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。
OneWave-AI/claude-skills3402026年10月2日 更新
無料GitHub で公開
personalization-at-scale
Generate unique personalized first lines for hundreds of prospects using company news, LinkedIn activity, and mutual connections. Saves 10+ hours of manual research per campaign. Use when you need personalized outreach at volume.
含まれるファイル（7）
- SKILL.md2.4 KB
- references/benchmarks.md1.8 KB
- references/example-campaigns.md1.6 KB
- references/fallbacks.md1.2 KB
- references/output-template.md2.5 KB
- references/patterns-by-type.md5.9 KB
- references/research-sources.md1.5 KB
SKILL.md（原文）
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。
Personalization at Scale
Generate hundreds of unique, researched first lines in minutes instead of hours, making cold outreach feel warm.
Contents
references/research-sources.md- signal sources, personalization styles, quality standardsreferences/patterns-by-type.md- sample first lines and tables for each angle (congrats, observation, mutual connection, company news, hiring, tech stack, thought leadership, shared background)references/fallbacks.md- role/stage/industry/competitor lines for prospects with no anglereferences/output-template.md- full campaign deliverable structurereferences/benchmarks.md- expected lift, A/B reference data, pro tips (do/don't)references/example-campaigns.md- worked campaign examples by persona
Workflow
-
Ingest the prospect list (CSV or pasted). Require First Name, Last Name, Title, Company; use LinkedIn URL, email, website, industry, size, and location when available.
-
Confirm preferences: which personalization styles to prioritize (1-3), tone (professional, casual, direct, consultative), and any exclusions (recency cutoff, personal topics, sensitive subjects).
-
Research each prospect across the sources in
references/research-sources.md. Identify the strongest, most recent, verifiable angle per prospect. -
Match each prospect to its angle and draft from the matching pattern in
references/patterns-by-type.md. For prospects with no angle, draft fromreferences/fallbacks.md. -
Generate 2-3 first-line options per prospect, each with a confidence score (High/Medium/Low) and notes on alternative angles. Follow the structure in
references/output-template.md. -
Quality-check the first 10 manually. Confirm each line is specific, recent, relevant, natural, and verifiable before scaling the batch.
-
Export in the requested format: CSV with personalization columns, merge fields for the outreach tool (Outreach, Salesloft), individual drafts, or copy-paste blocks.
-
Track response rates by personalization type and refresh personalizations every 30 days as activity changes.
See references/benchmarks.md for target success rates and references/example-campaigns.md for persona-specific approaches.
レビュー
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。
同じリポジトリのスキル
概要と使いどころ
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。
OneWave-AI/claude-skills3402026年10月2日 更新
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。
OneWave-AI/claude-skills3402026年10月2日 更新
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。
OneWave-AI/claude-skills3402026年10月2日 更新
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。
OneWave-AI/claude-skills3402026年10月2日 更新
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。
OneWave-AI/claude-skills3402026年10月2日 更新