nfrom Bio.PDB import PDBParser\n\nparser = PDBParser()\nstructure = parser.get_structure(\"protein\", \"4HHB.pdb\")\n\n# Iterate through atoms\nfor model in structure:\n    for chain in model:\n        for residue in chain:\n            for atom in residue:\n                print(atom.get_coord())\n```\n\n**Extract Metadata:**\n```python\nfrom rcsbapi.data import fetch, Schema\n\n# Get experimental details\ndata = fetch(\"4HHB\", schema=Schema.ENTRY)\n\nresolution = data.get(\"rcsb_entry_info\", {}).get(\"resolution_combined\")\nmethod = data.get(\"exptl\", [{}])[0].get(\"method\")\ndeposition_date = data.get(\"rcsb_accession_info\", {}).get(\"deposit_date\")\n\nprint(f\"Resolution: {resolution} Å\")\nprint(f\"Method: {method}\")\nprint(f\"Deposited: {deposition_date}\")\n```\n\n### 5. Batch Operations\n\nProcess multiple structures efficiently:\n\n```python\nfrom rcsbapi.data import fetch, Schema\n\npdb_ids = [\"4HHB\", \"1MBN\", \"1GZX\"]  # Hemoglobin, myoglobin, etc.\n\nresults = {}\nfor pdb_id in pdb_ids:\n    try:\n        data = fetch(pdb_id, schema=Schema.ENTRY)\n        results[pdb_id] = {\n            \"title\": data[\"struct\"][\"title\"],\n            \"resolution\": data.get(\"rcsb_entry_info\", {}).get(\"resolution_combined\"),\n            \"organism\": data.get(\"rcsb_entity_source_organism\", [{}])[0].get(\"scientific_name\")\n        }\n    except Exception as e:\n        print(f\"Error fetching {pdb_id}: {e}\")\n\n# Display results\nfor pdb_id, info in results.items():\n    print(f\"\\n{pdb_id}: {info['title']}\")\n    print(f\"  Resolution: {info['resolution']} Å\")\n    print(f\"  Organism: {info['organism']}\")\n```\n\n## Python Package Installation\n\nInstall the official RCSB PDB Python API client:\n\n```bash\n# Current recommended package\nuv pip install rcsb-api\n\n# For legacy code (deprecated, use rcsb-api instead)\nuv pip install rcsbsearchapi\n```\n\nThe `rcsb-api` package provides unified access to both Search and Data APIs through the `rcsbapi.search` and `rcsbapi.data` modules.\n\n## Common Use Cases\n\n### Drug Discovery\n- Search for structures of drug targets\n- Analyze ligand binding sites\n- Compare protein-ligand complexes\n- Identify similar binding pockets\n\n### Protein Engineering\n- Find homologous structures for modeling\n- Analyze sequence-structure relationships\n- Compare mutant structures\n- Study protein stability and dynamics\n\n### Structural Biology Research\n- Download structures for computational analysis\n- Build structure-based alignments\n- Analyze structural features (secondary structure, domains)\n- Compare experimental methods and quality metrics\n\n### Education and Visualization\n- Retrieve structures for teaching\n- Generate molecular visualizations\n- Explore structure-function relationships\n- Study evolutionary conservation\n\n## Key Concepts\n\n**PDB ID:** Unique 4-character identifier (e.g., \"4HHB\") for each structure entry. AlphaFold and ModelArchive entries start with \"AF_\" or \"MA_\" prefixes.\n\n**mmCIF\u002FPDBx:** Modern file format that uses key-value structure, replacing legacy PDB format for large structures.\n\n**Biological Assembly:** The functional form of a macromolecule, which may contain multiple copies of chains from the asymmetric unit.\n\n**Resolution:** Measure of detail in crystallographic structures (lower values = higher detail). Typical range: 1.5-3.5 Å for high-quality structures.\n\n**Entity:** A unique molecular component in a structure (protein chain, DNA, ligand, etc.).\n\n## Resources\n\nThis skill includes reference documentation in the `references\u002F` directory:\n\n### references\u002Fapi_reference.md\nComprehensive API documentation covering:\n- Detailed API endpoint specifications\n- Advanced query patterns and examples\n- Data schema reference\n- Rate limiting and best practices\n- Troubleshooting common issues\n\nUse this reference when you need in-depth information about API capabilities, complex query construction, or detailed data schema information.\n\n## Additional Resources\n\n- **RCSB PDB Website:** https:\u002F\u002Fwww.rcsb.org\n- **PDB-101 Educational Portal:** https:\u002F\u002Fpdb101.rcsb.org\n- **API Documentation:** https:\u002F\u002Fwww.rcsb.org\u002Fdocs\u002Fprogrammatic-access\u002Fweb-apis-overview\n- **Python Package Docs:** https:\u002F\u002Frcsbapi.readthedocs.io\u002F\n- **Data API Documentation:** https:\u002F\u002Fdata.rcsb.org\u002F\n- **GitHub Repository:** https:\u002F\u002Fgithub.com\u002Frcsb\u002Fpy-rcsb-api\n","# PDB Database\n\n## Overview\n\nRCSB PDB is the worldwide repository for 3D structural data of biological macromolecules. Search for structures, retrieve coordinates and metadata, perform sequence and structure similarity searches across 200,000+ experimentally determined structures and computed models.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Searching for protein or nucleic acid 3D structures by text, sequence, or structural similarity\n- Downloading coordinate files in PDB, mmCIF, or BinaryCIF formats\n- Retrieving structural metadata, experimental methods, or quality metrics\n- Performing batch operations across multiple structures\n- Integrating PDB data into computational workflows for drug discovery, protein engineering, or structural biology research\n\n## Core Capabilities\n\n### 1. Searching for Structures\n\nFind PDB entries using various search criteria:\n\n**Text Search:** Search by protein name, keywords, or descriptions\n```python\nfrom rcsbapi.search import TextQuery\nquery = TextQuery(\"hemoglobin\")\nresults = list(query())\nprint(f\"Found {len(results)} structures\")\n```\n\n**Attribute Search:** Query specific properties (organism, resolution, method, etc.)\n```python\nfrom rcsbapi.search import AttributeQuery\nfrom rcsbapi.search.attrs import rcsb_entity_source_organism\n\n# Find human protein structures\nquery = AttributeQuery(\n    attribute=rcsb_entity_source_organism.scientific_name,\n    operator=\"exact_match\",\n    value=\"Homo sapiens\"\n)\nresults = list(query())\n```\n\n**Sequence Similarity:** Find structures similar to a given sequence\n```python\nfrom rcsbapi.search import SequenceQuery\n\nquery = SequenceQuery(\n    value=\"MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHHYREQIKRVKDSEDVPMVLVGNKCDLPSRTVDTKQAQDLARSYGIPFIETSAKTRQGVDDAFYTLVREIRKHKEKMSKDGKKKKKKSKTKCVIM\",\n    evalue_cutoff=0.1,\n    identity_cutoff=0.9\n)\nresults = list(query())\n```\n\n**Structure Similarity:** Find structures with similar 3D geometry\n```python\nfrom rcsbapi.search import StructSimilarityQuery\n\nquery = StructSimilarityQuery(\n    structure_search_type=\"entry\",\n    entry_id=\"4HHB\"  # Hemoglobin\n)\nresults = list(query())\n```\n\n**Combining Queries:** Use logical operators to build complex searches\n```python\nfrom rcsbapi.search import TextQuery, AttributeQuery\nfrom rcsbapi.search.attrs import rcsb_entry_info\n\n# High-resolution human proteins\nquery1 = AttributeQuery(\n    attribute=rcsb_entity_source_organism.scientific_name,\n    operator=\"exact_match\",\n    value=\"Homo sapiens\"\n)\nquery2 = AttributeQuery(\n    attribute=rcsb_entry_info.resolution_combined,\n    operator=\"less\",\n    value=2.0\n)\ncombined_query = query1 & query2  # AND operation\nresults = list(combined_query())\n```\n\n### 2. Retrieving Structure Data\n\nAccess detailed information about specific PDB entries:\n\n**Basic Entry Information:**\n```python\nfrom rcsbapi.data import Schema, fetch\n\n# Get entry-level data\nentry_data = fetch(\"4HHB\", schema=Schema.ENTRY)\nprint(entry_data[\"struct\"][\"title\"])\nprint(entry_data[\"exptl\"][0][\"method\"])\n```\n\n**Polymer Entity Information:**\n```python\n# Get protein\u002Fnucleic acid information\nentity_data = fetch(\"4HHB_1\", schema=Schema.POLYMER_ENTITY)\nprint(entity_data[\"entity_poly\"][\"pdbx_seq_one_letter_code\"])\n```\n\n**Using GraphQL for Flexible Queries:**\n```python\nfrom rcsbapi.data import fetch\n\n# Custom GraphQL query\nquery = \"\"\"\n{\n  entry(entry_id: \"4HHB\") {\n    struct {\n      title\n    }\n    exptl {\n      method\n    }\n    rcsb_entry_info {\n      resolution_combined\n      deposited_atom_count\n    }\n  }\n}\n\"\"\"\ndata = fetch(query_type=\"graphql\", query=query)\n```\n\n### 3. Downloading Structure Files\n\nRetrieve coordinate files in various formats:\n\n**Download Methods:**\n- **PDB format** (legacy text format): `https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{PDB_ID}.pdb`\n- **mmCIF format** (modern standard): `https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{PDB_ID}.cif`\n- **BinaryCIF** (compressed binary): Use ModelServer API for efficient access\n- **Biological assembly**: `https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{PDB_ID}.pdb1` (for assembly 1)\n\n**Example Download:**\n```python\nimport requests\n\npdb_id = \"4HHB\"\n\n# Download PDB format\npdb_url = f\"https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{pdb_id}.pdb\"\nresponse = requests.get(pdb_url)\nwith open(f\"{pdb_id}.pdb\", \"w\") as f:\n    f.write(response.text)\n\n# Download mmCIF format\ncif_url = f\"https:\u002F\u002Ffiles.rcsb.org\u002Fdownload\u002F{pdb_id}.cif\"\nresponse = requests.get(cif_url)\nwith open(f\"{pdb_id}.cif\", \"w\") as f:\n    f.write(response.text)\n```\n\n### 4. Working with Structure Data\n\nCommon operations with retrieved structures:\n\n**Parse and Analyze Coordinates:**\nUse BioPython or other structural biology libraries to work with downloaded files:\n```python\nfrom Bio.PDB import PDBParser\n\nparser = PDBParser()\nstructure = parser.get_structure(\"protein\", \"4HHB.pdb\")\n\n# Iterate through atoms\nfor model in structure:\n    for chain in model:\n        for residue in chain:\n            for atom in residue:\n                print(atom.get_coord())\n```\n\n**Extract Metadata:**\n```python\nfrom rcsbapi.data import fetch, Schema\n\n# Get experimental details\ndata = fetch(\"4HHB\", schema=Schema.ENTRY)\n\nresolution = data.get(\"rcsb_entry_info\", {}).get(\"resolution_combined\")\nmethod = data.get(\"exptl\", [{}])[0].get(\"method\")\ndeposition_date = data.get(\"rcsb_accession_info\", {}).get(\"deposit_date\")\n\nprint(f\"Resolution: {resolution} Å\")\nprint(f\"Method: {method}\")\nprint(f\"Deposited: {deposition_date}\")\n```\n\n### 5. Batch Operations\n\nProcess multiple structures efficiently:\n\n```python\nfrom rcsbapi.data import fetch, Schema\n\npdb_ids = [\"4HHB\", \"1MBN\", \"1GZX\"]  # Hemoglobin, myoglobin, etc.\n\nresults = {}\nfor pdb_id in pdb_ids:\n    try:\n        data = fetch(pdb_id, schema=Schema.ENTRY)\n        results[pdb_id] = {\n            \"title\": data[\"struct\"][\"title\"],\n            \"resolution\": data.get(\"rcsb_entry_info\", {}).get(\"resolution_combined\"),\n            \"organism\": data.get(\"rcsb_entity_source_organism\", [{}])[0].get(\"scientific_name\")\n        }\n    except Exception as e:\n        print(f\"Error fetching {pdb_id}: {e}\")\n\n# Display results\nfor pdb_id, info in results.items():\n    print(f\"\\n{pdb_id}: {info['title']}\")\n    print(f\"  Resolution: {info['resolution']} Å\")\n    print(f\"  Organism: {info['organism']}\")\n```\n\n## Python Package Installation\n\nInstall the official RCSB PDB Python API client:\n\n```bash\n# Current recommended package\nuv pip install rcsb-api\n\n# For legacy code (deprecated, use rcsb-api instead)\nuv pip install rcsbsearchapi\n```\n\nThe `rcsb-api` package provides unified access to both Search and Data APIs through the `rcsbapi.search` and `rcsbapi.data` modules.\n\n## Common Use Cases\n\n### Drug Discovery\n- Search for structures of drug targets\n- Analyze ligand binding sites\n- Compare protein-ligand complexes\n- Identify similar binding pockets\n\n### Protein Engineering\n- Find homologous structures for modeling\n- Analyze sequence-structure relationships\n- Compare mutant structures\n- Study protein stability and dynamics\n\n### Structural Biology Research\n- Download structures for computational analysis\n- Build structure-based alignments\n- Analyze structural features (secondary structure, domains)\n- Compare experimental methods and quality metrics\n\n### Education and Visualization\n- Retrieve structures for teaching\n- Generate molecular visualizations\n- Explore structure-function relationships\n- Study evolutionary conservation\n\n## Key Concepts\n\n**PDB ID:** Unique 4-character identifier (e.g., \"4HHB\") for each structure entry. AlphaFold and ModelArchive entries start with \"AF_\" or \"MA_\" prefixes.\n\n**mmCIF\u002FPDBx:** Modern file format that uses key-value structure, replacing legacy PDB format for large structures.\n\n**Biological Assembly:** The functional form of a macromolecule, which may contain multiple copies of chains from the asymmetric unit.\n\n**Resolution:** Measure of detail in crystallographic structures (lower values = higher detail). Typical range: 1.5-3.5 Å for high-quality structures.\n\n**Entity:** A unique molecular component in a structure (protein chain, DNA, ligand, etc.).\n\n## Resources\n\nThis skill includes reference documentation in the `references\u002F` directory:\n\n### references\u002Fapi_reference.md\nComprehensive API documentation covering:\n- Detailed API endpoint specifications\n- Advanced query patterns and examples\n- Data schema reference\n- Rate limiting and best practices\n- Troubleshooting common issues\n\nUse this reference when you need in-depth information about API capabilities, complex query construction, or detailed data schema information.\n\n## Additional Resources\n\n- **RCSB PDB Website:** https:\u002F\u002Fwww.rcsb.org\n- **PDB-101 Educational Portal:** https:\u002F\u002Fpdb101.rcsb.org\n- **API Documentation:** https:\u002F\u002Fwww.rcsb.org\u002Fdocs\u002Fprogrammatic-access\u002Fweb-apis-overview\n- **Python Package Docs:** https:\u002F\u002Frcsbapi.readthedocs.io\u002F\n- **Data API Documentation:** https:\u002F\u002Fdata.rcsb.org\u002F\n- **GitHub Repository:** https:\u002F\u002Fgithub.com\u002Frcsb\u002Fpy-rcsb-api\n",{"name":5,"description":7},"main","2b749c82b5d11fac39d9a6e021ce3f5b8a541bd1","cli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fpdb-database",3931,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates","https:\u002F\u002Faitmpl.com","https:\u002F\u002Fgithub.com\u002Fdavila7","https:\u002F\u002Fdanielavila.me","Building AI dev tools with LLMs","2026-11-14 06:14:46",{"source":8,"skillName":5,"commands":60,"prompt":70,"zipAvailable":71},[61,64,67],{"tool":62,"command":63},"npx","npx skills add davila7\u002Fclaude-code-templates --skill pdb-database",{"tool":65,"command":66},"bunx","bunx skills add davila7\u002Fclaude-code-templates --skill pdb-database",{"tool":68,"command":69},"pnpm","pnpm dlx skills add davila7\u002Fclaude-code-templates --skill pdb-database","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fpdb-database\u002FSKILL.md",true,[73],{"path":74,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":77,"sourceHtmlUrl":78},"references\u002Fapi_reference.md","REFERENCE","参考文档",15244,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fpdb-database\u002Freferences\u002Fapi_reference.md",[80,109,136,165,200,224],{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":84,"categories":85,"keywords":89,"publishedAt":44},"01M70NHBTQ8BV0A2SCAZXEPHCX","wealthville-pool-scoring","Score DeFi liquidity pools before providing liquidity. Returns a 0-100 pool score and an Enter\u002FHold\u002FExit\u002FReduce\u002FAvoid verdict with calibrated confidence for ~68,800 Solana pools and 575 EVM pools, plus a public miss-inclusive track record. Use when asked whether a pool is worth LPing into, which pools look best right now, or how accurate the scores have actually been.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fweb-data\u002Fwealthville-pool-scoring\u002FSKILL.md",[86],{"categoryNo":87,"categoryName":88,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[90,91,92,93,94,30,95,96,97,98,99,100,101,102,103,104,105,106,107,108],"scoring","pool","wealthville pool scoring","liquidity","which","exit","now","use","when","reduce","with","record","track","verdict","evm","solana","how","public","look",{"skillNo":110,"name":111,"nameZh":6,"description":112,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":113,"categories":114,"keywords":116,"publishedAt":44},"01M70MB6VR8ERJ4EM8D5KHBMEV","technical-debt-auditor","Scans a codebase and produces a quantified technical debt report with a prioritized remediation plan. Analyzes dead code, TODO\u002FFIXME\u002FHACK markers, dependency staleness, complexity hotspots, code duplication signals, test coverage gaps, unused exports, and outdated patterns. Use this skill when the user asks to audit their codebase for tech debt, wants a health check of their code quality, says things like \"where should I focus refactoring\", \"find code smells\", \"audit my codebase\", \"what technical debt do we have\", \"prioritize cleanup work\", or asks about code quality metrics. Also trigger when the user mentions \"code rot\", \"legacy cleanup\", \"refactoring priorities\", or wants to understand the overall health of a project before a major effort. Trigger even if the user doesn't say \"technical debt\" explicitly — any request to systematically assess code quality and identify improvement priorities belongs here.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Ftechnical-debt-auditor\u002FSKILL.md",[115],{"categoryNo":87,"categoryName":88,"taxonomyType":21,"taxonomyTypeDesc":22},[117,118,119,120,121,122,123,124,125,126,127,98,128,129,130,131,132,133,134,135],"technical debt","debt","technical","technical debt auditor","auditor","coverage","complexity","markers","project","cleanup","unused","code","todo","work","plan","focus","signals","audit","dependency",{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":149,"publishedAt":44},"01M70KPYH9QNHCNME5GJQGE22K","readonly-sql-guard","Make an agent's database access provably read-only. Use when an agent runs caller-supplied SQL against a production\u002FERP\u002Fanalytics database (a \"query\" MCP tool, text-to-SQL, an admin console), or when reviewing DB-access code for write\u002FDDL\u002Fside-effect\u002Ftransaction-escape risks. Checks what a statement CALLS, not just its shape.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdatabase\u002Freadonly-sql-guard\u002FSKILL.md",[142,143,144],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":87,"categoryName":88,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":145,"categoryName":146,"taxonomyType":147,"taxonomyTypeDesc":148},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[150,151,152,153,154,155,156,30,157,158,159,160,161,162,163,97,39,26,98,164],"readonly","guard","sql guard","sql","readonly sql guard","erp","effect","read-only","db","just","tool","calls","only","MCP","query",{"skillNo":166,"name":167,"nameZh":6,"description":168,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":169,"licenseFileUrl":170,"sourceHtmlUrl":171,"categories":172,"keywords":176,"publishedAt":44},"01M6AFY6F7CC2BBZP1QD6VTNVC","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FSKILL.md",[173],{"categoryNo":174,"categoryName":175,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,30,199],"artifacts builder","web","web artifacts builder","artifacts","builder","state","routing","state management","component","css","frontend","ui","Tools","file","components","shadcn","react","Tailwind","suite","jsx","html","single-file","ui components",{"skillNo":201,"name":202,"nameZh":6,"description":203,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":169,"licenseFileUrl":204,"sourceHtmlUrl":205,"categories":206,"keywords":211,"publishedAt":44},"01M6AFWF33SFV9Z3SF4PEEE4BF","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FSKILL.md",[207,210],{"categoryNo":208,"categoryName":209,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":174,"categoryName":175,"taxonomyType":21,"taxonomyTypeDesc":22},[212,213,214,215,216,178,217,187,188,218,219,220,221,30,222,100,223],"webapp testing","testing","webapp","browser","playwright","applications","debugging","toolkit","logs","screenshots","local","behavior",{"skillNo":225,"name":226,"nameZh":6,"description":227,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":169,"licenseFileUrl":228,"sourceHtmlUrl":229,"categories":230,"keywords":238,"publishedAt":44},"01M6AF67Q67JJJ5V51JR2P52KA","discernment-nudge","After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FSKILL.md",[231,234,235],{"categoryNo":232,"categoryName":233,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":87,"categoryName":88,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":236,"categoryName":237,"taxonomyType":147,"taxonomyTypeDesc":148},"01JBSEEDCAT000000000000036","内容创作者",[239,240,241,242,243,244,245,246,180,247,190,128,248,249,250,251,252,162,253,98,254,255,256,257,258,106,259],"discernment nudge","nudge","interpretation","help","run","reasoning","data","writing","lookup","content","review","conversation","short","up","invoke","you","analysis","claims","argument","assemble","recommendations"]