本文へ移動
cccskills
無料GitHub で公開

linkedin-sales-navigator-alt

Build targeted prospect lists by analyzing LinkedIn profiles, extracting job titles, companies, locations, and recent activity. Identifies decision-makers, tracks job changes for warm outreach, and enriches contact data. Use when users need to find prospects, build lead lists, or track decision-maker movements.

インストール方法を見る

含まれるファイル(5)

  • SKILL.md2.6 KB
  • references/campaigns.md1.2 KB
  • references/examples.md1.3 KB
  • references/output-template.md6.8 KB
  • references/tools-and-export.md1.8 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。

LinkedIn Sales Navigator Alternative

Find and qualify prospects on LinkedIn without expensive subscriptions, using only publicly available information.

Contents

  • references/output-template.md — full prospect-list Markdown structure and section layout
  • references/campaigns.md — segmented campaign playbooks (new-in-role, account-based, event follow-up)
  • references/tools-and-export.md — contact-finding methods, tool stack, CSV/CRM export formats
  • references/examples.md — trigger phrases, example request, best practices

Compliance

Work only with publicly available information and respect LinkedIn's Terms of Service. Encourage official LinkedIn tools where appropriate. Aggregate public data for legitimate business development only.

Workflow

  1. Define the Ideal Customer Profile (ICP). Capture industry/sector, company size (employees, revenue), geography, tech stack, and funding stage.

  2. Identify decision-maker personas. Map the primary buyer, influencers, the economic buyer (budget holder), and the technical buyer (evaluation team).

  3. Build the search strategy. Set job-title patterns, company criteria, location filters, seniority level, and description keywords. Choose a list-building approach: account-based, role-based, industry-based, event-based (job changes, funding rounds), or geography-based.

  4. Collect and enrich data (public info only). Compile name, title, company, size, location, industry, public activity, and shared connections. Verify company details, find contact information, add personalization context, and score lead quality. See references/tools-and-export.md for discovery and verification methods.

  5. Prioritize and segment. Tag hot leads (recent job changes), warm leads (shared connections), and cold leads (no prior contact). Group by account for campaigns.

  6. Deliver the prospect list. Format the output per references/output-template.md, attach relevant campaign playbooks from references/campaigns.md, and provide export-ready data per references/tools-and-export.md.

Deliver a targeted, researched set of qualified prospects with personalization context — not just a list of names. See references/examples.md for trigger phrases and best practices.

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

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-skills3392026年10月2日 更新

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-skills3392026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-skills3392026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-skills3392026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-skills3392026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-skills3392026年10月2日 更新

OneWave-AI のスキルをすべて見る

このスキルの問題を報告する