[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-microsoft-channel-digest":3,"mdc--yaybfy-key":34,"related-repo-microsoft-channel-digest":1067,"related-org-microsoft-channel-digest":1176},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":29,"sourceUrl":32,"mdContent":33},"channel-digest","generate digests for Microsoft Teams channels","Summarize activity across multiple Teams channels into a single consolidated digest — key discussions, decisions, mentions, and action items.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"microsoft","Microsoft","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fmicrosoft.png",[12,16,17,20],{"name":13,"slug":14,"type":15},"Summarization","summarization","tag",{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},"Microsoft Teams","microsoft-teams",{"name":21,"slug":22,"type":15},"Messaging","messaging",947,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fwork-iq","2026-04-06T18:35:25.021901",null,109,[],{"repoUrl":24,"stars":23,"forks":27,"topics":30,"description":31},[],"MCP Server and CLI for accessing Work IQ","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fwork-iq\u002Ftree\u002FHEAD\u002Fplugins\u002Fworkiq-productivity\u002Fskills\u002Fchannel-digest","---\nname: channel-digest\ndescription: Summarize activity across multiple Teams channels into a single consolidated digest — key discussions, decisions, mentions, and action items.\n---\n\n# Channel Digest\n\nProduce a consolidated summary of activity across multiple Microsoft Teams channels. Scans recent messages from each channel, identifies key discussions, decisions made, action items, and @‑mentions — then presents everything in a single, scannable digest. Ideal for managers, leads, or anyone tracking multiple project channels.\n\n## When to Use\n\n- \"What happened in my channels today?\"\n- \"Summarize the last 3 days across all my project channels\"\n- \"Give me a digest of Engineering and Product channels\"\n- \"Any decisions made in the team channels this week?\"\n- \"Channel digest for the sprint channels\"\n- \"What did I miss in the channels while I was out?\"\n\n## Instructions\n\n### Step 1: Identify the User\n\n```\nworkiq-ask (\n  question: \"What is my profile information including display name, email, and time zone?\"\n)\n```\n\nExtract **displayName**, **email**, and **timeZone**.\n\n### Step 2: Discover Teams and Channels\n\nList all teams and their channels:\n\n```\nworkiq-ask (\n  question: \"List all Microsoft Teams teams I belong to and their channels.\"\n)\n```\n\nIf the user specified particular channels (e.g., \"Engineering #general and #design-reviews\"), filter to only those. Otherwise, include all non‑archived channels across relevant teams.\n\nBuild a channel inventory:\n- **Team name** → **Channel name**\n- Skip channels named \"General\" in low‑priority teams unless the user explicitly includes them.\n\n### Step 3: Pull Recent Messages from Each Channel\n\nFor each target channel, fetch recent messages within the lookback window:\n\n```\nworkiq-ask (\n  question: \"Show me the last 30 messages in the '\u003Cchannel name>' channel of the '\u003Cteam name>' team including replies. For each message include the sender name, date and time, message content, reply count, any @mentions, reactions count, and any attachments or shared links.\"\n)\n```\n\nFor each message, capture:\n- **Sender** display name\n- **Timestamp**\n- **Content** (text body for analysis)\n- **Reply count** — indicates discussion depth\n- **Mentions** — anyone @‑mentioned, especially the current user\n- **Reactions** — high reaction count signals importance\n- **Attachments** — files or links shared\n\n### Step 4: Analyze and Categorize Messages\n\nFor each channel, classify the messages into categories:\n\n**🔑 Key Decisions** — messages containing:\n- Decision language: \"decided\", \"approved\", \"agreed\", \"going with\", \"finalized\", \"confirmed\"\n- Follow‑up with context about what was decided\n\n**💬 Active Discussions** — threads with:\n- 3+ replies indicating substantive conversation\n- Multiple participants contributing\n- Ongoing debate or open questions\n\n**📌 Action Items** — messages containing:\n- Task language: \"action item\", \"TODO\", \"follow up\", \"need to\", \"can you\", \"please\"\n- Assignments: \"@person please…\", \"owned by…\"\n- Deadlines: \"by Friday\", \"due date\", \"EOD\"\n\n**📢 Announcements** — messages that are:\n- From team owners or managers\n- Posted with high importance\n- Information‑sharing without expecting discussion\n\n**📎 Shared Resources** — messages with:\n- File attachments (documents, spreadsheets)\n- Links to external resources, PRs, or documents\n\n**👤 Your Mentions** — messages where the current user was @‑mentioned or referenced by name.\n\n### Step 5: Search for User Mentions Across Channels\n\nCast a wider net for the user's mentions:\n\n```\nworkiq-ask (\n  question: \"Find all Teams channel messages that mention me or are directed at me in the last \u003Clookback period>. Include the team name, channel name, sender, date, and message content for each.\"\n)\n```\n\nCross‑reference with messages already captured to avoid duplicates. Add any new mentions to the **Your Mentions** category.\n\n### Step 6: Compile the Consolidated Digest\n\nOrganize findings by channel, then surface cross‑channel themes at the top.\n\n## Output Format\n\n```\n📰 CHANNEL DIGEST\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n📅 Period: {start date} → {end date}\n🔍 Channels scanned: {N}  ·  💬 Messages analyzed: {N}\n\n🎯 CROSS‑CHANNEL HIGHLIGHTS\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n🔑 {N} decisions made  ·  📌 {N} action items  ·  👤 {N} times you were mentioned\n\nTop Decisions:\n  1. {Team} › #{Channel}: \"{decision summary}\" — {Person}, {date}\n  2. {Team} › #{Channel}: \"{decision summary}\" — {Person}, {date}\n\nAction Items Needing You:\n  • {Person} in #{Channel}: \"{action item}\" — due {date}\n  • {Person} in #{Channel}: \"{action item}\"\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n📢 {Team Name} › #{Channel Name}\n   💬 {N} messages  ·  🧵 {N} threads  ·  👥 {N} participants\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\n   🔑 DECISIONS\n   • \"{Decision summary}\" — {Person}, {date}\n\n   💬 KEY DISCUSSIONS\n   • \"{Topic summary}\" — {N} replies, {participants}\n     └─ Status: {resolved \u002F ongoing \u002F needs input}\n\n   📌 ACTION ITEMS\n   • {Person}: \"{task description}\" — {due date or \"no deadline\"}\n\n   📢 ANNOUNCEMENTS\n   • {Person}: \"{announcement summary}\" — {date}\n\n   📎 SHARED FILES\n   • {filename} — shared by {Person}, {date}\n\n   👤 YOUR MENTIONS\n   • {Person}: \"@you {message preview}\" — {date}\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n📢 {Team Name} › #{Channel Name}\n   💬 {N} messages  ·  ⏸️ Low activity\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n   • {brief summary of the few messages}\n\n🔇 QUIET CHANNELS (no messages in period)\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n   • {Team} › #{Channel}\n   • {Team} › #{Channel}\n```\n\n## Parameters\n\n| Parameter | Required | Default | Description |\n|-----------|----------|---------|-------------|\n| Lookback | No | 24 hours | Time window to scan (e.g., \"3 days\", \"this week\") |\n| Teams | No | All user's teams | Specific teams to include |\n| Channels | No | All channels | Specific channels to include |\n| Focus | No | All categories | Filter to \"decisions\", \"action-items\", or \"mentions\" |\n| Include Quiet | No | true | Whether to list channels with no activity |\n| Max Messages | No | 30 per channel | Maximum messages to pull per channel |\n\n## Required MCP Tools\n\n| MCP Server | Tool | Purpose |\n|---|---|---|\n| workiq (Local WorkIQ CLI) | `ask` | User identity, team\u002Fchannel discovery, message retrieval, and mention search |\n\n## Tips\n\n- Say \"digest for Engineering channels only\" to narrow the scope and speed up results.\n- Use \"channel digest for the last week\" before a Monday planning meeting to see what happened while you were out.\n- Use **action-item-extractor** to pull action items from meeting content after reviewing channel activity.\n- For recurring digests, establish a cadence: \"give me my channel digest every morning.\"\n- Ask \"expand on the discussion in #{Channel}\" to drill into a specific conversation with full context.\n\n## Examples\n\n**Example 1 — Morning standup prep (default 24-hour window)**\n\n> \"Give me a channel digest for today.\"\n\nScans all of the user's Teams channels for the past 24 hours, surfaces any decisions made overnight, flags action items assigned to the user, and lists @-mentions — all in a single digest organized by team and channel.\n\n---\n\n**Example 2 — Catch up after time off (multi-day, scoped channels)**\n\n> \"Channel digest for the Engineering and Product channels over the last 5 days.\"\n\nLimits the scan to channels in the Engineering and Product teams, pulls up to 30 messages per channel across the 5-day window, and highlights key decisions (e.g., architecture choices, scope changes), active threads, and any messages that mentioned the user while they were away.\n\n---\n\n**Example 3 — Decision-focused digest before a planning meeting**\n\n> \"Show me only decisions and action items from the sprint channels this week.\"\n\nUses the `Focus` parameter to filter output to **Key Decisions** and **Action Items** only, skipping announcements and low-activity channel summaries. Ideal for quickly building a pre-meeting agenda from what was agreed or assigned across sprint-related channels.\n\n## Error Handling\n\n**No teams or channels found**\n- `ask` returns an empty result if the user is not a member of any team, or if the account lacks access to the Teams API.\n- *Resolution:* Confirm the user's account has Microsoft Teams access and is a member of at least one team. Ask the user to specify a team name manually if discovery fails.\n\n**Channel message fetch returns empty or partial results**\n- `ask` may return fewer messages than expected if the channel has low activity or if the lookback window predates available message history (Teams message retention policies vary).\n- *Resolution:* Proceed with available messages and note in the digest that history may be limited. Surface \"No messages in period\" for those channels in the **Quiet Channels** section rather than failing silently.\n\n**Permission denied on a channel**\n- Private channels require explicit membership; `ask` will indicate an access error if the user is not a member of a private channel even within a team they belong to.\n- *Resolution:* Skip the inaccessible channel, log it as \"access restricted\" in the digest output, and continue processing remaining channels.\n\n**Search for mentions returns no results**\n- The mentions query via `ask` may return empty results for broad queries or large tenants.\n- *Resolution:* Fall back to the mentions already captured during the per-channel message retrieval. Note that the mention search could not be completed so the **Your Mentions** section may be incomplete.\n\n**Slow responses with many channels**\n- Querying messages from a large number of channels requires multiple `ask` calls and may be slow.\n- *Resolution:* Process channels in batches. 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Helps you triage and prioritize your workday.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1115,1116,1119,1122,1123],{"name":9,"slug":8,"type":15},{"name":1117,"slug":1118,"type":15},"Outlook Calendar","outlook-calendar",{"name":1120,"slug":1121,"type":15},"Outlook Email","outlook-email",{"name":1079,"slug":1080,"type":15},{"name":13,"slug":14,"type":15},"2026-04-06T18:35:28.767999",{"slug":1126,"name":1126,"fn":1127,"description":1128,"org":1129,"tags":1130,"stars":23,"repoUrl":24,"updatedAt":1144},"declarative-agent-developer","build and deploy declarative agents for M365","Create, build, deploy, and localize declarative agents for M365 Copilot and Teams. USE THIS SKILL for ANY task involving a declarative agent — including localization, scaffolding, editing manifests, adding capabilities, and deploying. Localization requires tokenized manifests and language files that only this skill knows how to produce. Triggers: \"create agent\", \"create a declarative agent\", \"new declarative agent\", \"scaffold an agent\", \"new agent project\", \"add a capability\", \"add a plugin\", \"configure my agent\", \"deploy my agent\", \"fix my agent manifest\", \"edit my agent\", \"localize my agent\", \"add localization\", \"translate my agent\", \"multi-language agent\", \"add an API plugin\", \"add an MCP plugin\", \"add OAuth to my plugin\", \"review instructions\", \"improve instructions\", \"fix my instructions\"\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1131,1134,1137,1140,1141],{"name":1132,"slug":1133,"type":15},"Agents","agents",{"name":1135,"slug":1136,"type":15},"Copilot","copilot",{"name":1138,"slug":1139,"type":15},"Deployment","deployment",{"name":9,"slug":8,"type":15},{"name":1142,"slug":1143,"type":15},"Microsoft 365","microsoft-365","2026-04-06T18:35:42.309091",{"slug":1146,"name":1146,"fn":1147,"description":1148,"org":1149,"tags":1150,"stars":23,"repoUrl":24,"updatedAt":1158},"email-analytics","analyze email volume and response patterns","Analyze your email patterns over a time period — volume trends, top senders, response time estimates, busiest days, and unread backlog statistics.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1151,1154,1156,1157],{"name":1152,"slug":1153,"type":15},"Analytics","analytics",{"name":1155,"slug":138,"type":15},"Email",{"name":9,"slug":8,"type":15},{"name":1079,"slug":1080,"type":15},"2026-04-06T18:35:26.264312",{"slug":1160,"name":1160,"fn":1161,"description":1162,"org":1163,"tags":1164,"stars":23,"repoUrl":24,"updatedAt":1174},"install-atk","install and update M365 Agents Toolkit","Install or update the M365 Agents Toolkit (ATK) CLI and VS Code extension. Triggers: \"install atk\", \"update atk\", \"install agents toolkit\", \"update agents toolkit\", \"install the toolkit\", \"setup atk\", \"get atk\", \"install atk cli\", \"install atk extension\", \"install atk vsix\", \"update the vs code extension\", \"install latest atk\", \"upgrade atk\"\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1165,1166,1169,1172,1173],{"name":1132,"slug":1133,"type":15},{"name":1167,"slug":1168,"type":15},"CLI","cli",{"name":1170,"slug":1171,"type":15},"Local Development","local-development",{"name":9,"slug":8,"type":15},{"name":1142,"slug":1143,"type":15},"2026-04-06T18:35:40.873947",14,{"items":1177,"total":1366},[1178,1198,1217,1236,1251,1268,1279,1292,1307,1322,1341,1354],{"slug":1179,"name":1179,"fn":1180,"description":1181,"org":1182,"tags":1183,"stars":1195,"repoUrl":1196,"updatedAt":1197},"rushstack-best-practices","manage Rush monorepos with best practices","Provides best practices and guidance for working with Rush monorepos. Use when the user is working in a Rush-based repository, asks about Rush commands (install, update, build, rebuild), needs help with project selection, dependency management, build caching, subspace configuration, or troubleshooting Rush-specific issues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1184,1187,1188,1189,1192],{"name":1185,"slug":1186,"type":15},"Engineering","engineering",{"name":1170,"slug":1171,"type":15},{"name":9,"slug":8,"type":15},{"name":1190,"slug":1191,"type":15},"Project Management","project-management",{"name":1193,"slug":1194,"type":15},"Rush","rush",6484,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frushstack","2026-04-06T18:34:44.965032",{"slug":1199,"name":1199,"fn":1200,"description":1201,"org":1202,"tags":1203,"stars":1214,"repoUrl":1215,"updatedAt":1216},"azure-ai-agents-persistent-dotnet","build AI agents with Azure .NET SDK","Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: \"PersistentAgentsClient\", \"persistent agents\", \"agent threads\", \"agent runs\", \"streaming agents\", \"function calling agents .NET\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1204,1207,1208,1211],{"name":1205,"slug":1206,"type":15},".NET","net",{"name":1132,"slug":1133,"type":15},{"name":1209,"slug":1210,"type":15},"Azure","azure",{"name":1212,"slug":1213,"type":15},"LLM","llm",2804,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills","2026-07-03T16:32:10.297433",{"slug":1218,"name":1218,"fn":1219,"description":1220,"org":1221,"tags":1222,"stars":1214,"repoUrl":1215,"updatedAt":1235},"azure-ai-anomalydetector-java","build anomaly detection applications with Java","Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate\u002Fmultivariate anomaly detection, time-series analysis, or AI-powered monitoring.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1223,1224,1225,1228,1231,1232],{"name":1152,"slug":1153,"type":15},{"name":1209,"slug":1210,"type":15},{"name":1226,"slug":1227,"type":15},"Data Analysis","data-analysis",{"name":1229,"slug":1230,"type":15},"Java","java",{"name":9,"slug":8,"type":15},{"name":1233,"slug":1234,"type":15},"Monitoring","monitoring","2026-05-13T06:14:16.261754",{"slug":1237,"name":1237,"fn":1238,"description":1239,"org":1240,"tags":1241,"stars":1214,"repoUrl":1215,"updatedAt":1250},"azure-ai-contentsafety-java","build content moderation applications with Azure AI","Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text\u002Fimage analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1242,1245,1246,1247],{"name":1243,"slug":1244,"type":15},"AI Infrastructure","ai-infrastructure",{"name":1209,"slug":1210,"type":15},{"name":1229,"slug":1230,"type":15},{"name":1248,"slug":1249,"type":15},"Security","security","2026-07-07T06:53:31.293235",{"slug":1252,"name":1252,"fn":1253,"description":1254,"org":1255,"tags":1256,"stars":1214,"repoUrl":1215,"updatedAt":1267},"azure-ai-contentsafety-py","detect harmful content with Azure AI Content Safety","Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.\nTriggers: \"azure-ai-contentsafety\", \"ContentSafetyClient\", \"content moderation\", \"harmful content\", \"text analysis\", \"image analysis\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1257,1258,1261,1262,1263,1266],{"name":1209,"slug":1210,"type":15},{"name":1259,"slug":1260,"type":15},"Compliance","compliance",{"name":1212,"slug":1213,"type":15},{"name":9,"slug":8,"type":15},{"name":1264,"slug":1265,"type":15},"Python","python",{"name":1248,"slug":1249,"type":15},"2026-07-18T05:14:23.017504",{"slug":1269,"name":1269,"fn":1270,"description":1271,"org":1272,"tags":1273,"stars":1214,"repoUrl":1215,"updatedAt":1278},"azure-ai-language-conversations-py","implement conversational language understanding with Python","Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1274,1275,1276,1277],{"name":1152,"slug":1153,"type":15},{"name":1209,"slug":1210,"type":15},{"name":1212,"slug":1213,"type":15},{"name":1264,"slug":1265,"type":15},"2026-07-31T05:54:29.068751",{"slug":1280,"name":1280,"fn":1281,"description":1282,"org":1283,"tags":1284,"stars":1214,"repoUrl":1215,"updatedAt":1291},"azure-ai-translation-text-py","translate text using Azure AI services","Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.\nTriggers: \"text translation\", \"translator\", \"translate text\", \"transliterate\", \"TextTranslationClient\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1285,1288,1289,1290],{"name":1286,"slug":1287,"type":15},"API Development","api-development",{"name":1209,"slug":1210,"type":15},{"name":9,"slug":8,"type":15},{"name":1264,"slug":1265,"type":15},"2026-07-18T05:14:16.988376",{"slug":1293,"name":1293,"fn":1294,"description":1295,"org":1296,"tags":1297,"stars":1214,"repoUrl":1215,"updatedAt":1306},"azure-ai-vision-imageanalysis-py","analyze images with Azure AI Vision","Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks.\nTriggers: \"image analysis\", \"computer vision\", \"OCR\", \"object detection\", \"ImageAnalysisClient\", \"image caption\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1298,1299,1302,1305],{"name":1209,"slug":1210,"type":15},{"name":1300,"slug":1301,"type":15},"Computer Vision","computer-vision",{"name":1303,"slug":1304,"type":15},"Images","images",{"name":1264,"slug":1265,"type":15},"2026-07-18T05:14:18.007737",{"slug":1308,"name":1308,"fn":1309,"description":1310,"org":1311,"tags":1312,"stars":1214,"repoUrl":1215,"updatedAt":1321},"azure-appconfiguration-java","manage configuration with Azure App Configuration","Azure App Configuration SDK for Java. Centralized application configuration management with key-value settings, feature flags, and snapshots.\nTriggers: \"ConfigurationClient java\", \"app configuration java\", \"feature flag java\", \"configuration setting java\", \"azure config java\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1313,1314,1317,1320],{"name":1209,"slug":1210,"type":15},{"name":1315,"slug":1316,"type":15},"Configuration","configuration",{"name":1318,"slug":1319,"type":15},"Feature Flags","feature-flags",{"name":1229,"slug":1230,"type":15},"2026-07-03T16:32:01.278468",{"slug":1323,"name":1323,"fn":1324,"description":1325,"org":1326,"tags":1327,"stars":1214,"repoUrl":1215,"updatedAt":1340},"azure-cosmos-rust","build applications with Azure Cosmos DB","Azure Cosmos DB library for Rust (NoSQL API). Document CRUD, containers, and globally distributed data.\nTriggers: \"cosmos db rust\", \"CosmosClient rust\", \"document crud rust\", \"NoSQL rust\", \"partition key rust\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1328,1331,1334,1337],{"name":1329,"slug":1330,"type":15},"Cosmos DB","cosmos-db",{"name":1332,"slug":1333,"type":15},"Database","database",{"name":1335,"slug":1336,"type":15},"NoSQL","nosql",{"name":1338,"slug":1339,"type":15},"Rust","rust","2026-07-31T05:54:27.021432",{"slug":1342,"name":1342,"fn":1324,"description":1343,"org":1344,"tags":1345,"stars":1214,"repoUrl":1215,"updatedAt":1353},"azure-cosmos-ts","Azure Cosmos DB JavaScript\u002FTypeScript SDK (@azure\u002Fcosmos) for data plane operations. Use for CRUD operations on documents, queries, bulk operations, and container management. Triggers: \"Cosmos DB\", \"@azure\u002Fcosmos\", \"CosmosClient\", \"document CRUD\", \"NoSQL queries\", \"bulk operations\", \"partition key\", \"container.items\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1346,1347,1348,1349,1350],{"name":1329,"slug":1330,"type":15},{"name":1332,"slug":1333,"type":15},{"name":9,"slug":8,"type":15},{"name":1335,"slug":1336,"type":15},{"name":1351,"slug":1352,"type":15},"TypeScript","typescript","2026-07-03T16:31:19.368382",{"slug":1355,"name":1355,"fn":1356,"description":1357,"org":1358,"tags":1359,"stars":1214,"repoUrl":1215,"updatedAt":1365},"azure-data-tables-java","build table storage applications with Java","Build table storage applications with Azure Tables SDK for Java. Use when working with Azure Table Storage or Cosmos DB Table API for NoSQL key-value data, schemaless storage, or structured data at scale.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1360,1361,1362,1363,1364],{"name":1209,"slug":1210,"type":15},{"name":1329,"slug":1330,"type":15},{"name":1332,"slug":1333,"type":15},{"name":1229,"slug":1230,"type":15},{"name":1335,"slug":1336,"type":15},"2026-05-13T06:14:17.582229",267]