[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-openai-create-data-context":3,"mdc--xozpgw-key":33,"related-repo-openai-create-data-context":426,"related-org-openai-create-data-context":539},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":22,"repoUrl":23,"updatedAt":24,"license":25,"forks":26,"topics":27,"repo":28,"sourceUrl":31,"mdContent":32},"create-data-context","create and manage data semantic layers","Create, update, inspect, or repair Data Analytics semantic layers. Use when the user asks to save data context or create a semantic layer that future Data Analytics work can inspect and cite.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"openai","OpenAI","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fopenai.png",[12,16,19],{"name":13,"slug":14,"type":15},"Data Analysis","data-analysis","tag",{"name":17,"slug":18,"type":15},"Data Modeling","data-modeling",{"name":20,"slug":21,"type":15},"Analytics","analytics",427,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Frole-specific-plugins","2026-07-14T05:43:44.330745",null,65,[],{"repoUrl":23,"stars":22,"forks":26,"topics":29,"description":30},[],"Role-specific Codex plugin templates","https:\u002F\u002Fgithub.com\u002Fopenai\u002Frole-specific-plugins\u002Ftree\u002FHEAD\u002Fplugins\u002Fdata-analytics\u002Fskills\u002Fcreate-data-context","---\nname: create-data-context\ndescription: \"Create, update, inspect, or repair Data Analytics semantic layers. Use when the user asks to save data context or create a semantic layer that future Data Analytics work can inspect and cite.\"\n---\n\n# Create Data Context\n\nThis skill creates and maintains semantic-layer skills for Data Analytics. A semantic-layer skill is an explicit artifact the user can inspect and cite later. It captures how future analyses should interpret the data, for example which metric definition is canonical, which dashboard or table is the best source of truth, and what caveats should be checked before answering.\n\nData-task routing is owned by the Data Analytics `index` skill. If the user wants Data Analytics to do work with data now, route to `index`, whether the work starts from connected sources, uploaded files, pasted tables, sample data, or an existing semantic layer. Examples include answering a metric question, building a report, or checking a dataset.\n\nUse this skill only when the user asks to save data context or create, update, inspect, or repair a semantic layer.\n\n## Runtime Routing\n\nUse the current runtime's classified `surface` and `mode` values, plus the capabilities exposed in the run, to choose intake and persistence. Build and validate the same canonical semantic-layer skill package before writing it to any destination.\n\nFor intake:\n\n- Use structured intake when a supported form action is available.\n- Use conversational intake for open-ended details and for runtimes without a supported form action.\n\nChoose one persistence destination by default:\n\n| Destination branch | Select this branch when | Action |\n| --- | --- | --- |\n| ChatGPT personal Skills | `surface = chatgpt_web` and the run exposes a product-backed personal Skills install surface, such as a native skill draft\u002Fupload\u002Finstall action or an installable skill package preview. | Install the generated skill into the user's personal Skills library. Capture the installed skill link or Skills-library reference returned by the install surface and include it as a Markdown link in the chat response. Verify through the available Skills-library, list, or fresh-thread discovery surface when the runtime exposes one. |\n| Local Codex | The user asks for local persistence, or `surface = codex_desktop`. | Write a filesystem skill to `$CODEX_HOME\u002Fskills\u002F\u003Carea>-semantic-layer`; if `$CODEX_HOME` is unavailable and the local runtime clearly uses the default home location, use `~\u002F.codex\u002Fskills\u002F\u003Carea>-semantic-layer`. Validate the written skill and verify it is discoverable in a new local Codex context when possible. |\n| Portable package | The current run has no supported persistent skill destination. | Return a portable skill package or source plan and clearly state that it has not been installed persistently, including the exact persistence blocker. |\n\nFor dual ChatGPT web and local Codex availability, install the same canonical package into both the ChatGPT Skills library and the local Codex user-skill directory.\n\nFor ordinary data work, return to the Data Analytics `index` workflow.\n\n## Skill Configuration\n\n### Audience And Language\n\nWrite for Data Analytics users, not plugin maintainers. Explain what context would improve the current or future analysis in practical terms. Avoid implementation terms such as raw state paths, connector ids, cache, runtime, metadata, or preflight unless the user asks for debugging details.\n\n### Source Links\n\nWhen referencing sources inline, prefer clickable Markdown links over plain labels whenever a useful URL exists. Use the source title, record name, channel\u002Fthread, or meeting\u002Fdate as the link text. Use plain labels only when no useful link is available.\n\n## Semantic Layer Setup\n\nUse this flow when the user wants to create or maintain a semantic layer. If they are not ready to create the layer yet, use the same flow to produce a short source plan for what the semantic layer needs.\n\nThe output is a visible skill or plan. Build the semantic-layer skill when enough source-backed detail exists to make it useful. When the available detail is still thin, return a practical plan that explains what source to collect next and why.\n\n## Creating Or Updating The Layer\n\nCreate one semantic layer per coherent product, business, metric, source, or reporting area unless the user explicitly asks for a broader shared layer. Infer the area from the provided context when it is clear; ask only when the answer changes the crawl, destination, or resulting skill.\n\nChoose the destination from `Runtime Routing` using the supported persistence mechanism exposed in the current run. For local Codex creations, default to `$CODEX_HOME\u002Fskills\u002F\u003Carea>-semantic-layer` unless the user chooses another destination. Ask before placing a generated semantic-layer skill inside a plugin.\n\nBefore crawling, build a data-source list that explains what was checked, what is missing, and which sources are lower-confidence. For direct creation or draft-file work, write it to `references\u002Fsource-inventory.md`; for planning-only work, return it in chat.\n\nUse source-backed evidence. Favor durable sources such as transformation code, tests, maintained metric docs, and verified dashboards over looser signals such as query history or team discussion. If sources disagree, keep the conflict visible instead of choosing silently.\n\nKeep generated semantic-layer skills compact. Put detailed metric definitions, tables, query patterns, caveats, and evidence into linked references using `references\u002Fsemantic-layer\u002Fskill-template.md`. Preserve provenance and avoid copying raw sensitive data, credentials, row-level examples, or long private messages into generated files.\n\nAfter creating or updating a semantic-layer skill, read `references\u002Fsemantic-layer\u002Fweekly-polling-automation.md` and always offer weekly refresh when the layer has a stable target path and usable `references\u002Fsource-inventory.md`. Weekly refresh is optional: do not create it without explicit user approval unless the user directly asked for recurring refresh. If the offer cannot be made, state the missing prerequisite.\n\nReturn the created or updated path or installed skill link, source coverage, any user-relevant caveats or blockers, future-use guidance, iteration guidance, and the weekly refresh automation offer or prerequisite blocker so the user can cite the semantic layer directly in later prompts. Tell the user they can ask to refine definitions, add sources, update caveats, or adjust the semantic layer as their understanding changes. For ChatGPT personal Skills creations, include the installed skill link in the response.\n\nKeep routine validation details in support artifacts unless a check failed, was unavailable, or changes how the user should rely on the semantic layer.\n\n## Output Contract\n\nFor semantic-layer work, report what was created, updated, inspected, or repaired; source coverage; any user-relevant caveats or blockers; and the exact path or installed skill link the user can cite later. For create or update results, include the weekly refresh automation offer or the missing prerequisite that prevented the offer, and let the user know they can iterate on the semantic layer. Keep routine validation details in support artifacts. If the request is ordinary data work, say that it should be routed through `index`.\n",{"data":34,"body":35},{"name":4,"description":6},{"type":36,"children":37},"root",[38,46,52,73,78,85,106,111,126,131,256,261,273,279,286,291,297,302,308,313,318,324,329,348,361,366,379,399,404,409,415],{"type":39,"tag":40,"props":41,"children":42},"element","h1",{"id":4},[43],{"type":44,"value":45},"text","Create Data Context",{"type":39,"tag":47,"props":48,"children":49},"p",{},[50],{"type":44,"value":51},"This skill creates and maintains semantic-layer skills for Data Analytics. A semantic-layer skill is an explicit artifact the user can inspect and cite later. It captures how future analyses should interpret the data, for example which metric definition is canonical, which dashboard or table is the best source of truth, and what caveats should be checked before answering.",{"type":39,"tag":47,"props":53,"children":54},{},[55,57,64,66,71],{"type":44,"value":56},"Data-task routing is owned by the Data Analytics ",{"type":39,"tag":58,"props":59,"children":61},"code",{"className":60},[],[62],{"type":44,"value":63},"index",{"type":44,"value":65}," skill. If the user wants Data Analytics to do work with data now, route to ",{"type":39,"tag":58,"props":67,"children":69},{"className":68},[],[70],{"type":44,"value":63},{"type":44,"value":72},", whether the work starts from connected sources, uploaded files, pasted tables, sample data, or an existing semantic layer. Examples include answering a metric question, building a report, or checking a dataset.",{"type":39,"tag":47,"props":74,"children":75},{},[76],{"type":44,"value":77},"Use this skill only when the user asks to save data context or create, update, inspect, or repair a semantic layer.",{"type":39,"tag":79,"props":80,"children":82},"h2",{"id":81},"runtime-routing",[83],{"type":44,"value":84},"Runtime Routing",{"type":39,"tag":47,"props":86,"children":87},{},[88,90,96,98,104],{"type":44,"value":89},"Use the current runtime's classified ",{"type":39,"tag":58,"props":91,"children":93},{"className":92},[],[94],{"type":44,"value":95},"surface",{"type":44,"value":97}," and ",{"type":39,"tag":58,"props":99,"children":101},{"className":100},[],[102],{"type":44,"value":103},"mode",{"type":44,"value":105}," values, plus the capabilities exposed in the run, to choose intake and persistence. Build and validate the same canonical semantic-layer skill package before writing it to any destination.",{"type":39,"tag":47,"props":107,"children":108},{},[109],{"type":44,"value":110},"For intake:",{"type":39,"tag":112,"props":113,"children":114},"ul",{},[115,121],{"type":39,"tag":116,"props":117,"children":118},"li",{},[119],{"type":44,"value":120},"Use structured intake when a supported form action is available.",{"type":39,"tag":116,"props":122,"children":123},{},[124],{"type":44,"value":125},"Use conversational intake for open-ended details and for runtimes without a supported form action.",{"type":39,"tag":47,"props":127,"children":128},{},[129],{"type":44,"value":130},"Choose one persistence destination by default:",{"type":39,"tag":132,"props":133,"children":134},"table",{},[135,159],{"type":39,"tag":136,"props":137,"children":138},"thead",{},[139],{"type":39,"tag":140,"props":141,"children":142},"tr",{},[143,149,154],{"type":39,"tag":144,"props":145,"children":146},"th",{},[147],{"type":44,"value":148},"Destination branch",{"type":39,"tag":144,"props":150,"children":151},{},[152],{"type":44,"value":153},"Select this branch when",{"type":39,"tag":144,"props":155,"children":156},{},[157],{"type":44,"value":158},"Action",{"type":39,"tag":160,"props":161,"children":162},"tbody",{},[163,188,238],{"type":39,"tag":140,"props":164,"children":165},{},[166,172,183],{"type":39,"tag":167,"props":168,"children":169},"td",{},[170],{"type":44,"value":171},"ChatGPT personal Skills",{"type":39,"tag":167,"props":173,"children":174},{},[175,181],{"type":39,"tag":58,"props":176,"children":178},{"className":177},[],[179],{"type":44,"value":180},"surface = chatgpt_web",{"type":44,"value":182}," and the run exposes a product-backed personal Skills install surface, such as a native skill draft\u002Fupload\u002Finstall action or an installable skill package preview.",{"type":39,"tag":167,"props":184,"children":185},{},[186],{"type":44,"value":187},"Install the generated skill into the user's personal Skills library. Capture the installed skill link or Skills-library reference returned by the install surface and include it as a Markdown link in the chat response. Verify through the available Skills-library, list, or fresh-thread discovery surface when the runtime exposes one.",{"type":39,"tag":140,"props":189,"children":190},{},[191,196,209],{"type":39,"tag":167,"props":192,"children":193},{},[194],{"type":44,"value":195},"Local Codex",{"type":39,"tag":167,"props":197,"children":198},{},[199,201,207],{"type":44,"value":200},"The user asks for local persistence, or ",{"type":39,"tag":58,"props":202,"children":204},{"className":203},[],[205],{"type":44,"value":206},"surface = codex_desktop",{"type":44,"value":208},".",{"type":39,"tag":167,"props":210,"children":211},{},[212,214,220,222,228,230,236],{"type":44,"value":213},"Write a filesystem skill to ",{"type":39,"tag":58,"props":215,"children":217},{"className":216},[],[218],{"type":44,"value":219},"$CODEX_HOME\u002Fskills\u002F\u003Carea>-semantic-layer",{"type":44,"value":221},"; if ",{"type":39,"tag":58,"props":223,"children":225},{"className":224},[],[226],{"type":44,"value":227},"$CODEX_HOME",{"type":44,"value":229}," is unavailable and the local runtime clearly uses the default home location, use ",{"type":39,"tag":58,"props":231,"children":233},{"className":232},[],[234],{"type":44,"value":235},"~\u002F.codex\u002Fskills\u002F\u003Carea>-semantic-layer",{"type":44,"value":237},". Validate the written skill and verify it is discoverable in a new local Codex context when possible.",{"type":39,"tag":140,"props":239,"children":240},{},[241,246,251],{"type":39,"tag":167,"props":242,"children":243},{},[244],{"type":44,"value":245},"Portable package",{"type":39,"tag":167,"props":247,"children":248},{},[249],{"type":44,"value":250},"The current run has no supported persistent skill destination.",{"type":39,"tag":167,"props":252,"children":253},{},[254],{"type":44,"value":255},"Return a portable skill package or source plan and clearly state that it has not been installed persistently, including the exact persistence blocker.",{"type":39,"tag":47,"props":257,"children":258},{},[259],{"type":44,"value":260},"For dual ChatGPT web and local Codex availability, install the same canonical package into both the ChatGPT Skills library and the local Codex user-skill directory.",{"type":39,"tag":47,"props":262,"children":263},{},[264,266,271],{"type":44,"value":265},"For ordinary data work, return to the Data Analytics ",{"type":39,"tag":58,"props":267,"children":269},{"className":268},[],[270],{"type":44,"value":63},{"type":44,"value":272}," workflow.",{"type":39,"tag":79,"props":274,"children":276},{"id":275},"skill-configuration",[277],{"type":44,"value":278},"Skill Configuration",{"type":39,"tag":280,"props":281,"children":283},"h3",{"id":282},"audience-and-language",[284],{"type":44,"value":285},"Audience And Language",{"type":39,"tag":47,"props":287,"children":288},{},[289],{"type":44,"value":290},"Write for Data Analytics users, not plugin maintainers. Explain what context would improve the current or future analysis in practical terms. Avoid implementation terms such as raw state paths, connector ids, cache, runtime, metadata, or preflight unless the user asks for debugging details.",{"type":39,"tag":280,"props":292,"children":294},{"id":293},"source-links",[295],{"type":44,"value":296},"Source Links",{"type":39,"tag":47,"props":298,"children":299},{},[300],{"type":44,"value":301},"When referencing sources inline, prefer clickable Markdown links over plain labels whenever a useful URL exists. Use the source title, record name, channel\u002Fthread, or meeting\u002Fdate as the link text. Use plain labels only when no useful link is available.",{"type":39,"tag":79,"props":303,"children":305},{"id":304},"semantic-layer-setup",[306],{"type":44,"value":307},"Semantic Layer Setup",{"type":39,"tag":47,"props":309,"children":310},{},[311],{"type":44,"value":312},"Use this flow when the user wants to create or maintain a semantic layer. If they are not ready to create the layer yet, use the same flow to produce a short source plan for what the semantic layer needs.",{"type":39,"tag":47,"props":314,"children":315},{},[316],{"type":44,"value":317},"The output is a visible skill or plan. Build the semantic-layer skill when enough source-backed detail exists to make it useful. When the available detail is still thin, return a practical plan that explains what source to collect next and why.",{"type":39,"tag":79,"props":319,"children":321},{"id":320},"creating-or-updating-the-layer",[322],{"type":44,"value":323},"Creating Or Updating The Layer",{"type":39,"tag":47,"props":325,"children":326},{},[327],{"type":44,"value":328},"Create one semantic layer per coherent product, business, metric, source, or reporting area unless the user explicitly asks for a broader shared layer. Infer the area from the provided context when it is clear; ask only when the answer changes the crawl, destination, or resulting skill.",{"type":39,"tag":47,"props":330,"children":331},{},[332,334,339,341,346],{"type":44,"value":333},"Choose the destination from ",{"type":39,"tag":58,"props":335,"children":337},{"className":336},[],[338],{"type":44,"value":84},{"type":44,"value":340}," using the supported persistence mechanism exposed in the current run. For local Codex creations, default to ",{"type":39,"tag":58,"props":342,"children":344},{"className":343},[],[345],{"type":44,"value":219},{"type":44,"value":347}," unless the user chooses another destination. Ask before placing a generated semantic-layer skill inside a plugin.",{"type":39,"tag":47,"props":349,"children":350},{},[351,353,359],{"type":44,"value":352},"Before crawling, build a data-source list that explains what was checked, what is missing, and which sources are lower-confidence. For direct creation or draft-file work, write it to ",{"type":39,"tag":58,"props":354,"children":356},{"className":355},[],[357],{"type":44,"value":358},"references\u002Fsource-inventory.md",{"type":44,"value":360},"; for planning-only work, return it in chat.",{"type":39,"tag":47,"props":362,"children":363},{},[364],{"type":44,"value":365},"Use source-backed evidence. Favor durable sources such as transformation code, tests, maintained metric docs, and verified dashboards over looser signals such as query history or team discussion. If sources disagree, keep the conflict visible instead of choosing silently.",{"type":39,"tag":47,"props":367,"children":368},{},[369,371,377],{"type":44,"value":370},"Keep generated semantic-layer skills compact. Put detailed metric definitions, tables, query patterns, caveats, and evidence into linked references using ",{"type":39,"tag":58,"props":372,"children":374},{"className":373},[],[375],{"type":44,"value":376},"references\u002Fsemantic-layer\u002Fskill-template.md",{"type":44,"value":378},". Preserve provenance and avoid copying raw sensitive data, credentials, row-level examples, or long private messages into generated files.",{"type":39,"tag":47,"props":380,"children":381},{},[382,384,390,392,397],{"type":44,"value":383},"After creating or updating a semantic-layer skill, read ",{"type":39,"tag":58,"props":385,"children":387},{"className":386},[],[388],{"type":44,"value":389},"references\u002Fsemantic-layer\u002Fweekly-polling-automation.md",{"type":44,"value":391}," and always offer weekly refresh when the layer has a stable target path and usable ",{"type":39,"tag":58,"props":393,"children":395},{"className":394},[],[396],{"type":44,"value":358},{"type":44,"value":398},". Weekly refresh is optional: do not create it without explicit user approval unless the user directly asked for recurring refresh. If the offer cannot be made, state the missing prerequisite.",{"type":39,"tag":47,"props":400,"children":401},{},[402],{"type":44,"value":403},"Return the created or updated path or installed skill link, source coverage, any user-relevant caveats or blockers, future-use guidance, iteration guidance, and the weekly refresh automation offer or prerequisite blocker so the user can cite the semantic layer directly in later prompts. Tell the user they can ask to refine definitions, add sources, update caveats, or adjust the semantic layer as their understanding changes. For ChatGPT personal Skills creations, include the installed skill link in the response.",{"type":39,"tag":47,"props":405,"children":406},{},[407],{"type":44,"value":408},"Keep routine validation details in support artifacts unless a check failed, was unavailable, or changes how the user should rely on the semantic layer.",{"type":39,"tag":79,"props":410,"children":412},{"id":411},"output-contract",[413],{"type":44,"value":414},"Output Contract",{"type":39,"tag":47,"props":416,"children":417},{},[418,420,425],{"type":44,"value":419},"For semantic-layer work, report what was created, updated, inspected, or repaired; source coverage; any user-relevant caveats or blockers; and the exact path or installed skill link the user can cite later. For create or update results, include the weekly refresh automation offer or the missing prerequisite that prevented the offer, and let the user know they can iterate on the semantic layer. Keep routine validation details in support artifacts. If the request is ordinary data work, say that it should be routed through ",{"type":39,"tag":58,"props":421,"children":423},{"className":422},[],[424],{"type":44,"value":63},{"type":44,"value":208},{"items":427,"total":538},[428,445,461,474,490,506,523],{"slug":429,"name":429,"fn":430,"description":431,"org":432,"tags":433,"stars":22,"repoUrl":23,"updatedAt":444},"analyze-account-signals","analyze account signals for sales intelligence","Use when the user wants to know what changed with one account, monitor an owner portfolio or watchlist, or rank accounts needing attention from recent evidence. Produce an evidence-backed account brief or bounded watchlist summary with recommended actions.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[434,435,438,441],{"name":20,"slug":21,"type":15},{"name":436,"slug":437,"type":15},"CRM","crm",{"name":439,"slug":440,"type":15},"Research","research",{"name":442,"slug":443,"type":15},"Sales","sales","2026-07-01T07:54:11.79288",{"slug":446,"name":446,"fn":447,"description":448,"org":449,"tags":450,"stars":22,"repoUrl":23,"updatedAt":460},"analyze-data-quality","assess data quality for analysis","Assess whether structured data, query results, dashboards, or analytical evidence are trustworthy enough to use. Use when the task is to check data quality, reconcile conflicting sources or metric definitions, or decide whether evidence is safe to cite.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[451,454,457],{"name":452,"slug":453,"type":15},"Audit","audit",{"name":455,"slug":456,"type":15},"Data Engineering","data-engineering",{"name":458,"slug":459,"type":15},"Data Quality","data-quality","2026-07-01T07:55:01.146961",{"slug":462,"name":462,"fn":463,"description":464,"org":465,"tags":466,"stars":22,"repoUrl":23,"updatedAt":473},"answers-ask-user-input","request missing context from users","Use when a small amount of missing context would materially improve the answer and tappable options plus a free-text answer can gather it efficiently.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[467,470],{"name":468,"slug":469,"type":15},"Communications","communications",{"name":471,"slug":472,"type":15},"Productivity","productivity","2026-07-14T05:43:36.096323",{"slug":475,"name":475,"fn":476,"description":477,"org":478,"tags":479,"stars":22,"repoUrl":23,"updatedAt":489},"apollo","prospect and enrich leads with Apollo","Use only when a focused Sales workflow has selected a present and connected Apollo connector, or the user explicitly asks for Apollo prospecting, enrichment, Company Details, records, sequences, or outbound planning. Apply Apollo v2-specific behavior only after verifying app version 2.0.0 or later.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[480,482,485,488],{"name":481,"slug":475,"type":15},"Apollo",{"name":483,"slug":484,"type":15},"Lead Enrichment","lead-enrichment",{"name":486,"slug":487,"type":15},"Prospecting","prospecting",{"name":442,"slug":443,"type":15},"2026-07-14T05:43:34.800076",{"slug":453,"name":453,"fn":491,"description":492,"org":493,"tags":494,"stars":22,"repoUrl":23,"updatedAt":505},"audit product flows and user journeys","Audit or critique a product flow, journey, workflow, funnel, onboarding path, checkout path, settings path, screen, or multi-step product experience by capturing screenshots first, then reporting UX, design, and accessibility findings inline from that evidence. Use Figma only when the user explicitly asks for a board. Use when the user asks to audit, review, critique, inspect, assess, analyze, evaluate, or give feedback on a product experience.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[495,496,499,502],{"name":452,"slug":453,"type":15},{"name":497,"slug":498,"type":15},"Design","design",{"name":500,"slug":501,"type":15},"Product Management","product-management",{"name":503,"slug":504,"type":15},"UX Design","ux-design","2026-07-01T07:54:30.613428",{"slug":507,"name":507,"fn":508,"description":509,"org":510,"tags":511,"stars":22,"repoUrl":23,"updatedAt":522},"build-business-case","build customer-led business cases and ROI","Review commercial proposals and build customer-led business cases, ROI or value models, pricing or investment rationales, executive summaries, and customer-ready value stories tied to a customer, workflow, initiative, or decision.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[512,515,518,521],{"name":513,"slug":514,"type":15},"Content Creation","content-creation",{"name":516,"slug":517,"type":15},"Finance","finance",{"name":519,"slug":520,"type":15},"Financial Modeling","financial-modeling",{"name":442,"slug":443,"type":15},"2026-07-01T07:54:02.779003",{"slug":524,"name":524,"fn":525,"description":526,"org":527,"tags":528,"stars":22,"repoUrl":23,"updatedAt":537},"build-competitive-brief","build competitive briefs and battlecards","Use when the user wants a competitor or vendor comparison, market-landscape analysis, battlecard, objection package, positioning brief, or account-specific competitive view. Produce an evidence-backed comparison, guidance, and brief, using supplied materials, connected research, and public evidence when appropriate.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[529,532,535,536],{"name":530,"slug":531,"type":15},"Competitive Intelligence","competitive-intelligence",{"name":533,"slug":534,"type":15},"Marketing","marketing",{"name":439,"slug":440,"type":15},{"name":442,"slug":443,"type":15},"2026-07-01T07:54:13.073252",43,{"items":540,"total":741},[541,562,585,602,618,637,654,668,684,698,710,725],{"slug":542,"name":542,"fn":543,"description":544,"org":545,"tags":546,"stars":559,"repoUrl":560,"updatedAt":561},"prior-auth-packet-builder","build healthcare prior authorization packets","Build a concise prior authorization packet from local case files and payer policy docs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[547,550,553,556],{"name":548,"slug":549,"type":15},"Documents","documents",{"name":551,"slug":552,"type":15},"Healthcare","healthcare",{"name":554,"slug":555,"type":15},"Insurance","insurance",{"name":557,"slug":558,"type":15},"Regulatory Compliance","regulatory-compliance",28169,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fopenai-agents-python","2026-04-16T05:11:39.180399",{"slug":563,"name":563,"fn":564,"description":565,"org":566,"tags":567,"stars":582,"repoUrl":583,"updatedAt":584},"aspnet-core","build ASP.NET Core web applications","Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authentication, authorization, testing, performance, deployment, or ASP.NET Core upgrades.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[568,571,573,576,579],{"name":569,"slug":570,"type":15},".NET","dotnet",{"name":572,"slug":563,"type":15},"ASP.NET Core",{"name":574,"slug":575,"type":15},"Blazor","blazor",{"name":577,"slug":578,"type":15},"C#","csharp",{"name":580,"slug":581,"type":15},"Web Development","web-development",23787,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills","2026-04-12T05:07:02.819491",{"slug":586,"name":586,"fn":587,"description":588,"org":589,"tags":590,"stars":582,"repoUrl":583,"updatedAt":601},"chatgpt-apps","build ChatGPT Apps SDK applications","Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[591,594,597,600],{"name":592,"slug":593,"type":15},"Apps SDK","apps-sdk",{"name":595,"slug":596,"type":15},"ChatGPT","chatgpt",{"name":598,"slug":599,"type":15},"MCP","mcp",{"name":9,"slug":8,"type":15},"2026-04-12T05:07:05.468097",{"slug":603,"name":603,"fn":604,"description":605,"org":606,"tags":607,"stars":582,"repoUrl":583,"updatedAt":617},"cli-creator","build CLIs from API docs","Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read\u002Fwrite commands, return stable JSON, manage auth, and pair with a companion skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[608,611,614],{"name":609,"slug":610,"type":15},"API Development","api-development",{"name":612,"slug":613,"type":15},"CLI","cli",{"name":615,"slug":616,"type":15},"Codex","codex","2026-04-12T05:07:04.132762",{"slug":619,"name":619,"fn":620,"description":621,"org":622,"tags":623,"stars":582,"repoUrl":583,"updatedAt":636},"cloudflare-deploy","deploy projects to Cloudflare","Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[624,627,630,633],{"name":625,"slug":626,"type":15},"Cloudflare","cloudflare",{"name":628,"slug":629,"type":15},"Cloudflare Pages","cloudflare-pages",{"name":631,"slug":632,"type":15},"Cloudflare Workers","cloudflare-workers",{"name":634,"slug":635,"type":15},"Deployment","deployment","2026-04-12T05:07:14.275118",{"slug":638,"name":638,"fn":639,"description":640,"org":641,"tags":642,"stars":582,"repoUrl":583,"updatedAt":653},"define-goal","define and set measurable project goals","Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[643,644,647,650],{"name":471,"slug":472,"type":15},{"name":645,"slug":646,"type":15},"Project Management","project-management",{"name":648,"slug":649,"type":15},"Strategy","strategy",{"name":651,"slug":652,"type":15},"Task Management","task-management","2026-05-23T06:17:16.870838",{"slug":655,"name":655,"fn":656,"description":657,"org":658,"tags":659,"stars":582,"repoUrl":583,"updatedAt":667},"figma","translate Figma designs into code","Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[660,661,663,666],{"name":497,"slug":498,"type":15},{"name":662,"slug":655,"type":15},"Figma",{"name":664,"slug":665,"type":15},"Frontend","frontend",{"name":598,"slug":599,"type":15},"2026-04-12T05:06:47.939943",{"slug":669,"name":669,"fn":670,"description":671,"org":672,"tags":673,"stars":582,"repoUrl":583,"updatedAt":683},"figma-code-connect-components","connect Figma designs to code components","Connects Figma design components to code components using Code Connect mapping tools. Use when user says \"code connect\", \"connect this component to code\", \"map this component\", \"link component to code\", \"create code connect mapping\", or wants to establish mappings between Figma designs and code implementations. For canvas writes via `use_figma`, use `figma-use`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[674,675,678,679,680],{"name":497,"slug":498,"type":15},{"name":676,"slug":677,"type":15},"Design System","design-system",{"name":662,"slug":655,"type":15},{"name":664,"slug":665,"type":15},{"name":681,"slug":682,"type":15},"UI Components","ui-components","2026-05-10T05:59:52.971881",{"slug":685,"name":685,"fn":686,"description":687,"org":688,"tags":689,"stars":582,"repoUrl":583,"updatedAt":697},"figma-create-design-system-rules","generate design system rules from Figma","Generates custom design system rules for the user's codebase. Use when user says \"create design system rules\", \"generate rules for my project\", \"set up design rules\", \"customize design system guidelines\", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server connection.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[690,691,692,695,696],{"name":497,"slug":498,"type":15},{"name":676,"slug":677,"type":15},{"name":693,"slug":694,"type":15},"Documentation","documentation",{"name":662,"slug":655,"type":15},{"name":664,"slug":665,"type":15},"2026-05-16T06:07:47.821474",{"slug":699,"name":699,"fn":700,"description":701,"org":702,"tags":703,"stars":582,"repoUrl":583,"updatedAt":709},"figma-implement-design","translate Figma designs into application code","Translates Figma designs into production-ready application code with 1:1 visual fidelity. Use when implementing UI code from Figma files, when user mentions \"implement design\", \"generate code\", \"implement component\", provides Figma URLs, or asks to build components matching Figma specs. For Figma canvas writes via `use_figma`, use `figma-use`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[704,705,706,707,708],{"name":497,"slug":498,"type":15},{"name":662,"slug":655,"type":15},{"name":664,"slug":665,"type":15},{"name":681,"slug":682,"type":15},{"name":580,"slug":581,"type":15},"2026-05-16T06:07:40.583615",{"slug":711,"name":711,"fn":712,"description":713,"org":714,"tags":715,"stars":582,"repoUrl":583,"updatedAt":724},"hatch-pet","create animated pets for Codex","Create, repair, validate, visually QA, and package Codex-compatible animated pets and pet spritesheets from character art, generated images, company or prospect brand cues, or visual references. Use when a user wants a lightweight-worker Codex pet workflow, a non-pixel custom pet style, a prospect or company mascot pet, or a full 8x9 animated pet atlas with transparent unused cells, QA contact sheets, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[716,719,720,723],{"name":717,"slug":718,"type":15},"Animation","animation",{"name":615,"slug":616,"type":15},{"name":721,"slug":722,"type":15},"Creative","creative",{"name":497,"slug":498,"type":15},"2026-05-02T05:31:48.48485",{"slug":726,"name":726,"fn":727,"description":728,"org":729,"tags":730,"stars":582,"repoUrl":583,"updatedAt":740},"imagegen","generate and edit raster images","Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG\u002Fvector\u002Fcode-native assets, extending an established icon or logo system, or building the visual directly in HTML\u002FCSS\u002Fcanvas.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[731,732,733,736,739],{"name":721,"slug":722,"type":15},{"name":497,"slug":498,"type":15},{"name":734,"slug":735,"type":15},"Image Generation","image-generation",{"name":737,"slug":738,"type":15},"Images","images",{"name":9,"slug":8,"type":15},"2026-05-15T06:23:24.312127",675]