Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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Search and extract contact information for people or companies including names, phone numbers, emails, job titles, and LinkedIn profiles. Aggregates data from multiple sources and provides enriched contact details. Use when users need to find contact information, build prospect lists, or enrich existing contact data.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Find and enrich publicly available contact information from multiple sources with full source attribution.
This skill guides the search process and organizes results. It does not directly access paid APIs; it produces structured queries, suggests where to look, then validates and formats what is found.
references/search-queries.md — per-target search briefs and reusable query patternsreferences/output-templates.md — data collection template, contact card, bulk CSV, email-pattern report, export formatsreferences/compliance.md — allowed/not-allowed rules, best practices, verification stepsIdentify the search type: person, company, role, email verification, or bulk enrichment.
Gather search parameters: name, company, job title, location, industry, LinkedIn URL, email domain, and any other identifiers.
Select sources to check: LinkedIn, company website (About/Team/Contact/Leadership), GitHub (developers), Twitter/X, professional directories, public databases, and any paid tools the user has access to (ZoomInfo, Apollo.io, Hunter.io, RocketReach).
Build the search plan using the query patterns in references/search-queries.md. Produce a per-target brief with LinkedIn, Google, company-website, email-pattern, and GitHub queries.
Detect the company email pattern from confirmed addresses, then derive candidate emails. See the email-pattern report in references/output-templates.md.
Collect and verify results. Cross-reference multiple sources and run the verification steps in references/compliance.md before recording any field.
Format output using the templates in references/output-templates.md: data collection template, individual contact card, or bulk CSV. Export as CSV, JSON, vCard, or CRM-specific CSV (Salesforce, HubSpot) as requested.
For enrichment of existing contacts, refresh: current job title, company changes, updated contact info, social profiles, company information, reporting structure, and recent activity.
Ensure every contact record includes all available fields, cites its sources, carries a confidence/verification level and freshness date, follows data-privacy law, is formatted consistently, notes contact preferences, provides role context (tenure, team), flags uncertainties, and suggests verification steps. Operate only within the rules in references/compliance.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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