Triage failed Agent QA runs with MCP evidence, artifacts, logs, fixed failure categories, confidence, and actionable next steps.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Triage failed Agent QA runs with MCP evidence, artifacts, logs, fixed failure categories, confidence, and actionable next steps.
日本語の概要は準備中です。原文の説明を表示しています。
Debug, patch, and verify failed Agent QA runs from MCP evidence, artifacts, logs, and local code without hiding product or infrastructure defects.
日本語の概要は準備中です。原文の説明を表示しています。
Create, edit, validate, and run Agent QA tests, suites, and hooks through MCP or CLI while preserving canonical IDs and schema contracts.
日本語の概要は準備中です。原文の説明を表示しています。
Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
日本語の概要は準備中です。原文の説明を表示しています。
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).
日本語の概要は準備中です。原文の説明を表示しています。
Use when writing, testing, or preparing ANY contribution or pull request to the JSONbored/awesome-claude (HeyClaude) repo — adding a community content entry (agent/MCP server/skill/hook/command/rule/guide/collection/statusline), or making a platform/code change (website, registry package, MCP package, scripts). The repo has two separate review paths: a private, one-shot "HeyClaude submission gate" that decides single-file content PRs, and the shared gittensory-orb bot that posts an advisory readiness/linked-issue comment on platform/code PRs but does not itself merge or close content PRs. Unlike JSONbored/gittensory and JSONbored/metagraphed, a linked issue is OPTIONAL here — do not import their mandatory-linked-issue rule into this repo. Invoke for any "contribute to / open a PR against / submit an entry to / fix a bug in awesome-claude (HeyClaude)" task.
日本語の概要は準備中です。原文の説明を表示しています。
Publishes a local Markdown file to a user-specified Confluence location, creating a new page or updating an existing one through the Atlassian MCP server. Use when the user wants to post, publish, push, or sync a Markdown file to a Confluence space or page. Requires a configured Atlassian MCP server. Does not write or generate the Markdown itself — point it at an existing file, or use project-documentation-to-confluence for the document-then-publish flow, or plan-a-feature-to-confluence for the plan-then-publish flow. Does not publish to Jira — use work-items-to-jira.
日本語の概要は準備中です。原文の説明を表示しています。
Scan code, dependencies, containers, IaC and SBOMs with Snyk via its first-party MCP server: authenticate, trust a folder, run the right scanner, read the findings, fix and re-scan. Includes package-health checks before adding a dependency.
日本語の概要は準備中です。原文の説明を表示しています。
Diagnose malformed calls, retries, and unusable results after an agent selects an MCP tool.
日本語の概要は準備中です。原文の説明を表示しています。
Investigate MCP tool availability, discovery, and selection, including controlled adoption evaluations.
日本語の概要は準備中です。原文の説明を表示しています。
Investigate a Rezolus performance recording (.parquet, .rez, .dendro) through the rezolus MCP server. Discovery before query, verdicts and marks written back, links to the viewer.
日本語の概要は準備中です。原文の説明を表示しています。
Social Media Publisher. Takes approved content from outputs/ and schedules it across platforms via Blotato MCP. Generates infographic-style visuals (stat cards, framework diagrams, process graphics, quote graphics) for posts flagged by platform-specialist skills. Requires Blotato MCP to be configured. Run after /linkedin-writer, /threads-writer, /x-writer, or /caption-writer.
日本語の概要は準備中です。原文の説明を表示しています。
claude-mcp-plugin
日本語の概要は準備中です。原文の説明を表示しています。
Build TestDriver tests iteratively using MCP tools with visual feedback
日本語の概要は準備中です。原文の説明を表示しています。
麦当劳门店派对/包场/拼团的选址、成团调度与筹备助手。当用户想办生日派对、亲子派对、主题派对、品鉴会、读书会、麦麦体验营,或说「麦当劳派对」「派对拼团」「包场」「生日会怎么办」「哪家店能办派对」「还差几个人成团」「包场还是拼团划算」「帮我写拼团招募文案」「做一张派对邀请函」「孩子派对吃什么不超标」时使用。基于麦当劳官方 MCP(mcp.mcd.cn)的 party 系列工具:扫描全城场次、估算成团概率、对比包场与拼团成本、按官方营销活动日历挑最佳日期、审查儿童餐营养、生成招募卡与邀请函。
日本語の概要は準備中です。原文の説明を表示しています。
Expert SurrealDB 3 architect and developer skill (tracks v3.1.4+). SurrealQL mastery, multi-model data modeling (document, graph, vector, time-series, geospatial), schema design, security, deployment, performance tuning, SDK integration (JS, Python, Go, Rust, Java, .NET, C, PHP, Swift, Kotlin, Ruby), Surrealism WASM extensions, SurrealML scope coverage (preview), built-in MCP (v3.1+) and standalone SurrealMCP, LangChain Python integration, editor tooling (LSP v0.1.6, tree-sitter, CodeMirror v1.0.6, VS Code/JetBrains/Neovim/Zed), and ecosystem integrations (Surrealist v3.9, Surreal-Sync, SurrealFS, SurrealKit v0.7, n8n, Agent Skills, setup-surreal). Universal skill for 30+ AI agents.
日本語の概要は準備中です。原文の説明を表示しています。
Connects Claude Code, Codex, Cursor, and other MCP hosts to Writingmate for model discovery, text comparison, image generation, and video generation with Seedance, Sora, Veo, Kling, PixVerse, and other available models.
日本語の概要は準備中です。原文の説明を表示しています。
Ultimate MCP server for Civitai — search models, browse top images with prompts, download LoRAs/Checkpoints, analyze trends. Use when user asks about AI models, LoRAs, checkpoints, Stable Diffusion, Flux, image generation prompts, or Civitai.
日本語の概要は準備中です。原文の説明を表示しています。
Import Figma content into a HyperFrames composition — rendered assets, brand tokens, components, storyboard sections → reconstructed motion (frames read as states, not slides) (REST/CLI), Figma Motion animations (MCP), and shaders (MCP source / native export). Use when the user pastes a figma.com link or asks to bring a Figma design, frame, logo, brand, or animation into a video/composition.
日本語の概要は準備中です。原文の説明を表示しています。
IOTA blockchain MCP server providing wallet management with human-in-the-loop signing, Move smart contract build/test/publish, and on-chain queries via JSON-RPC and GraphQL. Use when interacting with IOTA network from AI coding agents, managing IOTA wallets, building or publishing Move packages, querying on-chain objects or transactions, or checking epoch and network statistics.
日本語の概要は準備中です。原文の説明を表示しています。
Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface (18 tools) available with --full flag. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.
日本語の概要は準備中です。原文の説明を表示しています。
Build MCP (Model Context Protocol) servers on Cloudflare Workers with tools, resources, and prompts.
日本語の概要は準備中です。原文の説明を表示しています。
思源任务笔记管理插件 MCP 工具总览技能。
日本語の概要は準備中です。原文の説明を表示しています。
Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).
日本語の概要は準備中です。原文の説明を表示しています。