[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DAW0M99TAQ2VN357EYHTQE":3,"skill-same:01M6DAW0M99TAQ2VN357EYHTQE":51},{"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":18,"publishedAt":26,"linkOnly":27,"markdownContent":28,"markdownBody":29,"frontMatter":30,"refName":31,"commitSha":32,"skillDirectory":33,"forksCount":14,"repositoryHtmlUrl":34,"repositoryHomepageUrl":6,"ownerHtmlUrl":35,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":36,"install":37,"resources":50},"01M6DAW0M99TAQ2VN357EYHTQE","tooluniverse-protein-modification-analysis",null,"Analyze post-translational modifications (PTMs) of proteins — modification sites, types, proteoforms, functional effects at PTM sites, and PTM-dependent protein interactions. Integrates iPTMnet, ProtVar, UniProt, and STRING databases. Use when asked about protein phosphorylation, ubiquitination, acetylation, glycosylation, methylation, SUMOylation, or other PTMs; proteoform diversity; PTM-regulated interactions; or functional impact of PTM sites.","Prekzursil\u002Fagent-skills-toolchain","Prekzursil","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F54636077?v=4","01M6DACZ1PCQHD99SCR1YXG28B","Andrei Mihai Visalon","01M6DACZ670WZF535V3WYYSS4Z",0,"MIT","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-protein-modification-analysis\u002FSKILL.md",[],[19,20,21,22,23,24,25],"analysis","tooluniverse protein modification analysis","analyze","use","databases","diversity","proteins","2026-11-10 10:12:30",false,"---\nname: tooluniverse-protein-modification-analysis\ndescription: Analyze post-translational modifications (PTMs) of proteins — modification sites, types, proteoforms, functional effects at PTM sites, and PTM-dependent protein interactions. Integrates iPTMnet, ProtVar, UniProt, and STRING databases. Use when asked about protein phosphorylation, ubiquitination, acetylation, glycosylation, methylation, SUMOylation, or other PTMs; proteoform diversity; PTM-regulated interactions; or functional impact of PTM sites.\n---\n\n# Protein Post-Translational Modification Analysis\n\nComprehensive PTM analysis using iPTMnet (primary), ProtVar (functional context), UniProt (baseline), STRING (interactions), ELM (linear motifs), and MassIVE\u002FProteomeXchange (experimental data).\n\n## LOOK UP DON'T GUESS\n\n- PTM sites\u002Fenzymes: `iPTMnet_get_ptm_sites`\n- Functional consequence: `ProtVar_get_function` + `iPTMnet_get_ptm_ppi`\n- Proteoforms: `iPTMnet_get_proteoforms`\n- Linear motifs: `ELM_get_instances`\n\n## COMPUTE, DON'T DESCRIBE\nWhen analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.\n\n## Domain Reasoning\n\nPTMs are context-dependent: same phosphorylation site can activate or inhibit depending on kinase and effectors. Always check: which enzyme, what functional consequence, in what cell context.\n\n---\n\n## KEY PRINCIPLES\n\n1. **Disambiguation first** -- resolve to UniProt accession before iPTMnet calls\n2. **iPTMnet is SOAP-style** -- every call requires `operation` parameter\n3. **Evidence-graded** -- distinguish experimental (T1) from predicted (T4)\n4. **English-first queries**\n\n---\n\n## Workflow\n\n```\nPhase 0: Protein Disambiguation → UniProt accession\nPhase 1: PTM Site Inventory → iPTMnet_get_ptm_sites\nPhase 2: Proteoform Analysis → iPTMnet_get_proteoforms\nPhase 3: PTM-Dependent Interactions → iPTMnet_get_ptm_ppi\nPhase 4: Functional Context → ProtVar_get_function at key sites\nPhase 4b: Linear Motif Context → ELM_get_instances for SLiM overlap\nPhase 4c: Experimental Data → MassIVE\u002FProteomeXchange\nPhase 5: Synthesis & Report\n```\n\n---\n\n## Phase 0: Disambiguation\n\n- `iPTMnet_search(operation=\"search\", search_term=\"TP53\", role=\"Substrate\")` -- find UniProt IDs\n- If user provides UniProt accession directly, use it\n- Select human entry if multiple hits\n\n## Phase 1: PTM Sites\n\n`iPTMnet_get_ptm_sites(operation=\"get_ptm_sites\", uniprot_id=\"P04637\")` -- returns position, residue, modification type, enzyme, evidence. Group by modification type. Fallback: `UniProt_get_entry_by_accession` PTM annotations.\n\n## Phase 2: Proteoforms\n\n`iPTMnet_get_proteoforms(operation=\"get_proteoforms\", uniprot_id=...)` -- distinct PTM combinations. Focus on those with functional\u002Fdisease annotations if >20.\n\n## Phase 3: PTM-Dependent Interactions\n\n`iPTMnet_get_ptm_ppi(operation=\"get_ptm_ppi\", uniprot_id=...)` -- interacting protein, PTM site, effect (enables\u002Fdisrupts). Supplement with `STRING_get_interaction_partners(identifiers=gene, species=9606, required_score=700)`.\n\n## Phase 4: Functional Context\n\n`ProtVar_get_function(accession=..., position=N, variant_aa=AA)` -- domain, active site, binding site, conservation. Grade: active-site PTM > domain-core > disordered region.\n\n## Phase 4b: Linear Motifs (ELM)\n\n`ELM_get_instances(operation=\"get_instances\", uniprot_id=..., motif_type=\"MOD\")` -- MOD = modification sites, DEG = degradation signals. Cross-reference with Phase 1 PTM positions. `ELM_list_classes(operation=\"list_classes\")` for motif details.\n\n## Phase 4c: Experimental Data\n\n`MassIVE_search_datasets(species=\"9606\")`, `MassIVE_get_dataset(accession=\"MSV...\")` for public MS datasets.\n\n---\n\n## Evidence Grading\n\n| Tier | Criteria |\n|------|----------|\n| T1 | PTM at validated active\u002Fbinding site with functional data |\n| T2 | PTM in structured domain with ProtVar annotation |\n| T3 | Correlation data only (mass spec detection) |\n| T4 | Predicted, no experimental validation |\n\n---\n\n## Tool Parameter Reference\n\n| Tool | Key Params |\n|------|-----------|\n| `iPTMnet_search` | `operation=\"search\"`, `search_term`, `role` |\n| `iPTMnet_get_ptm_sites` | `operation=\"get_ptm_sites\"`, `uniprot_id` |\n| `iPTMnet_get_proteoforms` | `operation=\"get_proteoforms\"`, `uniprot_id` |\n| `iPTMnet_get_ptm_ppi` | `operation=\"get_ptm_ppi\"`, `uniprot_id` |\n| `ELM_get_instances` | `operation=\"get_instances\"`, `uniprot_id`, `motif_type` |\n| `ELM_list_classes` | `operation=\"list_classes\"` |\n| `MassIVE_search_datasets` | `page_size`, `species` |\n\n**Critical**: All iPTMnet and ELM tools require `operation` as first parameter (SOAP-style).\n\n---\n\n## Fallbacks\n\n| Situation | Fallback |\n|-----------|----------|\n| Not in iPTMnet | UniProt PTM\u002Fprocessing annotations |\n| No PTM-PPI data | STRING general PPI |\n| No ProtVar data | UniProt domain annotations |\n| No ELM data | Proceed with iPTMnet\u002FUniProt only |\n\n## Limitations\n\n- iPTMnet biased toward well-studied proteins\n- Proteoform data covers observed combinations only\n- PTM-PPI: only PTM-specific evidence; more PPIs exist in STRING\n","# Protein Post-Translational Modification Analysis\n\nComprehensive PTM analysis using iPTMnet (primary), ProtVar (functional context), UniProt (baseline), STRING (interactions), ELM (linear motifs), and MassIVE\u002FProteomeXchange (experimental data).\n\n## LOOK UP DON'T GUESS\n\n- PTM sites\u002Fenzymes: `iPTMnet_get_ptm_sites`\n- Functional consequence: `ProtVar_get_function` + `iPTMnet_get_ptm_ppi`\n- Proteoforms: `iPTMnet_get_proteoforms`\n- Linear motifs: `ELM_get_instances`\n\n## COMPUTE, DON'T DESCRIBE\nWhen analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.\n\n## Domain Reasoning\n\nPTMs are context-dependent: same phosphorylation site can activate or inhibit depending on kinase and effectors. Always check: which enzyme, what functional consequence, in what cell context.\n\n---\n\n## KEY PRINCIPLES\n\n1. **Disambiguation first** -- resolve to UniProt accession before iPTMnet calls\n2. **iPTMnet is SOAP-style** -- every call requires `operation` parameter\n3. **Evidence-graded** -- distinguish experimental (T1) from predicted (T4)\n4. **English-first queries**\n\n---\n\n## Workflow\n\n```\nPhase 0: Protein Disambiguation → UniProt accession\nPhase 1: PTM Site Inventory → iPTMnet_get_ptm_sites\nPhase 2: Proteoform Analysis → iPTMnet_get_proteoforms\nPhase 3: PTM-Dependent Interactions → iPTMnet_get_ptm_ppi\nPhase 4: Functional Context → ProtVar_get_function at key sites\nPhase 4b: Linear Motif Context → ELM_get_instances for SLiM overlap\nPhase 4c: Experimental Data → MassIVE\u002FProteomeXchange\nPhase 5: Synthesis & Report\n```\n\n---\n\n## Phase 0: Disambiguation\n\n- `iPTMnet_search(operation=\"search\", search_term=\"TP53\", role=\"Substrate\")` -- find UniProt IDs\n- If user provides UniProt accession directly, use it\n- Select human entry if multiple hits\n\n## Phase 1: PTM Sites\n\n`iPTMnet_get_ptm_sites(operation=\"get_ptm_sites\", uniprot_id=\"P04637\")` -- returns position, residue, modification type, enzyme, evidence. Group by modification type. Fallback: `UniProt_get_entry_by_accession` PTM annotations.\n\n## Phase 2: Proteoforms\n\n`iPTMnet_get_proteoforms(operation=\"get_proteoforms\", uniprot_id=...)` -- distinct PTM combinations. Focus on those with functional\u002Fdisease annotations if >20.\n\n## Phase 3: PTM-Dependent Interactions\n\n`iPTMnet_get_ptm_ppi(operation=\"get_ptm_ppi\", uniprot_id=...)` -- interacting protein, PTM site, effect (enables\u002Fdisrupts). Supplement with `STRING_get_interaction_partners(identifiers=gene, species=9606, required_score=700)`.\n\n## Phase 4: Functional Context\n\n`ProtVar_get_function(accession=..., position=N, variant_aa=AA)` -- domain, active site, binding site, conservation. Grade: active-site PTM > domain-core > disordered region.\n\n## Phase 4b: Linear Motifs (ELM)\n\n`ELM_get_instances(operation=\"get_instances\", uniprot_id=..., motif_type=\"MOD\")` -- MOD = modification sites, DEG = degradation signals. Cross-reference with Phase 1 PTM positions. `ELM_list_classes(operation=\"list_classes\")` for motif details.\n\n## Phase 4c: Experimental Data\n\n`MassIVE_search_datasets(species=\"9606\")`, `MassIVE_get_dataset(accession=\"MSV...\")` for public MS datasets.\n\n---\n\n## Evidence Grading\n\n| Tier | Criteria |\n|------|----------|\n| T1 | PTM at validated active\u002Fbinding site with functional data |\n| T2 | PTM in structured domain with ProtVar annotation |\n| T3 | Correlation data only (mass spec detection) |\n| T4 | Predicted, no experimental validation |\n\n---\n\n## Tool Parameter Reference\n\n| Tool | Key Params |\n|------|-----------|\n| `iPTMnet_search` | `operation=\"search\"`, `search_term`, `role` |\n| `iPTMnet_get_ptm_sites` | `operation=\"get_ptm_sites\"`, `uniprot_id` |\n| `iPTMnet_get_proteoforms` | `operation=\"get_proteoforms\"`, `uniprot_id` |\n| `iPTMnet_get_ptm_ppi` | `operation=\"get_ptm_ppi\"`, `uniprot_id` |\n| `ELM_get_instances` | `operation=\"get_instances\"`, `uniprot_id`, `motif_type` |\n| `ELM_list_classes` | `operation=\"list_classes\"` |\n| `MassIVE_search_datasets` | `page_size`, `species` |\n\n**Critical**: All iPTMnet and ELM tools require `operation` as first parameter (SOAP-style).\n\n---\n\n## Fallbacks\n\n| Situation | Fallback |\n|-----------|----------|\n| Not in iPTMnet | UniProt PTM\u002Fprocessing annotations |\n| No PTM-PPI data | STRING general PPI |\n| No ProtVar data | UniProt domain annotations |\n| No ELM data | Proceed with iPTMnet\u002FUniProt only |\n\n## Limitations\n\n- iPTMnet biased toward well-studied proteins\n- Proteoform data covers observed combinations only\n- PTM-PPI: only PTM-specific evidence; more PPIs exist in STRING\n",{"name":5,"description":7},"main","a298c929b6cbd662e1fce54302ce520d5ceea1a5",".agents\u002Flibrary\u002Fskills\u002Ftooluniverse-protein-modification-analysis","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain","https:\u002F\u002Fgithub.com\u002FPrekzursil","2026-11-02 14:30:57",{"source":8,"skillName":5,"commands":38,"prompt":48,"zipAvailable":49},[39,42,45],{"tool":40,"command":41},"npx","npx skills add Prekzursil\u002Fagent-skills-toolchain --skill tooluniverse-protein-modification-analysis",{"tool":43,"command":44},"bunx","bunx skills add Prekzursil\u002Fagent-skills-toolchain --skill tooluniverse-protein-modification-analysis",{"tool":46,"command":47},"pnpm","pnpm dlx skills add Prekzursil\u002Fagent-skills-toolchain --skill tooluniverse-protein-modification-analysis","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-protein-modification-analysis\u002FSKILL.md",true,[],[52,73,103,130,144,160],{"skillNo":53,"name":54,"nameZh":6,"description":55,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":56,"categories":57,"keywords":58,"publishedAt":26},"01M6DF7D7478R55P46REYH4QAC","clarify-requirements","Resolve genuine pre-execution ambiguity by scanning repo context, generating 1-6 grounded options, and asking 1-3 focused questions via AskUserQuestion. 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