[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-openai-twilio-customer-memory":3,"mdc-oqn0cx-key":36,"related-repo-openai-twilio-customer-memory":4122,"related-org-openai-twilio-customer-memory":4245},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":25,"repoUrl":26,"updatedAt":27,"license":28,"forks":29,"topics":30,"repo":31,"sourceUrl":34,"mdContent":35},"twilio-customer-memory","manage customer context with Twilio Memory","Store and retrieve customer context using Twilio Conversation Memory. Covers Memory Store provisioning, profile management, traits, observations, conversation summaries, and semantic Recall. Use this skill to give AI agents or human agents persistent memory of customer interactions across sessions and channels.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"openai","OpenAI","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fopenai.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Automation","automation","tag",{"name":17,"slug":18,"type":15},"Customer Support","customer-support",{"name":20,"slug":21,"type":15},"Memory","memory",{"name":23,"slug":24,"type":15},"Twilio","twilio",3992,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fplugins","2026-06-30T19:00:57.102",null,465,[],{"repoUrl":26,"stars":25,"forks":29,"topics":32,"description":33},[],"OpenAI Plugins","https:\u002F\u002Fgithub.com\u002Fopenai\u002Fplugins\u002Ftree\u002FHEAD\u002Fplugins\u002Ftwilio-developer-kit\u002Fskills\u002Ftwilio-customer-memory","---\nname: twilio-customer-memory\ndescription: >\n  Store and retrieve customer context using Twilio Conversation Memory.\n  Covers Memory Store provisioning, profile management, traits, observations,\n  conversation summaries, and semantic Recall. Use this skill to give AI agents\n  or human agents persistent memory of customer interactions across sessions\n  and channels.\n---\n\n## Overview\n\nConversation Memory gives your application persistent customer memory. Observations (what happened) and traits (who the customer is) are written automatically from conversations flowing through Conversation Orchestrator\u002FOrchestrator — or posted directly if you run your own extraction. Retrieve relevant context via Recall before responding.\n\n```\nConversation Orchestrator\u002FOrchestrator conversation → auto-extracted observations & summaries → Memory Store\nYour App → Recall → relevant context injected into LLM prompt\n```\n\n**All Conversation Memory APIs are on `memory.twilio.com`.** Observations, traits, profiles, summaries — everything is on the same host.\n\n**Auth: Basic Auth** — `TWILIO_ACCOUNT_SID` and `TWILIO_AUTH_TOKEN`.\n\n---\n\n## Prerequisites\n\n- Twilio account with Conversation Memory access (requires enablement)\n  — New to Twilio? See `twilio-account-setup`\n- `TWILIO_ACCOUNT_SID` and `TWILIO_AUTH_TOKEN` — see `twilio-iam-auth-setup`\n- **Memory Store must be created before creating a Conversations Service in Conversation Orchestrator\u002FOrchestrator** — the store SID is required in the conversation config\n- For conversation orchestration: `twilio-conversation-orchestrator`\n\n---\n\n## Quickstart\n\n### Step 1 — Create a Memory Store\n\nDo this before setting up Conversation Orchestrator\u002FOrchestrator. The Memory Store SID goes into your conversation service config.\n\n**Python**\n```python\nimport os, requests\n\naccount_sid = os.environ[\"TWILIO_ACCOUNT_SID\"]\nauth_token = os.environ[\"TWILIO_AUTH_TOKEN\"]\n\nstore = requests.post(\n    \"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\",\n    auth=(account_sid, auth_token),\n    json={\n        \"uniqueName\": \"my-app-memory\",\n        \"friendlyName\": \"My App Memory Store\"\n    }\n).json()\n\nmemory_store_sid = store[\"sid\"]\nprint(memory_store_sid)\n```\n\n**Node.js**\n```javascript\nconst accountSid = process.env.TWILIO_ACCOUNT_SID;\nconst authToken = process.env.TWILIO_AUTH_TOKEN;\n\nconst store = await fetch(\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\", {\n    method: \"POST\",\n    headers: {\n        \"Authorization\": \"Basic \" + btoa(`${accountSid}:${authToken}`),\n        \"Content-Type\": \"application\u002Fjson\",\n    },\n    body: JSON.stringify({\n        uniqueName: \"my-app-memory\",\n        friendlyName: \"My App Memory Store\",\n    }),\n}).then(r => r.json());\n\nconst memoryStoreSid = store.sid;\n```\n\nUse `memory_store_sid` when creating your Conversations Service in Conversation Orchestrator\u002FOrchestrator. The two must be linked for automatic observation and summary extraction to work.\n\n### Step 2 — Profiles\n\nProfiles are **created automatically** when conversations flow through Conversation Orchestrator\u002FOrchestrator — the conversation config determines how participants are resolved into profiles. You can also create or enrich profiles manually using traits.\n\n**Create a profile manually with traits:**\n\n**Python**\n```python\nprofile = requests.post(\n    f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{memory_store_sid}\u002FProfiles\",\n    auth=(account_sid, auth_token),\n    json={\n        \"traits\": {\n            \"Contact\": {\n                \"phone\": \"+15558675310\",\n                \"firstName\": \"Alyssa\",\n                \"lastName\": \"Mock\",\n                \"email\": \"alyssa@example.com\"\n            }\n        }\n    }\n).json()\n\nprofile_id = profile[\"id\"]\n```\n\n**Node.js**\n```javascript\nconst profile = await fetch(\n    `https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F${memoryStoreSid}\u002FProfiles`,\n    {\n        method: \"POST\",\n        headers: {\n            \"Authorization\": \"Basic \" + btoa(`${accountSid}:${authToken}`),\n            \"Content-Type\": \"application\u002Fjson\",\n        },\n        body: JSON.stringify({\n            traits: {\n                Contact: {\n                    phone: \"+15558675310\",\n                    firstName: \"Alyssa\",\n                    lastName: \"Mock\",\n                    email: \"alyssa@example.com\",\n                }\n            }\n        }),\n    }\n).then(r => r.json());\n\nconst profileId = profile.id;\n```\n\n**Look up a profile by phone number** (for inbound calls where you only have the caller's number):\n\n**Python**\n```python\nlookup = requests.post(\n    f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{memory_store_sid}\u002FProfiles\u002FLookup\",\n    auth=(account_sid, auth_token),\n    json={\"idType\": \"phone\", \"value\": \"+15558675310\"}\n).json()\n\nprofile_id = lookup[\"profiles\"][0][\"id\"] if lookup.get(\"profiles\") else None\n```\n\n### Step 3 — Observations\n\nObservations are **extracted automatically** from conversations when a conversation becomes inactive or is closed, based on your conversation config. You don't need to write them manually for Conversation Orchestrator-managed conversations.\n\n**If you run your own extraction** (custom pipeline outside Conversation Orchestrator), post results directly:\n\n**Python**\n```python\nrequests.post(\n    f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{memory_store_sid}\u002FProfiles\u002F{profile_id}\u002FObservations\",\n    auth=(account_sid, auth_token),\n    json={\n        \"observations\": [\n            {\n                \"content\": \"Customer asked about order #4521. Wants expedited shipping. Prefers SMS updates.\",\n                \"source\": \"custom_extraction\",\n                \"occurredAt\": \"2026-04-20T14:30:00Z\",\n                \"conversationIds\": [conversation_sid]\n            }\n        ]\n    }\n)\n```\n\n**Node.js**\n```javascript\nawait fetch(\n    `https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F${memoryStoreSid}\u002FProfiles\u002F${profileId}\u002FObservations`,\n    {\n        method: \"POST\",\n        headers: {\n            \"Authorization\": \"Basic \" + btoa(`${accountSid}:${authToken}`),\n            \"Content-Type\": \"application\u002Fjson\",\n        },\n        body: JSON.stringify({\n            observations: [{\n                content: \"Customer asked about order #4521. Wants expedited shipping. Prefers SMS updates.\",\n                source: \"custom_extraction\",\n                occurredAt: new Date().toISOString(),\n                conversationIds: [conversationSid],\n            }]\n        }),\n    }\n);\n```\n\nBatch up to 10 observations in one request.\n\n### Step 4 — Recall Context Before Responding\n\nRecall runs hybrid lexical + semantic search and returns the most relevant observations and summaries for an LLM prompt.\n\n**Recommended: pass a `conversationId` from Conversation Orchestrator\u002FOrchestrator.** Recall builds a contextually relevant query from the active conversation automatically — no need to craft one yourself.\n\n**Python**\n```python\nrecall = requests.post(\n    f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{memory_store_sid}\u002FProfiles\u002F{profile_id}\u002FRecall\",\n    auth=(account_sid, auth_token),\n    json={\n        \"conversationId\": orchestrator_conversation_sid,\n        \"observationsLimit\": 10,\n        \"summariesLimit\": 3,\n    }\n).json()\n\nobservations = \"\\n\".join(o[\"content\"] for o in recall.get(\"observations\", []))\nsummaries = \"\\n\".join(s[\"content\"] for s in recall.get(\"summaries\", []))\n\nsystem_prompt = f\"\"\"You are a helpful support agent.\n\nCustomer history:\n{observations}\n\nRecent summaries:\n{summaries}\"\"\"\n```\n\n**Node.js**\n```javascript\nconst recall = await fetch(\n    `https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F${memoryStoreSid}\u002FProfiles\u002F${profileId}\u002FRecall`,\n    {\n        method: \"POST\",\n        headers: {\n            \"Authorization\": \"Basic \" + btoa(`${accountSid}:${authToken}`),\n            \"Content-Type\": \"application\u002Fjson\",\n        },\n        body: JSON.stringify({\n            conversationId: orchestratorConversationSid,\n            observationsLimit: 10,\n            summariesLimit: 3,\n        }),\n    }\n).then(r => r.json());\n\nconst context = [\n    ...recall.observations.map(o => o.content),\n    ...recall.summaries.map(s => s.content),\n].join(\"\\n\");\n```\n\n**Other Recall modes:**\n\n| Mode | How | When to use |\n|------|-----|-------------|\n| Conversation ID (recommended) | `\"conversationId\": orchestrator_sid` | Active Conversation Orchestrator\u002FOrchestrator conversation — query is generated from conversation context |\n| Custom query | `\"query\": \"your question\"` | Custom pipelines outside Conversation Orchestrator, or when you need precise control over relevance |\n| No query | Omit both `query` and `conversationId` | Returns most recent observations in chronological order — useful for loading history at session start |\n\n---\n\n## Key Patterns\n\n### Trait Groups\n\nTraits are organized into named groups. The `Contact` group is the standard identity anchor — its fields are promoted to profile identifiers for lookup.\n\n| Group | Fields | Use |\n|-------|--------|-----|\n| `Contact` | phone, email, firstName, lastName | Identity anchor — always include |\n| `Account` | accountNumber, tier, region | Business account data |\n| `Support` | disposition, caseId, lastIssueType | Support history |\n\nDefine your own groups for domain-specific data.\n\n### Summaries\n\nSummaries are written automatically at conversation close or when a conversation goes inactive, based on your conversation config — the same trigger as observations. You can also write them manually:\n\n**Python**\n```python\nrequests.post(\n    f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{memory_store_sid}\u002FProfiles\u002F{profile_id}\u002FConversationSummaries\",\n    auth=(account_sid, auth_token),\n    json={\n        \"conversationId\": conversation_sid,\n        \"content\": \"Customer called about order #4521. Resolved: approved expedited upgrade.\",\n        \"source\": \"manual\"\n    }\n)\n```\n\nSummaries are returned in the `summaries` array of Recall results.\n\n### Voice Agent Integration\n\nRetrieve memory at call start, store observations at call end. For voice AI agents on ConversationRelay.\n\n**Python (WebSocket handler)**\n```python\nasync def handle_call(websocket):\n    setup = json.loads(await websocket.recv())\n    caller = setup.get(\"from\", \"unknown\")\n\n    # Look up profile by caller phone\n    lookup = requests.post(\n        f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{MEMORY_STORE_SID}\u002FProfiles\u002FLookup\",\n        auth=(ACCOUNT_SID, AUTH_TOKEN),\n        json={\"idType\": \"phone\", \"value\": caller}\n    ).json()\n    profiles = lookup.get(\"profiles\", [])\n    profile_id = profiles[0][\"id\"] if profiles else None\n\n    context = \"\"\n    if profile_id:\n        recall = requests.post(\n            f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{MEMORY_STORE_SID}\u002FProfiles\u002F{profile_id}\u002FRecall\",\n            auth=(ACCOUNT_SID, AUTH_TOKEN),\n            json={\"observationsLimit\": 5, \"summariesLimit\": 2}\n        ).json()\n        context = \"\\n\".join(o[\"content\"] for o in recall.get(\"observations\", []))\n\n    system_prompt = f\"You are a helpful agent.\\n\\nCustomer history:\\n{context}\" if context else \"You are a helpful agent.\"\n\n    # ... handle conversation ...\n\n    # Store observation at end if running custom extraction\n    if profile_id:\n        requests.post(\n            f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{MEMORY_STORE_SID}\u002FProfiles\u002F{profile_id}\u002FObservations\",\n            auth=(ACCOUNT_SID, AUTH_TOKEN),\n            json={\"observations\": [{\"content\": call_summary, \"source\": \"voice_agent\", \"conversationIds\": [orchestrator_conversation_sid]}]}\n        )\n```\n\n### Multi-Tenant (ISV) Pattern\n\nUse one Memory Store per client. The `uniqueName` doubles as a namespace.\n\n```python\n# At client onboarding\nstore = requests.post(\n    \"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\",\n    auth=(account_sid, auth_token),\n    json={\"uniqueName\": f\"client-{client_id}\", \"friendlyName\": client_name}\n).json()\n# Store store[\"sid\"] in your tenant config — pass it to Conversation Orchestrator conversation service setup\n```\n\n---\n\n## CANNOT\n\n- **Cannot create Conversation Orchestrator before Memory Store** — Create Memory Store first. Its SID is required when creating the Conversations Service. Reversing this order breaks the linkage.\n- **Cannot extract observations mid-conversation** — Automatic extraction happens on conversation close or inactive. For real-time writing, post directly to the Observations endpoint.\n- **Cannot read observations immediately after write** — Eventual consistency. Allow ~2 seconds after write before querying Recall.\n- **Cannot exceed 15 Memory Stores per account** — ISVs with more than 15 tenants should use sub-accounts\n- **Cannot detect misconfigured linkages** — If Memory Store is not correctly linked in Conversation Orchestrator config, observations are silently not extracted. See `twilio-debugging-observability`.\n- **Cannot recover deleted profiles** — Profile deletion is irreversible, permanent\n- **Cannot exceed 20 observations per Recall query** — `observationsLimit` max 20, default 5. `summariesLimit` and `communicationsLimit` similar.\n- **Cannot batch more than 10 observations per request** — Hard limit on batch writes\n\n---\n\n## Next Steps\n\n- **Set up Conversation Orchestrator conversations:** `twilio-conversation-orchestrator`\n- **Add real-time intelligence:** `twilio-conversation-intelligence`\n- **Enterprise knowledge retrieval (scripts, offers, policies):** `twilio-enterprise-knowledge`\n- **Voice agent setup:** `twilio-voice-conversation-relay`\n- **Debug integration issues:** `twilio-debugging-observability`\n",{"data":37,"body":38},{"name":4,"description":6},{"type":39,"children":40},"root",[41,50,56,69,88,113,117,123,182,185,191,198,203,211,365,373,928,941,947,959,967,974,1104,1111,1674,1684,1691,1751,1757,1769,1779,1786,1901,1908,2376,2381,2387,2392,2410,2417,2576,2583,3194,3202,3309,3312,3318,3324,3337,3429,3434,3439,3444,3451,3525,3537,3543,3548,3556,3831,3837,3850,3909,3912,3918,4030,4033,4039,4116],{"type":42,"tag":43,"props":44,"children":46},"element","h2",{"id":45},"overview",[47],{"type":48,"value":49},"text","Overview",{"type":42,"tag":51,"props":52,"children":53},"p",{},[54],{"type":48,"value":55},"Conversation Memory gives your application persistent customer memory. Observations (what happened) and traits (who the customer is) are written automatically from conversations flowing through Conversation Orchestrator\u002FOrchestrator — or posted directly if you run your own extraction. Retrieve relevant context via Recall before responding.",{"type":42,"tag":57,"props":58,"children":62},"pre",{"className":59,"code":61,"language":48},[60],"language-text","Conversation Orchestrator\u002FOrchestrator conversation → auto-extracted observations & summaries → Memory Store\nYour App → Recall → relevant context injected into LLM prompt\n",[63],{"type":42,"tag":64,"props":65,"children":67},"code",{"__ignoreMap":66},"",[68],{"type":48,"value":61},{"type":42,"tag":51,"props":70,"children":71},{},[72,86],{"type":42,"tag":73,"props":74,"children":75},"strong",{},[76,78,84],{"type":48,"value":77},"All Conversation Memory APIs are on ",{"type":42,"tag":64,"props":79,"children":81},{"className":80},[],[82],{"type":48,"value":83},"memory.twilio.com",{"type":48,"value":85},".",{"type":48,"value":87}," Observations, traits, profiles, summaries — everything is on the same host.",{"type":42,"tag":51,"props":89,"children":90},{},[91,96,98,104,106,112],{"type":42,"tag":73,"props":92,"children":93},{},[94],{"type":48,"value":95},"Auth: Basic Auth",{"type":48,"value":97}," — ",{"type":42,"tag":64,"props":99,"children":101},{"className":100},[],[102],{"type":48,"value":103},"TWILIO_ACCOUNT_SID",{"type":48,"value":105}," and ",{"type":42,"tag":64,"props":107,"children":109},{"className":108},[],[110],{"type":48,"value":111},"TWILIO_AUTH_TOKEN",{"type":48,"value":85},{"type":42,"tag":114,"props":115,"children":116},"hr",{},[],{"type":42,"tag":43,"props":118,"children":120},{"id":119},"prerequisites",[121],{"type":48,"value":122},"Prerequisites",{"type":42,"tag":124,"props":125,"children":126},"ul",{},[127,139,161,171],{"type":42,"tag":128,"props":129,"children":130},"li",{},[131,133],{"type":48,"value":132},"Twilio account with Conversation Memory access (requires enablement)\n— New to Twilio? See ",{"type":42,"tag":64,"props":134,"children":136},{"className":135},[],[137],{"type":48,"value":138},"twilio-account-setup",{"type":42,"tag":128,"props":140,"children":141},{},[142,147,148,153,155],{"type":42,"tag":64,"props":143,"children":145},{"className":144},[],[146],{"type":48,"value":103},{"type":48,"value":105},{"type":42,"tag":64,"props":149,"children":151},{"className":150},[],[152],{"type":48,"value":111},{"type":48,"value":154}," — see ",{"type":42,"tag":64,"props":156,"children":158},{"className":157},[],[159],{"type":48,"value":160},"twilio-iam-auth-setup",{"type":42,"tag":128,"props":162,"children":163},{},[164,169],{"type":42,"tag":73,"props":165,"children":166},{},[167],{"type":48,"value":168},"Memory Store must be created before creating a Conversations Service in Conversation Orchestrator\u002FOrchestrator",{"type":48,"value":170}," — the store SID is required in the conversation config",{"type":42,"tag":128,"props":172,"children":173},{},[174,176],{"type":48,"value":175},"For conversation orchestration: ",{"type":42,"tag":64,"props":177,"children":179},{"className":178},[],[180],{"type":48,"value":181},"twilio-conversation-orchestrator",{"type":42,"tag":114,"props":183,"children":184},{},[],{"type":42,"tag":43,"props":186,"children":188},{"id":187},"quickstart",[189],{"type":48,"value":190},"Quickstart",{"type":42,"tag":192,"props":193,"children":195},"h3",{"id":194},"step-1-create-a-memory-store",[196],{"type":48,"value":197},"Step 1 — Create a Memory Store",{"type":42,"tag":51,"props":199,"children":200},{},[201],{"type":48,"value":202},"Do this before setting up Conversation Orchestrator\u002FOrchestrator. The Memory Store SID goes into your conversation service config.",{"type":42,"tag":51,"props":204,"children":205},{},[206],{"type":42,"tag":73,"props":207,"children":208},{},[209],{"type":48,"value":210},"Python",{"type":42,"tag":57,"props":212,"children":216},{"className":213,"code":214,"language":215,"meta":66,"style":66},"language-python shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","import os, requests\n\naccount_sid = os.environ[\"TWILIO_ACCOUNT_SID\"]\nauth_token = os.environ[\"TWILIO_AUTH_TOKEN\"]\n\nstore = requests.post(\n    \"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\",\n    auth=(account_sid, auth_token),\n    json={\n        \"uniqueName\": \"my-app-memory\",\n        \"friendlyName\": \"My App Memory Store\"\n    }\n).json()\n\nmemory_store_sid = store[\"sid\"]\nprint(memory_store_sid)\n","python",[217],{"type":42,"tag":64,"props":218,"children":219},{"__ignoreMap":66},[220,231,241,250,259,267,276,285,294,303,312,321,330,339,347,356],{"type":42,"tag":221,"props":222,"children":225},"span",{"class":223,"line":224},"line",1,[226],{"type":42,"tag":221,"props":227,"children":228},{},[229],{"type":48,"value":230},"import os, requests\n",{"type":42,"tag":221,"props":232,"children":234},{"class":223,"line":233},2,[235],{"type":42,"tag":221,"props":236,"children":238},{"emptyLinePlaceholder":237},true,[239],{"type":48,"value":240},"\n",{"type":42,"tag":221,"props":242,"children":244},{"class":223,"line":243},3,[245],{"type":42,"tag":221,"props":246,"children":247},{},[248],{"type":48,"value":249},"account_sid = os.environ[\"TWILIO_ACCOUNT_SID\"]\n",{"type":42,"tag":221,"props":251,"children":253},{"class":223,"line":252},4,[254],{"type":42,"tag":221,"props":255,"children":256},{},[257],{"type":48,"value":258},"auth_token = os.environ[\"TWILIO_AUTH_TOKEN\"]\n",{"type":42,"tag":221,"props":260,"children":262},{"class":223,"line":261},5,[263],{"type":42,"tag":221,"props":264,"children":265},{"emptyLinePlaceholder":237},[266],{"type":48,"value":240},{"type":42,"tag":221,"props":268,"children":270},{"class":223,"line":269},6,[271],{"type":42,"tag":221,"props":272,"children":273},{},[274],{"type":48,"value":275},"store = requests.post(\n",{"type":42,"tag":221,"props":277,"children":279},{"class":223,"line":278},7,[280],{"type":42,"tag":221,"props":281,"children":282},{},[283],{"type":48,"value":284},"    \"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\",\n",{"type":42,"tag":221,"props":286,"children":288},{"class":223,"line":287},8,[289],{"type":42,"tag":221,"props":290,"children":291},{},[292],{"type":48,"value":293},"    auth=(account_sid, 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... handle conversation ...\n\n    # Store observation at end if running custom extraction\n    if profile_id:\n        requests.post(\n            f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{MEMORY_STORE_SID}\u002FProfiles\u002F{profile_id}\u002FObservations\",\n            auth=(ACCOUNT_SID, AUTH_TOKEN),\n            json={\"observations\": [{\"content\": call_summary, \"source\": \"voice_agent\", \"conversationIds\": [orchestrator_conversation_sid]}]}\n        )\n",[3560],{"type":42,"tag":64,"props":3561,"children":3562},{"__ignoreMap":66},[3563,3571,3579,3587,3594,3602,3610,3618,3626,3634,3642,3650,3658,3665,3673,3681,3689,3697,3705,3713,3721,3729,3736,3745,3753,3762,3770,3779,3787,3796,3805,3813,3822],{"type":42,"tag":221,"props":3564,"children":3565},{"class":223,"line":224},[3566],{"type":42,"tag":221,"props":3567,"children":3568},{},[3569],{"type":48,"value":3570},"async def handle_call(websocket):\n",{"type":42,"tag":221,"props":3572,"children":3573},{"class":223,"line":233},[3574],{"type":42,"tag":221,"props":3575,"children":3576},{},[3577],{"type":48,"value":3578},"    setup = json.loads(await websocket.recv())\n",{"type":42,"tag":221,"props":3580,"children":3581},{"class":223,"line":243},[3582],{"type":42,"tag":221,"props":3583,"children":3584},{},[3585],{"type":48,"value":3586},"    caller = setup.get(\"from\", \"unknown\")\n",{"type":42,"tag":221,"props":3588,"children":3589},{"class":223,"line":252},[3590],{"type":42,"tag":221,"props":3591,"children":3592},{"emptyLinePlaceholder":237},[3593],{"type":48,"value":240},{"type":42,"tag":221,"props":3595,"children":3596},{"class":223,"line":261},[3597],{"type":42,"tag":221,"props":3598,"children":3599},{},[3600],{"type":48,"value":3601},"    # Look up profile by caller phone\n",{"type":42,"tag":221,"props":3603,"children":3604},{"class":223,"line":269},[3605],{"type":42,"tag":221,"props":3606,"children":3607},{},[3608],{"type":48,"value":3609},"    lookup = requests.post(\n",{"type":42,"tag":221,"props":3611,"children":3612},{"class":223,"line":278},[3613],{"type":42,"tag":221,"props":3614,"children":3615},{},[3616],{"type":48,"value":3617},"        f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{MEMORY_STORE_SID}\u002FProfiles\u002FLookup\",\n",{"type":42,"tag":221,"props":3619,"children":3620},{"class":223,"line":287},[3621],{"type":42,"tag":221,"props":3622,"children":3623},{},[3624],{"type":48,"value":3625},"        auth=(ACCOUNT_SID, AUTH_TOKEN),\n",{"type":42,"tag":221,"props":3627,"children":3628},{"class":223,"line":296},[3629],{"type":42,"tag":221,"props":3630,"children":3631},{},[3632],{"type":48,"value":3633},"        json={\"idType\": \"phone\", \"value\": caller}\n",{"type":42,"tag":221,"props":3635,"children":3636},{"class":223,"line":305},[3637],{"type":42,"tag":221,"props":3638,"children":3639},{},[3640],{"type":48,"value":3641},"    ).json()\n",{"type":42,"tag":221,"props":3643,"children":3644},{"class":223,"line":314},[3645],{"type":42,"tag":221,"props":3646,"children":3647},{},[3648],{"type":48,"value":3649},"    profiles = lookup.get(\"profiles\", [])\n",{"type":42,"tag":221,"props":3651,"children":3652},{"class":223,"line":323},[3653],{"type":42,"tag":221,"props":3654,"children":3655},{},[3656],{"type":48,"value":3657},"    profile_id = profiles[0][\"id\"] if profiles else None\n",{"type":42,"tag":221,"props":3659,"children":3660},{"class":223,"line":332},[3661],{"type":42,"tag":221,"props":3662,"children":3663},{"emptyLinePlaceholder":237},[3664],{"type":48,"value":240},{"type":42,"tag":221,"props":3666,"children":3667},{"class":223,"line":341},[3668],{"type":42,"tag":221,"props":3669,"children":3670},{},[3671],{"type":48,"value":3672},"    context = \"\"\n",{"type":42,"tag":221,"props":3674,"children":3675},{"class":223,"line":349},[3676],{"type":42,"tag":221,"props":3677,"children":3678},{},[3679],{"type":48,"value":3680},"    if profile_id:\n",{"type":42,"tag":221,"props":3682,"children":3683},{"class":223,"line":358},[3684],{"type":42,"tag":221,"props":3685,"children":3686},{},[3687],{"type":48,"value":3688},"        recall = requests.post(\n",{"type":42,"tag":221,"props":3690,"children":3691},{"class":223,"line":1552},[3692],{"type":42,"tag":221,"props":3693,"children":3694},{},[3695],{"type":48,"value":3696},"            f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{MEMORY_STORE_SID}\u002FProfiles\u002F{profile_id}\u002FRecall\",\n",{"type":42,"tag":221,"props":3698,"children":3699},{"class":223,"line":1560},[3700],{"type":42,"tag":221,"props":3701,"children":3702},{},[3703],{"type":48,"value":3704},"            auth=(ACCOUNT_SID, AUTH_TOKEN),\n",{"type":42,"tag":221,"props":3706,"children":3707},{"class":223,"line":1577},[3708],{"type":42,"tag":221,"props":3709,"children":3710},{},[3711],{"type":48,"value":3712},"            json={\"observationsLimit\": 5, \"summariesLimit\": 2}\n",{"type":42,"tag":221,"props":3714,"children":3715},{"class":223,"line":1585},[3716],{"type":42,"tag":221,"props":3717,"children":3718},{},[3719],{"type":48,"value":3720},"        ).json()\n",{"type":42,"tag":221,"props":3722,"children":3723},{"class":223,"line":1633},[3724],{"type":42,"tag":221,"props":3725,"children":3726},{},[3727],{"type":48,"value":3728},"        context = \"\\n\".join(o[\"content\"] for o in recall.get(\"observations\", []))\n",{"type":42,"tag":221,"props":3730,"children":3731},{"class":223,"line":1641},[3732],{"type":42,"tag":221,"props":3733,"children":3734},{"emptyLinePlaceholder":237},[3735],{"type":48,"value":240},{"type":42,"tag":221,"props":3737,"children":3739},{"class":223,"line":3738},23,[3740],{"type":42,"tag":221,"props":3741,"children":3742},{},[3743],{"type":48,"value":3744},"    system_prompt = f\"You are a helpful agent.\\n\\nCustomer history:\\n{context}\" if context else \"You are a helpful agent.\"\n",{"type":42,"tag":221,"props":3746,"children":3748},{"class":223,"line":3747},24,[3749],{"type":42,"tag":221,"props":3750,"children":3751},{"emptyLinePlaceholder":237},[3752],{"type":48,"value":240},{"type":42,"tag":221,"props":3754,"children":3756},{"class":223,"line":3755},25,[3757],{"type":42,"tag":221,"props":3758,"children":3759},{},[3760],{"type":48,"value":3761},"    # ... handle conversation ...\n",{"type":42,"tag":221,"props":3763,"children":3765},{"class":223,"line":3764},26,[3766],{"type":42,"tag":221,"props":3767,"children":3768},{"emptyLinePlaceholder":237},[3769],{"type":48,"value":240},{"type":42,"tag":221,"props":3771,"children":3773},{"class":223,"line":3772},27,[3774],{"type":42,"tag":221,"props":3775,"children":3776},{},[3777],{"type":48,"value":3778},"    # Store observation at end if running custom extraction\n",{"type":42,"tag":221,"props":3780,"children":3782},{"class":223,"line":3781},28,[3783],{"type":42,"tag":221,"props":3784,"children":3785},{},[3786],{"type":48,"value":3680},{"type":42,"tag":221,"props":3788,"children":3790},{"class":223,"line":3789},29,[3791],{"type":42,"tag":221,"props":3792,"children":3793},{},[3794],{"type":48,"value":3795},"        requests.post(\n",{"type":42,"tag":221,"props":3797,"children":3799},{"class":223,"line":3798},30,[3800],{"type":42,"tag":221,"props":3801,"children":3802},{},[3803],{"type":48,"value":3804},"            f\"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\u002F{MEMORY_STORE_SID}\u002FProfiles\u002F{profile_id}\u002FObservations\",\n",{"type":42,"tag":221,"props":3806,"children":3808},{"class":223,"line":3807},31,[3809],{"type":42,"tag":221,"props":3810,"children":3811},{},[3812],{"type":48,"value":3704},{"type":42,"tag":221,"props":3814,"children":3816},{"class":223,"line":3815},32,[3817],{"type":42,"tag":221,"props":3818,"children":3819},{},[3820],{"type":48,"value":3821},"            json={\"observations\": [{\"content\": call_summary, \"source\": \"voice_agent\", \"conversationIds\": [orchestrator_conversation_sid]}]}\n",{"type":42,"tag":221,"props":3823,"children":3825},{"class":223,"line":3824},33,[3826],{"type":42,"tag":221,"props":3827,"children":3828},{},[3829],{"type":48,"value":3830},"        )\n",{"type":42,"tag":192,"props":3832,"children":3834},{"id":3833},"multi-tenant-isv-pattern",[3835],{"type":48,"value":3836},"Multi-Tenant (ISV) Pattern",{"type":42,"tag":51,"props":3838,"children":3839},{},[3840,3842,3848],{"type":48,"value":3841},"Use one Memory Store per client. The ",{"type":42,"tag":64,"props":3843,"children":3845},{"className":3844},[],[3846],{"type":48,"value":3847},"uniqueName",{"type":48,"value":3849}," doubles as a namespace.",{"type":42,"tag":57,"props":3851,"children":3853},{"className":213,"code":3852,"language":215,"meta":66,"style":66},"# At client onboarding\nstore = requests.post(\n    \"https:\u002F\u002Fmemory.twilio.com\u002Fv1\u002FServices\",\n    auth=(account_sid, auth_token),\n    json={\"uniqueName\": f\"client-{client_id}\", \"friendlyName\": client_name}\n).json()\n# Store store[\"sid\"] in your tenant config — pass it to Conversation Orchestrator conversation service setup\n",[3854],{"type":42,"tag":64,"props":3855,"children":3856},{"__ignoreMap":66},[3857,3865,3872,3879,3886,3894,3901],{"type":42,"tag":221,"props":3858,"children":3859},{"class":223,"line":224},[3860],{"type":42,"tag":221,"props":3861,"children":3862},{},[3863],{"type":48,"value":3864},"# At client onboarding\n",{"type":42,"tag":221,"props":3866,"children":3867},{"class":223,"line":233},[3868],{"type":42,"tag":221,"props":3869,"children":3870},{},[3871],{"type":48,"value":275},{"type":42,"tag":221,"props":3873,"children":3874},{"class":223,"line":243},[3875],{"type":42,"tag":221,"props":3876,"children":3877},{},[3878],{"type":48,"value":284},{"type":42,"tag":221,"props":3880,"children":3881},{"class":223,"line":252},[3882],{"type":42,"tag":221,"props":3883,"children":3884},{},[3885],{"type":48,"value":293},{"type":42,"tag":221,"props":3887,"children":3888},{"class":223,"line":261},[3889],{"type":42,"tag":221,"props":3890,"children":3891},{},[3892],{"type":48,"value":3893},"    json={\"uniqueName\": f\"client-{client_id}\", \"friendlyName\": client_name}\n",{"type":42,"tag":221,"props":3895,"children":3896},{"class":223,"line":269},[3897],{"type":42,"tag":221,"props":3898,"children":3899},{},[3900],{"type":48,"value":338},{"type":42,"tag":221,"props":3902,"children":3903},{"class":223,"line":278},[3904],{"type":42,"tag":221,"props":3905,"children":3906},{},[3907],{"type":48,"value":3908},"# Store store[\"sid\"] in your tenant config — pass it to Conversation Orchestrator conversation service setup\n",{"type":42,"tag":114,"props":3910,"children":3911},{},[],{"type":42,"tag":43,"props":3913,"children":3915},{"id":3914},"cannot",[3916],{"type":48,"value":3917},"CANNOT",{"type":42,"tag":124,"props":3919,"children":3920},{},[3921,3931,3941,3951,3961,3978,3988,4020],{"type":42,"tag":128,"props":3922,"children":3923},{},[3924,3929],{"type":42,"tag":73,"props":3925,"children":3926},{},[3927],{"type":48,"value":3928},"Cannot create Conversation Orchestrator before Memory Store",{"type":48,"value":3930}," — Create Memory Store first. Its SID is required when creating the Conversations Service. Reversing this order breaks the linkage.",{"type":42,"tag":128,"props":3932,"children":3933},{},[3934,3939],{"type":42,"tag":73,"props":3935,"children":3936},{},[3937],{"type":48,"value":3938},"Cannot extract observations mid-conversation",{"type":48,"value":3940}," — Automatic extraction happens on conversation close or inactive. For real-time writing, post directly to the Observations endpoint.",{"type":42,"tag":128,"props":3942,"children":3943},{},[3944,3949],{"type":42,"tag":73,"props":3945,"children":3946},{},[3947],{"type":48,"value":3948},"Cannot read observations immediately after write",{"type":48,"value":3950}," — Eventual consistency. Allow ~2 seconds after write before querying Recall.",{"type":42,"tag":128,"props":3952,"children":3953},{},[3954,3959],{"type":42,"tag":73,"props":3955,"children":3956},{},[3957],{"type":48,"value":3958},"Cannot exceed 15 Memory Stores per account",{"type":48,"value":3960}," — ISVs with more than 15 tenants should use sub-accounts",{"type":42,"tag":128,"props":3962,"children":3963},{},[3964,3969,3971,3977],{"type":42,"tag":73,"props":3965,"children":3966},{},[3967],{"type":48,"value":3968},"Cannot detect misconfigured linkages",{"type":48,"value":3970}," — If Memory Store is not correctly linked in Conversation Orchestrator config, observations are silently not extracted. 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Biases towards retrieval from Cloudflare docs over pre-trained knowledge.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4176,4177,4180,4183,4186],{"name":4149,"slug":4150,"type":15},{"name":4178,"slug":4179,"type":15},"Cloudflare Workers","cloudflare-workers",{"name":4181,"slug":4182,"type":15},"SDK","sdk",{"name":4184,"slug":4185,"type":15},"Serverless","serverless",{"name":4187,"slug":4188,"type":15},"WebSockets","websockets","2026-04-06T18:39:51.717063",{"slug":4191,"name":4191,"fn":4192,"description":4193,"org":4194,"tags":4195,"stars":25,"repoUrl":26,"updatedAt":4211},"ai-elements","build chat UIs with AI Elements","AI Elements component library guidance — pre-built React components for AI interfaces built on shadcn\u002Fui. Use when building chat UIs, message displays, tool call rendering, streaming responses, reasoning panels, or any AI-native interface with the AI SDK.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4196,4199,4202,4205,4208],{"name":4197,"slug":4198,"type":15},"Frontend","frontend",{"name":4200,"slug":4201,"type":15},"React","react",{"name":4203,"slug":4204,"type":15},"shadcn\u002Fui","shadcn-ui",{"name":4206,"slug":4207,"type":15},"UI Components","ui-components",{"name":4209,"slug":4210,"type":15},"Vercel","vercel","2026-04-06T18:40:59.619419",{"slug":4213,"name":4213,"fn":4214,"description":4215,"org":4216,"tags":4217,"stars":25,"repoUrl":26,"updatedAt":4231},"ai-gateway","configure Vercel AI Gateway","Vercel AI Gateway expert guidance. Use when configuring model routing, provider failover, cost tracking, or managing multiple AI providers through a unified API.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4218,4221,4224,4227,4230],{"name":4219,"slug":4220,"type":15},"AI Infrastructure","ai-infrastructure",{"name":4222,"slug":4223,"type":15},"Cost Optimization","cost-optimization",{"name":4225,"slug":4226,"type":15},"LLM","llm",{"name":4228,"slug":4229,"type":15},"Performance","performance",{"name":4209,"slug":4210,"type":15},"2026-04-06T18:40:44.377464",{"slug":4233,"name":4233,"fn":4234,"description":4235,"org":4236,"tags":4237,"stars":25,"repoUrl":26,"updatedAt":4243},"ai-generation-persistence","implement persistence patterns for AI generations","AI generation persistence patterns — unique IDs, addressable URLs, database storage, and cost tracking for every LLM generation",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4238,4239,4242],{"name":4222,"slug":4223,"type":15},{"name":4240,"slug":4241,"type":15},"Database","database",{"name":4225,"slug":4226,"type":15},"2026-04-06T18:41:08.513425",600,{"items":4246,"total":4443},[4247,4268,4291,4308,4324,4341,4360,4372,4386,4400,4412,4427],{"slug":4248,"name":4248,"fn":4249,"description":4250,"org":4251,"tags":4252,"stars":4265,"repoUrl":4266,"updatedAt":4267},"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},[4253,4256,4259,4262],{"name":4254,"slug":4255,"type":15},"Documents","documents",{"name":4257,"slug":4258,"type":15},"Healthcare","healthcare",{"name":4260,"slug":4261,"type":15},"Insurance","insurance",{"name":4263,"slug":4264,"type":15},"Regulatory Compliance","regulatory-compliance",28169,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fopenai-agents-python","2026-04-16T05:11:39.180399",{"slug":4269,"name":4269,"fn":4270,"description":4271,"org":4272,"tags":4273,"stars":4288,"repoUrl":4289,"updatedAt":4290},"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},[4274,4277,4279,4282,4285],{"name":4275,"slug":4276,"type":15},".NET","dotnet",{"name":4278,"slug":4269,"type":15},"ASP.NET Core",{"name":4280,"slug":4281,"type":15},"Blazor","blazor",{"name":4283,"slug":4284,"type":15},"C#","csharp",{"name":4286,"slug":4287,"type":15},"Web Development","web-development",23787,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills","2026-04-12T05:07:02.819491",{"slug":4292,"name":4292,"fn":4293,"description":4294,"org":4295,"tags":4296,"stars":4288,"repoUrl":4289,"updatedAt":4307},"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},[4297,4300,4303,4306],{"name":4298,"slug":4299,"type":15},"Apps SDK","apps-sdk",{"name":4301,"slug":4302,"type":15},"ChatGPT","chatgpt",{"name":4304,"slug":4305,"type":15},"MCP","mcp",{"name":9,"slug":8,"type":15},"2026-04-12T05:07:05.468097",{"slug":4309,"name":4309,"fn":4310,"description":4311,"org":4312,"tags":4313,"stars":4288,"repoUrl":4289,"updatedAt":4323},"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},[4314,4317,4320],{"name":4315,"slug":4316,"type":15},"API Development","api-development",{"name":4318,"slug":4319,"type":15},"CLI","cli",{"name":4321,"slug":4322,"type":15},"Codex","codex","2026-04-12T05:07:04.132762",{"slug":4325,"name":4325,"fn":4326,"description":4327,"org":4328,"tags":4329,"stars":4288,"repoUrl":4289,"updatedAt":4340},"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},[4330,4333,4336,4337],{"name":4331,"slug":4332,"type":15},"Cloudflare","cloudflare",{"name":4334,"slug":4335,"type":15},"Cloudflare Pages","cloudflare-pages",{"name":4178,"slug":4179,"type":15},{"name":4338,"slug":4339,"type":15},"Deployment","deployment","2026-04-12T05:07:14.275118",{"slug":4342,"name":4342,"fn":4343,"description":4344,"org":4345,"tags":4346,"stars":4288,"repoUrl":4289,"updatedAt":4359},"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},[4347,4350,4353,4356],{"name":4348,"slug":4349,"type":15},"Productivity","productivity",{"name":4351,"slug":4352,"type":15},"Project Management","project-management",{"name":4354,"slug":4355,"type":15},"Strategy","strategy",{"name":4357,"slug":4358,"type":15},"Task Management","task-management","2026-05-23T06:17:16.870838",{"slug":4361,"name":4361,"fn":4362,"description":4363,"org":4364,"tags":4365,"stars":4288,"repoUrl":4289,"updatedAt":4371},"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},[4366,4367,4369,4370],{"name":4140,"slug":4141,"type":15},{"name":4368,"slug":4361,"type":15},"Figma",{"name":4197,"slug":4198,"type":15},{"name":4304,"slug":4305,"type":15},"2026-04-12T05:06:47.939943",{"slug":4373,"name":4373,"fn":4374,"description":4375,"org":4376,"tags":4377,"stars":4288,"repoUrl":4289,"updatedAt":4385},"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},[4378,4379,4382,4383,4384],{"name":4140,"slug":4141,"type":15},{"name":4380,"slug":4381,"type":15},"Design System","design-system",{"name":4368,"slug":4361,"type":15},{"name":4197,"slug":4198,"type":15},{"name":4206,"slug":4207,"type":15},"2026-05-10T05:59:52.971881",{"slug":4387,"name":4387,"fn":4388,"description":4389,"org":4390,"tags":4391,"stars":4288,"repoUrl":4289,"updatedAt":4399},"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},[4392,4393,4394,4397,4398],{"name":4140,"slug":4141,"type":15},{"name":4380,"slug":4381,"type":15},{"name":4395,"slug":4396,"type":15},"Documentation","documentation",{"name":4368,"slug":4361,"type":15},{"name":4197,"slug":4198,"type":15},"2026-05-16T06:07:47.821474",{"slug":4401,"name":4401,"fn":4402,"description":4403,"org":4404,"tags":4405,"stars":4288,"repoUrl":4289,"updatedAt":4411},"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},[4406,4407,4408,4409,4410],{"name":4140,"slug":4141,"type":15},{"name":4368,"slug":4361,"type":15},{"name":4197,"slug":4198,"type":15},{"name":4206,"slug":4207,"type":15},{"name":4286,"slug":4287,"type":15},"2026-05-16T06:07:40.583615",{"slug":4413,"name":4413,"fn":4414,"description":4415,"org":4416,"tags":4417,"stars":4288,"repoUrl":4289,"updatedAt":4426},"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},[4418,4421,4422,4425],{"name":4419,"slug":4420,"type":15},"Animation","animation",{"name":4321,"slug":4322,"type":15},{"name":4423,"slug":4424,"type":15},"Creative","creative",{"name":4140,"slug":4141,"type":15},"2026-05-02T05:31:48.48485",{"slug":4428,"name":4428,"fn":4429,"description":4430,"org":4431,"tags":4432,"stars":4288,"repoUrl":4289,"updatedAt":4442},"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},[4433,4434,4435,4438,4441],{"name":4423,"slug":4424,"type":15},{"name":4140,"slug":4141,"type":15},{"name":4436,"slug":4437,"type":15},"Image Generation","image-generation",{"name":4439,"slug":4440,"type":15},"Images","images",{"name":9,"slug":8,"type":15},"2026-05-15T06:23:24.312127",675]