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Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts\u002Fresources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.","JSGforever\u002Fskillguard","JSGforever","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F85541948?v=4","01M71FQD3E132VMR5F4TAYX3YS","01M71FQD4DYW0XJ4XQ4YQH75Y9",2,"GPL-3.0","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__binjuhor--mcp-management\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"mcp management","management","MCP","capability discovery","capability","context","Tools","server","analyze","filter","capabilities","model context protocol","tasks","when","access","with mcp","selection","model","discover","resources","2026-11-10 10:12:30",false,"---\nname: mcp-management\ndescription: Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools\u002Fprompts\u002Fresources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts\u002Fresources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.\n---\n\n# MCP Management\n\nSkill for managing and interacting with Model Context Protocol (MCP) servers.\n\n## Overview\n\nMCP is an open protocol enabling AI agents to connect to external tools and data sources. This skill provides scripts and utilities to discover, analyze, and execute MCP capabilities from configured servers without polluting the main context window.\n\n**Key Benefits**:\n- Progressive disclosure of MCP capabilities (load only what's needed)\n- Intelligent tool\u002Fprompt\u002Fresource selection based on task requirements\n- Multi-server management from single config file\n- Context-efficient: subagents handle MCP discovery and execution\n- Persistent tool catalog: automatically saves discovered tools to JSON for fast reference\n\n## When to Use This Skill\n\nUse this skill when:\n1. **Discovering MCP Capabilities**: Need to list available tools\u002Fprompts\u002Fresources from configured servers\n2. **Task-Based Tool Selection**: Analyzing which MCP tools are relevant for a specific task\n3. **Executing MCP Tools**: Calling MCP tools programmatically with proper parameter handling\n4. **MCP Integration**: Building or debugging MCP client implementations\n5. **Context Management**: Avoiding context pollution by delegating MCP operations to subagents\n\n## Core Capabilities\n\n### 1. Configuration Management\n\nMCP servers configured in `.claude\u002F.mcp.json`.\n\n**Gemini CLI Integration** (recommended): Create symlink to `.gemini\u002Fsettings.json`:\n```bash\nmkdir -p .gemini && ln -sf .claude\u002F.mcp.json .gemini\u002Fsettings.json\n```\n\nSee [references\u002Fconfiguration.md](references\u002Fconfiguration.md) and [references\u002Fgemini-cli-integration.md](references\u002Fgemini-cli-integration.md).\n\n**GEMINI.md Response Format**: Project root contains `GEMINI.md` that Gemini CLI auto-loads, enforcing structured JSON responses:\n```json\n{\"server\":\"name\",\"tool\":\"name\",\"success\":true,\"result\":\u003Cdata>,\"error\":null}\n```\n\nThis ensures parseable, consistent output instead of unpredictable natural language. The file defines:\n- Mandatory JSON-only response format (no markdown, no explanations)\n- Maximum 500 character responses\n- Error handling structure\n- Available MCP servers reference\n\n**Benefits**: Programmatically parseable output, consistent error reporting, DRY configuration (format defined once), context-efficient (auto-loaded by Gemini CLI).\n\n### 2. Capability Discovery\n\n```bash\nnpx tsx scripts\u002Fcli.ts list-tools  # Saves to assets\u002Ftools.json\nnpx tsx scripts\u002Fcli.ts list-prompts\nnpx tsx scripts\u002Fcli.ts list-resources\n```\n\nAggregates capabilities from multiple servers with server identification.\n\n### 3. Intelligent Tool Analysis\n\nLLM analyzes `assets\u002Ftools.json` directly - better than keyword matching algorithms.\n\n### 4. Tool Execution\n\n**Primary: Gemini CLI** (if available)\n```bash\n# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)\necho \"Take a screenshot of https:\u002F\u002Fexample.com\" | gemini -y -m gemini-2.5-flash\n```\n\n**Secondary: Direct Scripts**\n```bash\nnpx tsx scripts\u002Fcli.ts call-tool memory create_entities '{\"entities\":[...]}'\n```\n\n**Fallback: mcp-manager Subagent**\n\nSee [references\u002Fgemini-cli-integration.md](references\u002Fgemini-cli-integration.md) for complete examples.\n\n## Implementation Patterns\n\n### Pattern 1: Gemini CLI Auto-Execution (Primary)\n\nUse Gemini CLI for automatic tool discovery and execution. Gemini CLI auto-loads `GEMINI.md` from project root to enforce structured JSON responses.\n\n**Quick Example**:\n```bash\n# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)\n# Add \"Return JSON only per GEMINI.md instructions\" to enforce structured output\necho \"Take a screenshot of https:\u002F\u002Fexample.com. Return JSON only per GEMINI.md instructions.\" | gemini -y -m gemini-2.5-flash\n```\n\n**Expected Output**:\n```json\n{\"server\":\"puppeteer\",\"tool\":\"screenshot\",\"success\":true,\"result\":\"screenshot.png\",\"error\":null}\n```\n\n**Benefits**:\n- Automatic tool discovery\n- Structured JSON responses (parseable by Claude)\n- GEMINI.md auto-loaded for consistent formatting\n- Faster than subagent orchestration\n- No natural language ambiguity\n\nSee [references\u002Fgemini-cli-integration.md](references\u002Fgemini-cli-integration.md) for complete guide.\n\n### Pattern 2: Subagent-Based Execution (Fallback)\n\nUse `mcp-manager` agent when Gemini CLI unavailable. Subagent discovers tools, selects relevant ones, executes tasks, reports back.\n\n**Benefit**: Main context stays clean, only relevant tool definitions loaded when needed.\n\n### Pattern 3: LLM-Driven Tool Selection\n\nLLM reads `assets\u002Ftools.json`, intelligently selects relevant tools using context understanding, synonyms, and intent recognition.\n\n### Pattern 4: Multi-Server Orchestration\n\nCoordinate tools across multiple servers. Each tool knows its source server for proper routing.\n\n## Scripts Reference\n\n### scripts\u002Fmcp-client.ts\n\nCore MCP client manager class. Handles:\n- Config loading from `.claude\u002F.mcp.json`\n- Connecting to multiple MCP servers\n- Listing tools\u002Fprompts\u002Fresources across all servers\n- Executing tools with proper error handling\n- Connection lifecycle management\n\n### scripts\u002Fcli.ts\n\nCommand-line interface for MCP operations. Commands:\n- `list-tools` - Display all tools and save to `assets\u002Ftools.json`\n- `list-prompts` - Display all prompts\n- `list-resources` - Display all resources\n- `call-tool \u003Cserver> \u003Ctool> \u003Cjson>` - Execute a tool\n\n**Note**: `list-tools` persists complete tool catalog to `assets\u002Ftools.json` with full schemas for fast reference, offline browsing, and version control.\n\n## Quick Start\n\n**Method 1: Gemini CLI** (recommended)\n```bash\nnpm install -g gemini-cli\nmkdir -p .gemini && ln -sf .claude\u002F.mcp.json .gemini\u002Fsettings.json\n# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)\n# GEMINI.md auto-loads to enforce JSON responses\necho \"Take a screenshot of https:\u002F\u002Fexample.com. Return JSON only per GEMINI.md instructions.\" | gemini -y -m gemini-2.5-flash\n```\n\nReturns structured JSON: `{\"server\":\"puppeteer\",\"tool\":\"screenshot\",\"success\":true,\"result\":\"screenshot.png\",\"error\":null}`\n\n**Method 2: Scripts**\n```bash\ncd .claude\u002Fskills\u002Fmcp-management\u002Fscripts && npm install\nnpx tsx cli.ts list-tools  # Saves to assets\u002Ftools.json\nnpx tsx cli.ts call-tool memory create_entities '{\"entities\":[...]}'\n```\n\n**Method 3: mcp-manager Subagent**\n\nSee [references\u002Fgemini-cli-integration.md](references\u002Fgemini-cli-integration.md) for complete guide.\n\n## Technical Details\n\nSee [references\u002Fmcp-protocol.md](references\u002Fmcp-protocol.md) for:\n- JSON-RPC protocol details\n- Message types and formats\n- Error codes and handling\n- Transport mechanisms (stdio, HTTP+SSE)\n- Best practices\n\n## Integration Strategy\n\n### Execution Priority\n\n1. **Gemini CLI** (Primary): Fast, automatic, intelligent tool selection\n   - Check: `command -v gemini`\n   - Execute: `echo \"\u003Ctask>\" | gemini -y -m gemini-2.5-flash`\n   - **IMPORTANT**: Use stdin piping, NOT `-p` flag (deprecated, skips MCP init)\n   - Best for: All tasks when available\n\n2. **Direct CLI Scripts** (Secondary): Manual tool specification\n   - Use when: Need specific tool\u002Fserver control\n   - Execute: `npx tsx scripts\u002Fcli.ts call-tool \u003Cserver> \u003Ctool> \u003Cargs>`\n\n3. **mcp-manager Subagent** (Fallback): Context-efficient delegation\n   - Use when: Gemini unavailable or failed\n   - Keeps main context clean\n\n### Integration with Agents\n\nThe `mcp-manager` agent uses this skill to:\n- Check Gemini CLI availability first\n- Execute via `gemini` command if available\n- Fallback to direct script execution\n- Discover MCP capabilities without loading into main context\n- Report results back to main agent\n\nThis keeps main agent context clean and enables efficient MCP integration.","# MCP Management\n\nSkill for managing and interacting with Model Context Protocol (MCP) servers.\n\n## Overview\n\nMCP is an open protocol enabling AI agents to connect to external tools and data sources. This skill provides scripts and utilities to discover, analyze, and execute MCP capabilities from configured servers without polluting the main context window.\n\n**Key Benefits**:\n- Progressive disclosure of MCP capabilities (load only what's needed)\n- Intelligent tool\u002Fprompt\u002Fresource selection based on task requirements\n- Multi-server management from single config file\n- Context-efficient: subagents handle MCP discovery and execution\n- Persistent tool catalog: automatically saves discovered tools to JSON for fast reference\n\n## When to Use This Skill\n\nUse this skill when:\n1. **Discovering MCP Capabilities**: Need to list available tools\u002Fprompts\u002Fresources from configured servers\n2. **Task-Based Tool Selection**: Analyzing which MCP tools are relevant for a specific task\n3. **Executing MCP Tools**: Calling MCP tools programmatically with proper parameter handling\n4. **MCP Integration**: Building or debugging MCP client implementations\n5. **Context Management**: Avoiding context pollution by delegating MCP operations to subagents\n\n## Core Capabilities\n\n### 1. Configuration Management\n\nMCP servers configured in `.claude\u002F.mcp.json`.\n\n**Gemini CLI Integration** (recommended): Create symlink to `.gemini\u002Fsettings.json`:\n```bash\nmkdir -p .gemini && ln -sf .claude\u002F.mcp.json .gemini\u002Fsettings.json\n```\n\nSee [references\u002Fconfiguration.md](references\u002Fconfiguration.md) and [references\u002Fgemini-cli-integration.md](references\u002Fgemini-cli-integration.md).\n\n**GEMINI.md Response Format**: Project root contains `GEMINI.md` that Gemini CLI auto-loads, enforcing structured JSON responses:\n```json\n{\"server\":\"name\",\"tool\":\"name\",\"success\":true,\"result\":\u003Cdata>,\"error\":null}\n```\n\nThis ensures parseable, consistent output instead of unpredictable natural language. The file defines:\n- Mandatory JSON-only response format (no markdown, no explanations)\n- Maximum 500 character responses\n- Error handling structure\n- Available MCP servers reference\n\n**Benefits**: Programmatically parseable output, consistent error reporting, DRY configuration (format defined once), context-efficient (auto-loaded by Gemini CLI).\n\n### 2. Capability Discovery\n\n```bash\nnpx tsx scripts\u002Fcli.ts list-tools  # Saves to assets\u002Ftools.json\nnpx tsx scripts\u002Fcli.ts list-prompts\nnpx tsx scripts\u002Fcli.ts list-resources\n```\n\nAggregates capabilities from multiple servers with server identification.\n\n### 3. Intelligent Tool Analysis\n\nLLM analyzes `assets\u002Ftools.json` directly - better than keyword matching algorithms.\n\n### 4. Tool Execution\n\n**Primary: Gemini CLI** (if available)\n```bash\n# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)\necho \"Take a screenshot of https:\u002F\u002Fexample.com\" | gemini -y -m gemini-2.5-flash\n```\n\n**Secondary: Direct Scripts**\n```bash\nnpx tsx scripts\u002Fcli.ts call-tool memory create_entities '{\"entities\":[...]}'\n```\n\n**Fallback: mcp-manager Subagent**\n\nSee [references\u002Fgemini-cli-integration.md](references\u002Fgemini-cli-integration.md) for complete examples.\n\n## Implementation Patterns\n\n### Pattern 1: Gemini CLI Auto-Execution (Primary)\n\nUse Gemini CLI for automatic tool discovery and execution. Gemini CLI auto-loads `GEMINI.md` from project root to enforce structured JSON responses.\n\n**Quick Example**:\n```bash\n# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)\n# Add \"Return JSON only per GEMINI.md instructions\" to enforce structured output\necho \"Take a screenshot of https:\u002F\u002Fexample.com. Return JSON only per GEMINI.md instructions.\" | gemini -y -m gemini-2.5-flash\n```\n\n**Expected Output**:\n```json\n{\"server\":\"puppeteer\",\"tool\":\"screenshot\",\"success\":true,\"result\":\"screenshot.png\",\"error\":null}\n```\n\n**Benefits**:\n- Automatic tool discovery\n- Structured JSON responses (parseable by Claude)\n- GEMINI.md auto-loaded for consistent formatting\n- Faster than subagent orchestration\n- No natural language ambiguity\n\nSee [references\u002Fgemini-cli-integration.md](references\u002Fgemini-cli-integration.md) for complete guide.\n\n### Pattern 2: Subagent-Based Execution (Fallback)\n\nUse `mcp-manager` agent when Gemini CLI unavailable. Subagent discovers tools, selects relevant ones, executes tasks, reports back.\n\n**Benefit**: Main context stays clean, only relevant tool definitions loaded when needed.\n\n### Pattern 3: LLM-Driven Tool Selection\n\nLLM reads `assets\u002Ftools.json`, intelligently selects relevant tools using context understanding, synonyms, and intent recognition.\n\n### Pattern 4: Multi-Server Orchestration\n\nCoordinate tools across multiple servers. Each tool knows its source server for proper routing.\n\n## Scripts Reference\n\n### scripts\u002Fmcp-client.ts\n\nCore MCP client manager class. Handles:\n- Config loading from `.claude\u002F.mcp.json`\n- Connecting to multiple MCP servers\n- Listing tools\u002Fprompts\u002Fresources across all servers\n- Executing tools with proper error handling\n- Connection lifecycle management\n\n### scripts\u002Fcli.ts\n\nCommand-line interface for MCP operations. Commands:\n- `list-tools` - Display all tools and save to `assets\u002Ftools.json`\n- `list-prompts` - Display all prompts\n- `list-resources` - Display all resources\n- `call-tool \u003Cserver> \u003Ctool> \u003Cjson>` - Execute a tool\n\n**Note**: `list-tools` persists complete tool catalog to `assets\u002Ftools.json` with full schemas for fast reference, offline browsing, and version control.\n\n## Quick Start\n\n**Method 1: Gemini CLI** (recommended)\n```bash\nnpm install -g gemini-cli\nmkdir -p .gemini && ln -sf .claude\u002F.mcp.json .gemini\u002Fsettings.json\n# IMPORTANT: Use stdin piping, NOT -p flag (deprecated, skips MCP init)\n# GEMINI.md auto-loads to enforce JSON responses\necho \"Take a screenshot of https:\u002F\u002Fexample.com. Return JSON only per GEMINI.md instructions.\" | gemini -y -m gemini-2.5-flash\n```\n\nReturns structured JSON: `{\"server\":\"puppeteer\",\"tool\":\"screenshot\",\"success\":true,\"result\":\"screenshot.png\",\"error\":null}`\n\n**Method 2: Scripts**\n```bash\ncd .claude\u002Fskills\u002Fmcp-management\u002Fscripts && npm install\nnpx tsx cli.ts list-tools  # Saves to assets\u002Ftools.json\nnpx tsx cli.ts call-tool memory create_entities '{\"entities\":[...]}'\n```\n\n**Method 3: mcp-manager Subagent**\n\nSee [references\u002Fgemini-cli-integration.md](references\u002Fgemini-cli-integration.md) for complete guide.\n\n## Technical Details\n\nSee [references\u002Fmcp-protocol.md](references\u002Fmcp-protocol.md) for:\n- JSON-RPC protocol details\n- Message types and formats\n- Error codes and handling\n- Transport mechanisms (stdio, HTTP+SSE)\n- Best practices\n\n## Integration Strategy\n\n### Execution Priority\n\n1. **Gemini CLI** (Primary): Fast, automatic, intelligent tool 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deterministic+LLM agent-skill security scanner. Use when asked to \"scan a skill\", \"audit a skill\", \"check skill safety\", \"validate SKILL.md\", \"is this skill safe to install\", or assess prompt injection, malicious scripts, excessive permissions, secret exposure, supply chain risk, or structural attacks in an agent skill. Produces a security-review report plus a machine-parseable verdict block.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fsrc\u002Fskillguard\u002Fstatic_scanner\u002Fskillguard-codex-scanner\u002FSKILL.md",[126],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[128,129,130,131,132,133,134,135,136,137,138,139,36,140,141,142,143,144,145,146],"scanner","skillguard codex scanner","skillguard","codex","chain","skill security","security-review","review report","structural","secret","prompt injection","security scanner","review","malicious","permissions","exposure","audit","scripts","safe",{"skillNo":148,"name":149,"nameZh":6,"description":150,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":151,"licenseFileUrl":6,"sourceHtmlUrl":152,"categories":153,"keywords":159,"publishedAt":43},"01M71HY0SPKTT3S27BC2HPAC5M","data-exfiltrator","Analyzes data files","MIT","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Fsmoke-one-skill\u002Fasset1__cisco-ai-defense--data-exfiltrator\u002FSKILL.md",[154],{"categoryNo":155,"categoryName":156,"taxonomyType":157,"taxonomyTypeDesc":158},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[160,161,162],"data","data exfiltrator","files",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":169,"publishedAt":43},"01M71HXVS9EMN44BGDW215FZ72","real-time-collaboration-engine","Build real-time collaborative editing with WebSockets, OT\u002FCRDT conflict resolution, and presence awareness. Implements cursor tracking, optimistic updates, and offline sync. Use for collaborative editors, whiteboards, video editing. Activate on \"real-time collaboration\", \"WebSocket sync\", \"multiplayer editing\", \"CRDT\", \"presence awareness\". NOT for simple chat, request-response APIs, or single-user apps.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--real-time-collaboration-engine\u002FSKILL.md",[],[170,171,172,173,174,175,176,177,178,179,180,181,37,182,183,184,185,186,187,188],"time","real time collaboration engine","real time collaboration","collaboration","engine","real time","Video","reliability","video editing","performance","conflict resolution","presence","apps","updates","Bash","activate","optimizer","react","streaming",{"skillNo":190,"name":191,"nameZh":6,"description":192,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":193,"categories":194,"keywords":198,"publishedAt":43},"01M71HXP6CTY4KFN0QVMMN0V7J","react-performance-optimizer","Optimize React apps for 60fps performance. Implements memoization, virtualization, code splitting, bundle optimization. Use for slow renders, large lists, bundle bloat. Activate on \"React performance\", \"slow render\", \"useMemo\", \"bundle size\", \"virtualization\". NOT for backend optimization, non-React frameworks, or premature optimization.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--react-performance-optimizer\u002FSKILL.md",[195],{"categoryNo":196,"categoryName":197,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",[179,199,186,187,200,201,202,203,204,205,170,206,207,182,184,208,185,188,209,210],"react performance optimizer","react performance","performance optimizer","app","nextjs","expert","re","render","2025","code","router","strategies",{"skillNo":212,"name":213,"nameZh":6,"description":214,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":215,"categories":216,"keywords":218,"publishedAt":43},"01M71HXH7QXSQB4QTDZ7SP7YXQ","llm-streaming-response-handler","Build production LLM streaming UIs with Server-Sent Events, real-time token display, cancellation, error recovery. Handles OpenAI\u002FAnthropic\u002FClaude streaming APIs. Use for chatbots, AI assistants, real-time text generation. Activate on \"LLM streaming\", \"SSE\", \"token stream\", \"chat UI\", \"real-time AI\". NOT for batch processing, non-streaming APIs, or WebSocket bidirectional chat.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--llm-streaming-response-handler\u002FSKILL.md",[217],{"categoryNo":196,"categoryName":197,"taxonomyType":20,"taxonomyTypeDesc":21},[219,188,220,221,222,223,179,170,224,225,226,184,185,186,227,187,228,229,30,230],"llm streaming response handler","handler","error","processing","retry","chat ui","error recovery","critical","batch","display","text","read",{"skillNo":232,"name":233,"nameZh":6,"description":234,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":235,"categories":236,"keywords":244,"publishedAt":43},"01M71HXCB0E1YRKYW1Y8T0Y106","github-actions-pipeline-builder","Build production CI\u002FCD pipelines with GitHub Actions. Implements matrix builds, caching, deployments, testing, security scanning. Use for automated testing, deployments, release workflows. Activate on \"GitHub Actions\", \"CI\u002FCD\", \"workflow\", \"deployment pipeline\", \"automated testing\". NOT for Jenkins\u002FCircleCI, manual deployments, or non-GitHub repositories.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--github-actions-pipeline-builder\u002FSKILL.md",[237,240,243],{"categoryNo":238,"categoryName":239,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":241,"categoryName":242,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[245,246,247,248,249,250,251,177,204,252,253,254,185,210,255,230,256,257,258,259],"github actions pipeline builder","actions","github actions","pipeline builder","github","builder","pipeline","testing","ci","workflows","run","release","write","edit","git"]