[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-cloud-competitive-landscape-scan":3,"mdc-hcp8c8-key":33,"related-org-google-cloud-competitive-landscape-scan":395,"related-repo-google-cloud-competitive-landscape-scan":584},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":12,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":29,"sourceUrl":31,"mdContent":32},"competitive-landscape-scan","scan competitive drug development landscapes","Build a competitor pipeline view for a target \u002F mechanism \u002F indication — who is in the clinic, what phase, what differentiation. Use for BD \u002F portfolio \u002F commercial-strategy questions like \"who else is developing X\" or \"what's the pipeline for indication Y\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"google-cloud","Google Cloud","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgoogle-cloud.png","GoogleCloudPlatform",[13,17,20],{"name":14,"slug":15,"type":16},"Research","research","tag",{"name":18,"slug":19,"type":16},"Competitive Intelligence","competitive-intelligence",{"name":21,"slug":22,"type":16},"Life Sciences","life-sciences",14,"https:\u002F\u002Fgithub.com\u002FGoogleCloudPlatform\u002FLifeSciences","2026-07-12T07:40:55.676084",null,10,[],{"repoUrl":24,"stars":23,"forks":27,"topics":30,"description":26},[],"https:\u002F\u002Fgithub.com\u002FGoogleCloudPlatform\u002FLifeSciences\u002Ftree\u002FHEAD\u002Fapplications\u002Fpharma-on-gemini-enterprise\u002Fbiocompass-on-gemini-enterprise\u002Fapp\u002Fskills\u002Fcompetitive-landscape-scan","---\nname: competitive-landscape-scan\ndescription: Build a competitor pipeline view for a target \u002F mechanism \u002F indication — who is in the clinic, what phase, what differentiation. Use for BD \u002F portfolio \u002F commercial-strategy questions like \"who else is developing X\" or \"what's the pipeline for indication Y\".\n---\n\n# Competitive Landscape Scan\n\nYou are producing a competitive intelligence brief for a pharma BD,\nportfolio strategy, or commercial team. They need a structured view of\nwho is doing what, where in the development cycle, and what makes each\nprogram distinct. Speed-to-answer matters — keep the synthesis dense.\n\n## Workflow\n\n### 1. Define the scan boundary\n\nGet the user to specify (or infer + confirm):\n\n- **Axis**: target (e.g. \"anti-PD-1\"), mechanism class (e.g. \"GLP-1\u002FGIP\n  dual agonists\"), or indication (e.g. \"non-small-cell lung cancer\n  second-line\").\n- **Phase scope**: usually Phase 1 onwards; ask whether to include\n  preclinical (slower) or to restrict to Phase 2+.\n- **Sponsor scope**: industry only, or include academic \u002F cooperative\n  groups.\n- **Geography**: default to all; restrict if asked (e.g. China-only\n  registry).\n\n### 2. Pull the trial pipeline\n\nCall `search_clinical_trials` with the right combination of\n`condition` \u002F `intervention` \u002F `phase`. Run it twice if needed — once by\nindication, once by intervention — and de-duplicate by NCT ID.\n\nGroup results by:\n\n- **Sponsor** — lead sponsor + collaborators.\n- **Asset** — the intervention name. Many trials test the same asset\n  across indications; collapse them.\n- **Phase** — the highest phase any trial of the asset has reached.\n- **Status** — recruiting, active, completed, terminated. Terminated\n  programs are often the most informative — investigate the reason in\n  the trial's full record via `get_clinical_trial`.\n\n### 3. Pull the publication footprint\n\nFor the top 5-10 assets, run `search_europe_pmc` with\n`\u003Casset_name> AND \u003Cindication>` to find:\n\n- Clinical readouts (cite the specific trial PMID \u002F NCT).\n- Mechanism papers that justify the differentiation claim.\n- Recent congress abstracts (Europe PMC indexes ASCO \u002F ASH \u002F AHA\n  abstracts).\n\n### 4. Surface the differentiation story\n\nFor each top asset, write 1-2 lines on what makes it distinct:\n\n- Modality (small molecule vs. mAb vs. ADC vs. bispecific vs. cell\n  therapy vs. RNAi).\n- Selectivity \u002F specificity (e.g. KRAS G12C selective vs. pan-KRAS).\n- Dosing \u002F convenience (oral vs. IV, monthly vs. weekly).\n- Combination strategy (mono vs. doublet vs. triplet).\n- Patient-selection biomarker (e.g. PD-L1 ≥1%, HER2-low).\n\nThese are the dimensions BD\u002Fportfolio teams ask about; without them the\nscan is just a trial list.\n\n### 5. Output\n\n```\n# Competitive landscape — \u003Caxis>\nScan date: YYYY-MM-DD | Sources: ClinicalTrials.gov + Europe PMC + PubMed\n\n## Pipeline at a glance\nTotal assets: N | Phase 3+: N | Phase 2: N | Phase 1: N | Recently terminated: N\n\n## Leading programs\n| Asset | Sponsor | Modality | Highest phase | Indications | Differentiation | Key refs |\n|-------|---------|----------|---------------|-------------|-----------------|----------|\n\n## Notable readouts in last 12 months\n- ... (PMID \u002F NCT \u002F sponsor \u002F one-line outcome)\n\n## Recent terminations \u002F setbacks\n- ... (asset \u002F sponsor \u002F reason if disclosed)\n\n## Whitespace \u002F under-served angles\n- ... (3-5 bullets on indications, lines of therapy, or biomarker\n  segments where the pipeline is thin)\n```\n\n### 6. Optional figure\n\nCall `visualize_concept` with `figure_type=\"infographic\"` to render a\nsmall-multiples panel of the top assets — useful for one-pager\ndistribution. Each card shows asset \u002F sponsor \u002F phase \u002F modality \u002F\nindications.\n\n## Guardrails\n\n- Differentiate *approved* vs. *investigational* claims — never imply a\n  Phase 2 asset has an approved indication.\n- ClinicalTrials.gov has US bias; flag if a likely-relevant Asia-Pacific\n  program is missing (search by sponsor name when the user mentions one).\n- Use the trial's `phase` field, not the sponsor's marketing language —\n  press releases inflate phase.\n",{"data":34,"body":35},{"name":4,"description":6},{"type":36,"children":37},"root",[38,46,52,59,66,71,117,123,160,165,216,222,243,261,267,272,300,305,311,323,329,349,355],{"type":39,"tag":40,"props":41,"children":42},"element","h1",{"id":4},[43],{"type":44,"value":45},"text","Competitive Landscape Scan",{"type":39,"tag":47,"props":48,"children":49},"p",{},[50],{"type":44,"value":51},"You are producing a competitive intelligence brief for a pharma BD,\nportfolio strategy, or commercial team. They need a structured view of\nwho is doing what, where in the development cycle, and what makes each\nprogram distinct. Speed-to-answer matters — keep the synthesis dense.",{"type":39,"tag":53,"props":54,"children":56},"h2",{"id":55},"workflow",[57],{"type":44,"value":58},"Workflow",{"type":39,"tag":60,"props":61,"children":63},"h3",{"id":62},"_1-define-the-scan-boundary",[64],{"type":44,"value":65},"1. Define the scan boundary",{"type":39,"tag":47,"props":67,"children":68},{},[69],{"type":44,"value":70},"Get the user to specify (or infer + confirm):",{"type":39,"tag":72,"props":73,"children":74},"ul",{},[75,87,97,107],{"type":39,"tag":76,"props":77,"children":78},"li",{},[79,85],{"type":39,"tag":80,"props":81,"children":82},"strong",{},[83],{"type":44,"value":84},"Axis",{"type":44,"value":86},": target (e.g. \"anti-PD-1\"), mechanism class (e.g. \"GLP-1\u002FGIP\ndual agonists\"), or indication (e.g. \"non-small-cell lung cancer\nsecond-line\").",{"type":39,"tag":76,"props":88,"children":89},{},[90,95],{"type":39,"tag":80,"props":91,"children":92},{},[93],{"type":44,"value":94},"Phase scope",{"type":44,"value":96},": usually Phase 1 onwards; ask whether to include\npreclinical (slower) or to restrict to Phase 2+.",{"type":39,"tag":76,"props":98,"children":99},{},[100,105],{"type":39,"tag":80,"props":101,"children":102},{},[103],{"type":44,"value":104},"Sponsor scope",{"type":44,"value":106},": industry only, or include academic \u002F cooperative\ngroups.",{"type":39,"tag":76,"props":108,"children":109},{},[110,115],{"type":39,"tag":80,"props":111,"children":112},{},[113],{"type":44,"value":114},"Geography",{"type":44,"value":116},": default to all; restrict if asked (e.g. China-only\nregistry).",{"type":39,"tag":60,"props":118,"children":120},{"id":119},"_2-pull-the-trial-pipeline",[121],{"type":44,"value":122},"2. Pull the trial pipeline",{"type":39,"tag":47,"props":124,"children":125},{},[126,128,135,137,143,145,151,152,158],{"type":44,"value":127},"Call ",{"type":39,"tag":129,"props":130,"children":132},"code",{"className":131},[],[133],{"type":44,"value":134},"search_clinical_trials",{"type":44,"value":136}," with the right combination of\n",{"type":39,"tag":129,"props":138,"children":140},{"className":139},[],[141],{"type":44,"value":142},"condition",{"type":44,"value":144}," \u002F ",{"type":39,"tag":129,"props":146,"children":148},{"className":147},[],[149],{"type":44,"value":150},"intervention",{"type":44,"value":144},{"type":39,"tag":129,"props":153,"children":155},{"className":154},[],[156],{"type":44,"value":157},"phase",{"type":44,"value":159},". Run it twice if needed — once by\nindication, once by intervention — and de-duplicate by NCT ID.",{"type":39,"tag":47,"props":161,"children":162},{},[163],{"type":44,"value":164},"Group results by:",{"type":39,"tag":72,"props":166,"children":167},{},[168,178,188,198],{"type":39,"tag":76,"props":169,"children":170},{},[171,176],{"type":39,"tag":80,"props":172,"children":173},{},[174],{"type":44,"value":175},"Sponsor",{"type":44,"value":177}," — lead sponsor + collaborators.",{"type":39,"tag":76,"props":179,"children":180},{},[181,186],{"type":39,"tag":80,"props":182,"children":183},{},[184],{"type":44,"value":185},"Asset",{"type":44,"value":187}," — the intervention name. Many trials test the same asset\nacross indications; collapse them.",{"type":39,"tag":76,"props":189,"children":190},{},[191,196],{"type":39,"tag":80,"props":192,"children":193},{},[194],{"type":44,"value":195},"Phase",{"type":44,"value":197}," — the highest phase any trial of the asset has reached.",{"type":39,"tag":76,"props":199,"children":200},{},[201,206,208,214],{"type":39,"tag":80,"props":202,"children":203},{},[204],{"type":44,"value":205},"Status",{"type":44,"value":207}," — recruiting, active, completed, terminated. Terminated\nprograms are often the most informative — investigate the reason in\nthe trial's full record via ",{"type":39,"tag":129,"props":209,"children":211},{"className":210},[],[212],{"type":44,"value":213},"get_clinical_trial",{"type":44,"value":215},".",{"type":39,"tag":60,"props":217,"children":219},{"id":218},"_3-pull-the-publication-footprint",[220],{"type":44,"value":221},"3. Pull the publication footprint",{"type":39,"tag":47,"props":223,"children":224},{},[225,227,233,235,241],{"type":44,"value":226},"For the top 5-10 assets, run ",{"type":39,"tag":129,"props":228,"children":230},{"className":229},[],[231],{"type":44,"value":232},"search_europe_pmc",{"type":44,"value":234}," with\n",{"type":39,"tag":129,"props":236,"children":238},{"className":237},[],[239],{"type":44,"value":240},"\u003Casset_name> AND \u003Cindication>",{"type":44,"value":242}," to find:",{"type":39,"tag":72,"props":244,"children":245},{},[246,251,256],{"type":39,"tag":76,"props":247,"children":248},{},[249],{"type":44,"value":250},"Clinical readouts (cite the specific trial PMID \u002F NCT).",{"type":39,"tag":76,"props":252,"children":253},{},[254],{"type":44,"value":255},"Mechanism papers that justify the differentiation claim.",{"type":39,"tag":76,"props":257,"children":258},{},[259],{"type":44,"value":260},"Recent congress abstracts (Europe PMC indexes ASCO \u002F ASH \u002F AHA\nabstracts).",{"type":39,"tag":60,"props":262,"children":264},{"id":263},"_4-surface-the-differentiation-story",[265],{"type":44,"value":266},"4. Surface the differentiation story",{"type":39,"tag":47,"props":268,"children":269},{},[270],{"type":44,"value":271},"For each top asset, write 1-2 lines on what makes it distinct:",{"type":39,"tag":72,"props":273,"children":274},{},[275,280,285,290,295],{"type":39,"tag":76,"props":276,"children":277},{},[278],{"type":44,"value":279},"Modality (small molecule vs. mAb vs. ADC vs. bispecific vs. cell\ntherapy vs. RNAi).",{"type":39,"tag":76,"props":281,"children":282},{},[283],{"type":44,"value":284},"Selectivity \u002F specificity (e.g. KRAS G12C selective vs. pan-KRAS).",{"type":39,"tag":76,"props":286,"children":287},{},[288],{"type":44,"value":289},"Dosing \u002F convenience (oral vs. IV, monthly vs. weekly).",{"type":39,"tag":76,"props":291,"children":292},{},[293],{"type":44,"value":294},"Combination strategy (mono vs. doublet vs. triplet).",{"type":39,"tag":76,"props":296,"children":297},{},[298],{"type":44,"value":299},"Patient-selection biomarker (e.g. PD-L1 ≥1%, HER2-low).",{"type":39,"tag":47,"props":301,"children":302},{},[303],{"type":44,"value":304},"These are the dimensions BD\u002Fportfolio teams ask about; without them the\nscan is just a trial list.",{"type":39,"tag":60,"props":306,"children":308},{"id":307},"_5-output",[309],{"type":44,"value":310},"5. Output",{"type":39,"tag":312,"props":313,"children":317},"pre",{"className":314,"code":316,"language":44},[315],"language-text","# Competitive landscape — \u003Caxis>\nScan date: YYYY-MM-DD | Sources: ClinicalTrials.gov + Europe PMC + PubMed\n\n## Pipeline at a glance\nTotal assets: N | Phase 3+: N | Phase 2: N | Phase 1: N | Recently terminated: N\n\n## Leading programs\n| Asset | Sponsor | Modality | Highest phase | Indications | Differentiation | Key refs |\n|-------|---------|----------|---------------|-------------|-----------------|----------|\n\n## Notable readouts in last 12 months\n- ... (PMID \u002F NCT \u002F sponsor \u002F one-line outcome)\n\n## Recent terminations \u002F setbacks\n- ... (asset \u002F sponsor \u002F reason if disclosed)\n\n## Whitespace \u002F under-served angles\n- ... (3-5 bullets on indications, lines of therapy, or biomarker\n  segments where the pipeline is thin)\n",[318],{"type":39,"tag":129,"props":319,"children":321},{"__ignoreMap":320},"",[322],{"type":44,"value":316},{"type":39,"tag":60,"props":324,"children":326},{"id":325},"_6-optional-figure",[327],{"type":44,"value":328},"6. Optional figure",{"type":39,"tag":47,"props":330,"children":331},{},[332,333,339,341,347],{"type":44,"value":127},{"type":39,"tag":129,"props":334,"children":336},{"className":335},[],[337],{"type":44,"value":338},"visualize_concept",{"type":44,"value":340}," with ",{"type":39,"tag":129,"props":342,"children":344},{"className":343},[],[345],{"type":44,"value":346},"figure_type=\"infographic\"",{"type":44,"value":348}," to render a\nsmall-multiples panel of the top assets — useful for one-pager\ndistribution. Each card shows asset \u002F sponsor \u002F phase \u002F modality \u002F\nindications.",{"type":39,"tag":53,"props":350,"children":352},{"id":351},"guardrails",[353],{"type":44,"value":354},"Guardrails",{"type":39,"tag":72,"props":356,"children":357},{},[358,378,383],{"type":39,"tag":76,"props":359,"children":360},{},[361,363,369,371,376],{"type":44,"value":362},"Differentiate ",{"type":39,"tag":364,"props":365,"children":366},"em",{},[367],{"type":44,"value":368},"approved",{"type":44,"value":370}," vs. ",{"type":39,"tag":364,"props":372,"children":373},{},[374],{"type":44,"value":375},"investigational",{"type":44,"value":377}," claims — never imply a\nPhase 2 asset has an approved indication.",{"type":39,"tag":76,"props":379,"children":380},{},[381],{"type":44,"value":382},"ClinicalTrials.gov has US bias; flag if a likely-relevant Asia-Pacific\nprogram is missing (search by sponsor name when the user mentions one).",{"type":39,"tag":76,"props":384,"children":385},{},[386,388,393],{"type":44,"value":387},"Use the trial's ",{"type":39,"tag":129,"props":389,"children":391},{"className":390},[],[392],{"type":44,"value":157},{"type":44,"value":394}," field, not the sponsor's marketing language —\npress releases inflate phase.",{"items":396,"total":583},[397,415,431,453,467,478,492,509,526,539,555,565],{"slug":398,"name":398,"fn":399,"description":400,"org":401,"tags":402,"stars":412,"repoUrl":413,"updatedAt":414},"kb-search","search and extract local knowledge base documents","Allows listing, searching and extracting information from local knowledge base documents for information about tables\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[403,406,409],{"name":404,"slug":405,"type":16},"Documentation","documentation",{"name":407,"slug":408,"type":16},"Knowledge Base","knowledge-base",{"name":410,"slug":411,"type":16},"Search","search",6749,"https:\u002F\u002Fgithub.com\u002FGoogleCloudPlatform\u002Fknowledge-catalog","2026-07-12T07:38:52.157375",{"slug":416,"name":417,"fn":418,"description":419,"org":420,"tags":421,"stars":412,"repoUrl":413,"updatedAt":430},"knowledgecatalogdiscoveryagent","knowledge_catalog_discovery_agent","search and rank Knowledge Catalog data entries","Analyzes user queries, extracts relevant predicates, and utilizes Knowledge Catalog Search to find and rank the most relevant data entries. Engages with the user throughout the process.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[422,425,426,429],{"name":423,"slug":424,"type":16},"Data Analysis","data-analysis",{"name":9,"slug":8,"type":16},{"name":427,"slug":428,"type":16},"Knowledge Management","knowledge-management",{"name":410,"slug":411,"type":16},"2026-07-12T07:38:22.196851",{"slug":432,"name":432,"fn":433,"description":434,"org":435,"tags":436,"stars":450,"repoUrl":451,"updatedAt":452},"contributing","contribute to Cloud Foundation Fabric","End-to-end workflow for contributing to Cloud Foundation Fabric: triaging GitHub issues, proactive feature development, validating with tests and Policy Troubleshooter, and submitting sanitized Pull Requests. Use when addressing a Fabric GitHub issue, developing a module or FAST stage change, or preparing a branch for a pull request.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[437,440,443,446,447],{"name":438,"slug":439,"type":16},"Automation","automation",{"name":441,"slug":442,"type":16},"Engineering","engineering",{"name":444,"slug":445,"type":16},"GitHub","github",{"name":9,"slug":8,"type":16},{"name":448,"slug":449,"type":16},"Pull Requests","pull-requests",2062,"https:\u002F\u002Fgithub.com\u002FGoogleCloudPlatform\u002Fcloud-foundation-fabric","2026-07-31T06:23:36.935005",{"slug":454,"name":454,"fn":455,"description":456,"org":457,"tags":458,"stars":450,"repoUrl":451,"updatedAt":466},"fabric-builder","generate Terraform code for Google Cloud","Generates idiomatic Cloud Foundation Fabric (CFF) Terraform code using CFF modules. Use when users ask to create GCP resources, use Fabric modules, or generate Terraform code for Google Cloud.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[459,460,463],{"name":9,"slug":8,"type":16},{"name":461,"slug":462,"type":16},"Infrastructure as Code","infrastructure-as-code",{"name":464,"slug":465,"type":16},"Terraform","terraform","2026-07-12T07:38:23.514555",{"slug":468,"name":468,"fn":469,"description":470,"org":471,"tags":472,"stars":450,"repoUrl":451,"updatedAt":477},"fast-0-org-setup-prereqs","prepare prerequisites for FAST 0-org-setup","Guides the user step-by-step through the prerequisites for the FAST 0-org-setup stage, supporting both Standard GCP and Google Cloud Dedicated (GCD) environments. Use when a user asks to prepare or run prerequisites for 0-org-setup or bootstrap the FAST landing zone.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[473,474],{"name":9,"slug":8,"type":16},{"name":475,"slug":476,"type":16},"Operations","operations","2026-07-12T07:38:28.127148",{"slug":479,"name":479,"fn":480,"description":481,"org":482,"tags":483,"stars":489,"repoUrl":490,"updatedAt":491},"agent-aware-cli","design agent-aware command-line interfaces","Guide for designing and implementing command-line interfaces (CLIs) that are equally usable by human developers and automated coding agents. Use when the user wants to build a CLI, apply CLI best practices, or use Go with Cobra and Viper.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[484,487,488],{"name":485,"slug":486,"type":16},"CLI","cli",{"name":441,"slug":442,"type":16},{"name":9,"slug":8,"type":16},1150,"https:\u002F\u002Fgithub.com\u002FGoogleCloudPlatform\u002Fvertex-ai-creative-studio","2026-07-12T07:39:08.41406",{"slug":493,"name":493,"fn":494,"description":495,"org":496,"tags":497,"stars":489,"repoUrl":490,"updatedAt":508},"build-mcp-genmedia","build and configure GenAI MCP servers","Builds the mcp-genmedia Go MCP servers (nanobanana, veo, lyria, gemini-multimodal, chirp3-hd, avtool) from source and wires them into settings.json. Use this skill whenever the MCP tools are missing or broken — typically at the start of a new session, after a container restart, or when \u002Ftmp has been wiped. The prebuilt binaries in \u002Fworkspace\u002F.local\u002Fbin\u002F have no exec bit and live on a noexec mount; this skill compiles fresh executables into \u002Ftmp\u002Fbin\u002F where execution is allowed.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[498,501,502,505],{"name":499,"slug":500,"type":16},"API Development","api-development",{"name":9,"slug":8,"type":16},{"name":503,"slug":504,"type":16},"LLM","llm",{"name":506,"slug":507,"type":16},"MCP","mcp","2026-07-12T07:39:10.911302",{"slug":510,"name":510,"fn":511,"description":512,"org":513,"tags":514,"stars":489,"repoUrl":490,"updatedAt":525},"genmedia-audio-engineer","synthesize and mix audio content","Expert in audio synthesis, music generation, and mixing. Use when creating podcasts, background scores, or multi-track audio layering using mcp-chirp3-go, mcp-lyria-go, mcp-gemini-go, mcp-nanobanana-go, and mcp-avtool-go.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[515,518,521,522],{"name":516,"slug":517,"type":16},"Audio","audio",{"name":519,"slug":520,"type":16},"Creative","creative",{"name":9,"slug":8,"type":16},{"name":523,"slug":524,"type":16},"Vertex AI","vertex-ai","2026-07-12T07:39:16.623879",{"slug":527,"name":527,"fn":528,"description":529,"org":530,"tags":531,"stars":489,"repoUrl":490,"updatedAt":538},"genmedia-image-artist","generate and edit AI images","Expert in AI image generation and editing. Use when the user needs high-quality textures, character-consistent visuals, or image-to-image editing using mcp-nanobanana-go.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[532,533,534,537],{"name":519,"slug":520,"type":16},{"name":9,"slug":8,"type":16},{"name":535,"slug":536,"type":16},"Image Generation","image-generation",{"name":523,"slug":524,"type":16},"2026-07-12T07:39:15.372822",{"slug":540,"name":540,"fn":541,"description":542,"org":543,"tags":544,"stars":489,"repoUrl":490,"updatedAt":554},"genmedia-producer","produce multi-step media content","Expert media production assistant. Use when requested to help with storyboarding, podcast creation, audio assembly, or complex multi-step media workflows using the GenMedia MCP servers (Veo, Lyria, Gemini TTS, NanoBanana).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[545,546,547,548,551],{"name":516,"slug":517,"type":16},{"name":519,"slug":520,"type":16},{"name":9,"slug":8,"type":16},{"name":549,"slug":550,"type":16},"Media","media",{"name":552,"slug":553,"type":16},"Video","video","2026-07-12T07:39:09.672849",{"slug":556,"name":556,"fn":557,"description":558,"org":559,"tags":560,"stars":489,"repoUrl":490,"updatedAt":564},"genmedia-video-editor","edit and compose video content","Expert in video composition, editing, and format conversion. Use when the user wants to generate high-quality video, overlay images on video, concatenate clips, create GIFs, or sync audio to video using mcp-avtool-go and mcp-veo-go.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[561,562,563],{"name":519,"slug":520,"type":16},{"name":9,"slug":8,"type":16},{"name":552,"slug":553,"type":16},"2026-07-12T07:39:13.749081",{"slug":566,"name":566,"fn":567,"description":568,"org":569,"tags":570,"stars":489,"repoUrl":490,"updatedAt":582},"genmedia-voice-director","generate expressive text-to-speech with Gemini","Expert in casting, directing, and generating expressive text-to-speech using Gemini TTS. Use this when the user needs virtual voice actor personas, expressive speech generation, or multiple variations of a voiceover (like \"take 3 on the bounce\").",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[571,572,573,576,579],{"name":516,"slug":517,"type":16},{"name":519,"slug":520,"type":16},{"name":574,"slug":575,"type":16},"Gemini","gemini",{"name":577,"slug":578,"type":16},"Speech","speech",{"name":580,"slug":581,"type":16},"Text-to-Speech","text-to-speech","2026-07-12T07:39:17.86673",80,{"items":585,"total":649},[586,592,604,616,629,639],{"slug":4,"name":4,"fn":5,"description":6,"org":587,"tags":588,"stars":23,"repoUrl":24,"updatedAt":25},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[589,590,591],{"name":18,"slug":19,"type":16},{"name":21,"slug":22,"type":16},{"name":14,"slug":15,"type":16},{"slug":593,"name":593,"fn":594,"description":595,"org":596,"tags":597,"stars":23,"repoUrl":24,"updatedAt":603},"drug-safety-signal-scan","scan drug safety signals","Surface emerging safety signals for a drug or class from PubMed (case reports \u002F letters \u002F RCT AE tables), plus relevant trial AE disclosures. Use for pharmacovigilance triage, medical-affairs safety updates, or competitive risk assessment. NOT a substitute for formal PV systems.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[598,599,602],{"name":21,"slug":22,"type":16},{"name":600,"slug":601,"type":16},"PubMed","pubmed",{"name":14,"slug":15,"type":16},"2026-07-12T07:40:57.110395",{"slug":605,"name":605,"fn":606,"description":607,"org":608,"tags":609,"stars":23,"repoUrl":24,"updatedAt":615},"mechanism-of-action-explainer","explain drug mechanisms of action","Produce a literature-grounded mechanism-of-action explanation for a drug or drug class — receptor \u002F pathway \u002F downstream effects \u002F clinical relevance — with a Nano Banana Pro diagram and citations. Use for medical-affairs MSL prep, internal training, or when the user asks \"how does drug X work\" or \"what's the MoA of class Y\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[610,613,614],{"name":611,"slug":612,"type":16},"Diagrams","diagrams",{"name":21,"slug":22,"type":16},{"name":14,"slug":15,"type":16},"2026-07-12T07:41:01.085638",{"slug":617,"name":617,"fn":618,"description":619,"org":620,"tags":621,"stars":23,"repoUrl":24,"updatedAt":628},"pico-search-strategy","translate research questions into PubMed search strategies","Translate a clinical or research question into a PICO\u002FPECO-structured PubMed + Europe PMC search strategy with MeSH terms, field tags, and search hedges. Use whenever the user asks a comparative-effectiveness, etiology, prognosis, diagnosis, or HEOR question, OR when they explicitly ask for a \"search strategy\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[622,625,626,627],{"name":623,"slug":624,"type":16},"Bioinformatics","bioinformatics",{"name":21,"slug":22,"type":16},{"name":600,"slug":601,"type":16},{"name":14,"slug":15,"type":16},"2026-07-12T07:40:59.811387",{"slug":630,"name":630,"fn":631,"description":632,"org":633,"tags":634,"stars":23,"repoUrl":24,"updatedAt":638},"prisma-systematic-review","conduct PRISMA systematic reviews","Run a PRISMA 2020-aligned systematic-review workflow — identification → screening → eligibility → included — with a transparent record of exclusions at each step and a rendered PRISMA flow diagram. Use when the user asks for a systematic review, evidence map, scoping review, or any task that requires a defensible screening audit trail.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[635,636,637],{"name":611,"slug":612,"type":16},{"name":21,"slug":22,"type":16},{"name":14,"slug":15,"type":16},"2026-07-12T07:40:58.359064",{"slug":640,"name":640,"fn":641,"description":642,"org":643,"tags":644,"stars":23,"repoUrl":24,"updatedAt":648},"target-evidence-dossier","build target validation dossiers","Build a target-validation dossier for a gene \u002F protein \u002F pathway — biology, disease association, druggability, existing programs, key publications, trial pipeline, safety signals. Use for early-stage discovery target review, portfolio decisions, or when the user asks \"what do we know about target X\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[645,646,647],{"name":623,"slug":624,"type":16},{"name":21,"slug":22,"type":16},{"name":14,"slug":15,"type":16},"2026-07-12T07:40:53.048652",6]