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。
Designs pricing strategies for products and services. Takes product/service, costs, target market, competitors. Analyzes cost-plus, value-based, competitor-based, penetration, premium models. Researches competitor pricing. Generates pricing-strategy.md with recommended model, price points, tier structure, discount policies, annual vs monthly analysis, sensitivity to churn, expansion revenue modeling.
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Design data-driven pricing strategies that maximize revenue, align with market positioning, and scale with the business across B2B SaaS, consumer products, services, marketplaces, and physical goods.
references/required-inputs.md -- Inputs to gather before starting (product, market, competition, business context).references/analysis-framework.md -- The five pricing models to evaluate (cost-plus, value-based, competitor-based, penetration, premium).references/output-template.md -- Full pricing-strategy.md structure to populate.references/best-practices.md -- Best practices, trigger phrases, and a worked example.Gather inputs. Collect product, cost, market, and competitor information. See references/required-inputs.md. If anything is missing, ask before proceeding.
Research competitors. Use WebSearch and WebFetch to find current competitor pricing. Look for official pricing pages (search "[competitor] pricing"), G2/Capterra/TrustRadius comparisons, recent blog posts or press releases about pricing changes, and Crunchbase for funding and growth signals.
Analyze the market. Determine where the product sits in the competitive landscape using market reports, analyst commentary, and customer reviews that mention pricing.
Build the cost model. Fill in the cost structure with the user. When exact numbers are unavailable, use industry benchmarks and note the assumptions.
Evaluate all five pricing models. Score each model against the specific product and market context using the framework in references/analysis-framework.md. Do not skip a model; even when one is obviously wrong, explain why.
Design the tier structure. Create tiers that align with customer segments, create natural upgrade paths, and maximize expansion revenue.
Model the financials. Project revenue, churn, expansion, and cash flow under multiple scenarios.
Write the strategy document. Generate the full pricing-strategy.md following references/output-template.md. Use real numbers from the research, not placeholders.
For full best practices, trigger phrases, and a worked example, see references/best-practices.md.
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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。