Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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Generates properly tagged UTM links with consistent naming conventions. Maintains a UTM registry file (utm-registry.json) to enforce naming consistency, prevent duplicates, generate short links, and output ready-to-copy links for LinkedIn, email, social, and ads.
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Generate UTM-tagged links under a single naming-governance system: a utm-registry.json that enforces canonical conventions, prevents duplicates and naming drift, and outputs platform-ready links for LinkedIn, email, social, and ads.
references/naming-conventions.md -- enforced rules, UTM parameter reference, canonical source/medium lists, campaign naming pattern.references/platform-variants.md -- per-platform link templates (LinkedIn, email, social, paid ads).references/registry-schema.md -- utm-registry.json structure plus validation-report and output-summary templates.references/bulk-and-registry-ops.md -- bulk generation, registry commands (audit/add/report/export), error handling, integrations, best practices.utm-registry.json tracking all links and enforcing conventions.[a-z0-9-] characters, auto-correct known aliases, reject unknown source/medium values (suggest closest match), validate URL form, enforce the 50-character limit. Report corrections using the template in references/registry-schema.md. Full rules in references/naming-conventions.md.utm-registry.json (create if missing). Return existing link on exact duplicates, allow-with-warning on near duplicates, block on naming conflicts (same campaign, different casing/hyphenation).{base_url}?utm_source=&utm_medium=&utm_campaign=[&utm_term=][&utm_content=][&utm_id=]. Append with & if the base URL already has query params, URL-encode values, and preserve existing query params and fragment.references/platform-variants.md.utm-registry.json per the schema in references/registry-schema.md, refreshing stats and timestamps.references/registry-schema.md.For bulk runs, registry commands (audit, add source/medium, campaign report, CSV export), error handling, and integration notes, see references/bulk-and-registry-ops.md.
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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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