Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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Writes conversion-focused landing page copy - headlines, subheads, value propositions, feature and benefit blocks, social proof, FAQs, and CTA button text - using PAS, AIDA, or StoryBrand. Use when the user wants words for a landing page, sales page, product or pricing page, waitlist page, homepage hero, or ad-to-page flow, including rewriting weak copy, generating headline or CTA variants for A/B tests, or turning a product description into page sections. Use landing-page-optimizer instead for auditing an existing page's performance, and a frontend skill for building the page itself.
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Write landing page copy that makes one reader take one action. The copy is the deliverable; layout and code are out of scope unless asked.
Build the brief. Pull these from the conversation, attached docs, or the product's existing site before asking anything. Ask only for what is missing and blocking:
Write the message hierarchy before any sections. One sentence each:
If you cannot fill one of these, flag the gap instead of papering over it. Every section below expands one of these four lines.
Pick the framework from the reader's awareness:
Section-by-section guidance for each framework is in references/frameworks.md.
Draft the page in the order hero, problem, solution/features, how it works, proof, pricing (if relevant), FAQ, final CTA. Cut sections the product does not need; a waitlist page may be hero + three benefits + CTA.
Write variants where they matter: 3 headline options (different angles: outcome, pain, mechanism) and 2 CTA options. Say which you would test first and why.
Run the checks below, fix what fails, then deliver using references/output-template.md.
[TESTIMONIAL: ops lead at a customer, quote about time saved] and list every placeholder at the end.Brief: scheduling tool for independent physical therapy clinics; action is "book a demo"; readers come from a Google search for "PT clinic no-show software"; proof is one clinic that cut no-shows from 18% to 7%.
Message hierarchy:
Hero (PAS, since searchers already feel the pain):
Note what it avoids: no "revolutionary", no invented clinic count, and the headline only works for this product.
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Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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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.
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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.
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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.
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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.
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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.
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