Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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。
Analyze meeting transcripts to extract decisions, action items, blockers, sentiment, and generate follow-up emails. Use when user provides meeting notes, transcripts, or recordings and needs structured summaries or action tracking.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Transform meeting transcripts into actionable insights, decisions, and follow-ups.
Activate when the user:
Extract Meeting Metadata
Identify Decisions Made
Extract Action Items
Identify Blockers and Risks
Analyze Discussion Sentiment
Extract Key Topics Discussed
Generate Follow-Up Communications
# Meeting Summary: [Title]
**Date**: [Date] | **Participants**: [Names]
## Executive Summary
[2-3 sentence overview of meeting purpose and outcome]
## Decisions Made
1. **[Decision]**
- Owner: [Name]
- Rationale: [Why]
- Status: Final / Needs approval
## Action Items
| Priority | Action | Owner | Deadline | Status |
|----------|--------|-------|----------|--------|
| High | [Task] | [Name] | [Date] | Not started |
| Medium | [Task] | [Name] | [Date] | Not started |
## Blockers & Risks
1. **[Blocker]** - [Impact] - Needs: [Action]
2. **[Risk]** - [Mitigation plan]
## Key Discussion Points
- [Topic 1]: [Summary]
- [Topic 2]: [Summary]
## Open Questions
1. [Question] - Owner: [Who will answer]
## Sentiment Analysis
- **Overall Tone**: [productive/tense/etc.]
- **Team Alignment**: [high/medium/low]
- **Concerns Raised**: [Summary]
## Follow-Up Email Draft
Subject: Action Items from [Meeting Title] - [Date]
Hi team,
Thanks for joining today's [meeting type]. Here are our key outcomes:
**Decisions:**
- [Decision 1]
**Your Action Items:**
[Name]: [Task] by [Date]
**Blockers:**
- [Blocker] - please [action]
Next meeting: [Date/Time]
Best,
[Your name]
User: "Analyze this standup transcript" Response: Extract blockers mentioned → List action items per person → Flag impediments → Note team velocity concerns → Generate summary with focus on blockers
User: "Create action items from this product planning meeting" Response: Identify all decisions (feature prioritization) → Extract action items (design mockups, tech spec) → Assign owners → Set deadlines → Create tracking table → Draft follow-up email
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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。
Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.
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 to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.
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。
Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
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。
Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.
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。
Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.
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。