[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71MYZP8ZY8P0HKN64PYNVCJ":3,"skill-same:01M71MYZP8ZY8P0HKN64PYNVCJ":77},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":15,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":49,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":54,"ownerHtmlUrl":55,"ownerBlogUrl":56,"ownerDescription":6,"updatedAt":57,"install":58,"resources":71},"01M71MYZP8ZY8P0HKN64PYNVCJ","enrich-lead",null,"Instant lead enrichment. Drop a name, company, LinkedIn URL, or email and get the full contact card with email, phone, title, company intel, and next actions.","monoes\u002Fmonomind","monoes","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F276744696?v=4","01M71KWF37AJ2NJBP3KWBVSDGT","01M71KWF4CSF8ADH0M6HA09VD2",23,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fenrich-lead\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fenrich-lead\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"lead","enrich lead","enrich","get","company","title","URL","with","card","lead enrichment","github","drop","phone","apollo","linkedin","work","knowledge","enrichment","email","actions","2026-11-10 10:56:23",false,"---\nname: enrich-lead\ndescription: \"Instant lead enrichment. Drop a name, company, LinkedIn URL, or email and get the full contact card with email, phone, title, company intel, and next actions.\"\ntags: []\ntools: []\nlicense: Apache-2.0\nsource: https:\u002F\u002Fgithub.com\u002Fanthropics\u002Fknowledge-work-plugins\nsource_path: \"partner-built\u002Fapollo\u002Fskills\u002Fenrich-lead\"\nsource_commit: 8444efcd48f7012f09797778a36a33e73d0861f4\n---\n# Enrich Lead\n\nTurn any identifier into a full contact dossier. The user provides identifying info via \"$ARGUMENTS\".\n\n## Examples\n\n- `\u002Fapollo:enrich-lead Tim Zheng at Apollo`\n- `\u002Fapollo:enrich-lead https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Ftimzheng`\n- `\u002Fapollo:enrich-lead sarah@stripe.com`\n- `\u002Fapollo:enrich-lead Jane Smith, VP Engineering, Notion`\n- `\u002Fapollo:enrich-lead CEO of Figma`\n\n## Step 1 — Parse Input\n\nFrom \"$ARGUMENTS\", extract every identifier available:\n- First name, last name\n- Company name or domain\n- LinkedIn URL\n- Email address\n- Job title (use as a matching hint)\n\nIf the input is ambiguous (e.g. just \"CEO of Figma\"), first use `mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search` with relevant title and domain filters to identify the person, then proceed to enrichment.\n\n## Step 2 — Enrich the Person\n\n> **Credit warning**: Tell the user enrichment consumes 1 Apollo credit before calling.\n\nUse `mcp__claude_ai_Apollo_MCP__apollo_people_match` with all available identifiers:\n- `first_name`, `last_name` if name is known\n- `domain` or `organization_name` if company is known\n- `linkedin_url` if LinkedIn is provided\n- `email` if email is provided\n- Set `reveal_personal_emails` to `true`\n\nIf the match fails, try `mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search` with looser filters and present the top 3 candidates. Ask the user to pick one, then re-enrich.\n\n## Step 3 — Enrich Their Company\n\nUse `mcp__claude_ai_Apollo_MCP__apollo_organizations_enrich` with the person's company domain to pull firmographic context.\n\n## Step 4 — Present the Contact Card\n\nFormat the output exactly like this:\n\n---\n\n**[Full Name]** | [Title]\n[Company Name] · [Industry] · [Employee Count] employees\n\n| Field | Detail |\n|---|---|\n| Email (work) | ... |\n| Email (personal) | ... (if revealed) |\n| Phone (direct) | ... |\n| Phone (mobile) | ... |\n| Phone (corporate) | ... |\n| Location | City, State, Country |\n| LinkedIn | URL |\n| Company Domain | ... |\n| Company Revenue | Range |\n| Company Funding | Total raised |\n| Company HQ | Location |\n\n---\n\n## Step 5 — Offer Next Actions\n\nAsk the user which action to take:\n\n1. **Save to Apollo** — Create this person as a contact via `mcp__claude_ai_Apollo_MCP__apollo_contacts_create` with `run_dedupe: true`\n2. **Add to a sequence** — Ask which sequence, then run the sequence-load flow\n3. **Find colleagues** — Search for more people at the same company using `mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search` with `q_organization_domains_list` set to this company\n4. **Find similar people** — Search for people with the same title\u002Fseniority at other companies\n","# Enrich Lead\n\nTurn any identifier into a full contact dossier. The user provides identifying info via \"$ARGUMENTS\".\n\n## Examples\n\n- `\u002Fapollo:enrich-lead Tim Zheng at Apollo`\n- `\u002Fapollo:enrich-lead https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Ftimzheng`\n- `\u002Fapollo:enrich-lead sarah@stripe.com`\n- `\u002Fapollo:enrich-lead Jane Smith, VP Engineering, Notion`\n- `\u002Fapollo:enrich-lead CEO of Figma`\n\n## Step 1 — Parse Input\n\nFrom \"$ARGUMENTS\", extract every identifier available:\n- First name, last name\n- Company name or domain\n- LinkedIn URL\n- Email address\n- Job title (use as a matching hint)\n\nIf the input is ambiguous (e.g. just \"CEO of Figma\"), first use `mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search` with relevant title and domain filters to identify the person, then proceed to enrichment.\n\n## Step 2 — Enrich the Person\n\n> **Credit warning**: Tell the user enrichment consumes 1 Apollo credit before calling.\n\nUse `mcp__claude_ai_Apollo_MCP__apollo_people_match` with all available identifiers:\n- `first_name`, `last_name` if name is known\n- `domain` or `organization_name` if company is known\n- `linkedin_url` if LinkedIn is provided\n- `email` if email is provided\n- Set `reveal_personal_emails` to `true`\n\nIf the match fails, try `mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search` with looser filters and present the top 3 candidates. Ask the user to pick one, then re-enrich.\n\n## Step 3 — Enrich Their Company\n\nUse `mcp__claude_ai_Apollo_MCP__apollo_organizations_enrich` with the person's company domain to pull firmographic context.\n\n## Step 4 — Present the Contact Card\n\nFormat the output exactly like this:\n\n---\n\n**[Full Name]** | [Title]\n[Company Name] · [Industry] · [Employee Count] employees\n\n| Field | Detail |\n|---|---|\n| Email (work) | ... |\n| Email (personal) | ... (if revealed) |\n| Phone (direct) | ... |\n| Phone (mobile) | ... |\n| Phone (corporate) | ... |\n| Location | City, State, Country |\n| LinkedIn | URL |\n| Company Domain | ... |\n| Company Revenue | Range |\n| Company Funding | Total raised |\n| Company HQ | Location |\n\n---\n\n## Step 5 — Offer Next Actions\n\nAsk the user which action to take:\n\n1. **Save to Apollo** — Create this person as a contact via `mcp__claude_ai_Apollo_MCP__apollo_contacts_create` with `run_dedupe: true`\n2. **Add to a sequence** — Ask which sequence, then run the sequence-load flow\n3. **Find colleagues** — Search for more people at the same company using `mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search` with `q_organization_domains_list` set to this company\n4. **Find similar people** — Search for people with the same title\u002Fseniority at other companies\n",{"name":5,"tags":44,"tools":45,"source":46,"license":14,"description":7,"source_path":47,"source_commit":48},[],[],"https:\u002F\u002Fgithub.com\u002Fanthropics\u002Fknowledge-work-plugins","partner-built\u002Fapollo\u002Fskills\u002Fenrich-lead","8444efcd48f7012f09797778a36a33e73d0861f4","main","f7cd4595d0f8959822163e14f9787117765c931a","packages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fenrich-lead",2,"https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind","https:\u002F\u002Fmonoes.github.io\u002Fmonomind\u002F","https:\u002F\u002Fgithub.com\u002Fmonoes","https:\u002F\u002Fmonoes.me","2026-11-10 01:53:48",{"source":8,"skillName":5,"commands":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add monoes\u002Fmonomind --skill enrich-lead",{"tool":64,"command":65},"bunx","bunx skills add monoes\u002Fmonomind --skill enrich-lead",{"tool":67,"command":68},"pnpm","pnpm dlx skills add monoes\u002Fmonomind --skill enrich-lead","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fenrich-lead\u002FSKILL.md",true,[72],{"path":73,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":15},"LICENSE.txt","LICENSE","许可证",11607,[78,105,142,168,191,217],{"skillNo":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":84,"publishedAt":104},"01M71PB3SHWKMNJM6MD65VX8D6","zk-steward","Org role guidance for a ZK steward: engineer zero-knowledge proof systems with circuit design, SNARK vs STARK choice and security review. This is zero-knowledge cryptography, not Zettelkasten note-taking.","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fzk-steward\u002FSKILL.md",[],[85,86,87,88,89,90,91,35,92,93,94,95,96,97,98,99,100,101,102,103],"zk","zk steward","steward","zero-knowledge","engineer","choice","design","impact","query","snark","review","monomind","security review","stark","zettelkasten","cryptography","security","org","blockchain","2026-11-10 13:02:02",{"skillNo":106,"name":107,"nameZh":6,"description":108,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":109,"licenseFileUrl":110,"sourceHtmlUrl":111,"categories":112,"keywords":123,"publishedAt":104},"01M71PB18SDG28WBKPKJNB814K","writing-plans","Use when you have a spec or requirements for a multi-step coding task and must write an implementation plan before touching code. Produces bite-sized TDD tasks with exact file paths, code and commands for an engineer with zero context.","MIT","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fwriting-plans\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fwriting-plans\u002FSKILL.md",[113,118],{"categoryNo":114,"categoryName":115,"taxonomyType":116,"taxonomyTypeDesc":117},"01JBSEEDCAT000000000000018","写作与文案","SCENARIO","使用场景",{"categoryNo":119,"categoryName":120,"taxonomyType":121,"taxonomyTypeDesc":122},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[124,125,126,89,127,128,129,130,93,131,132,133,134,135,136,137,138,139,140,141],"writing","writing plans","plans","superpowers","implementation plan","when","you","code","tasks","plan","product","write","commands","paths","suggest","coding","context","ZeRO",{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":146,"sourceHtmlUrl":147,"categories":148,"keywords":152,"publishedAt":104},"01M71PAXFM488X9ARXK0T04TF5","write-spec","Write a feature spec or PRD from a problem statement or feature idea. Use when turning a vague idea or user request into a structured document, scoping a feature with goals and non-goals, defining success metrics and acceptance criteria, or breaking a big ask into a phased spec.","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fwrite-spec\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fwrite-spec\u002FSKILL.md",[149],{"categoryNo":150,"categoryName":151,"taxonomyType":121,"taxonomyTypeDesc":122},"01JBSEEDCAT000000000000031","产品经理",[135,153,154,155,156,35,157,129,158,159,34,134,160,161,162,163,164,165,166,167],"write spec","spec","user request","problem","acceptance","ask","vague","request","scoping","idea","metrics","feature","problem statement","use","document",{"skillNo":169,"name":170,"nameZh":6,"description":171,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":172,"sourceHtmlUrl":173,"categories":174,"keywords":178,"publishedAt":104},"01M71PASSZY800C0RPEARBS918","write-query","Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc.","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fwrite-query\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fwrite-query\u002FSKILL.md",[175],{"categoryNo":176,"categoryName":177,"taxonomyType":121,"taxonomyTypeDesc":122},"01JBSEEDCAT000000000000033","数据分析师",[93,135,179,180,181,182,35,166,129,183,184,26,185,34,29,186,187,188,189,190],"write query","postgres","for","snowflake","best practices","natural-language","multi","sql","https","syntax","plugins","data",{"skillNo":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":203,"publishedAt":104},"01M71PAPTX0T3PF6ETFVR96SJJ","workflow-automation","Org role guidance for workflow automation: build and maintain CI\u002FCD definitions in GitHub Actions or equivalent: triggers, jobs, matrices, caching. Covers path filters, dependency caching, parallel jobs, timeouts and fail-fast ordering.","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fworkflow-automation\u002FSKILL.md",[197,200],{"categoryNo":198,"categoryName":199,"taxonomyType":116,"taxonomyTypeDesc":117},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":201,"categoryName":202,"taxonomyType":116,"taxonomyTypeDesc":117},"01JBSEEDCAT000000000000023","Skill与智能体开发",[204,205,206,207,181,38,208,209,210,92,211,212,213,93,96,29,214,215,216,187],"Workflow Automation","automation","workflow","parallel","ci","triggers","github actions","maintain","filters","caching","build","dependency","devops",{"skillNo":218,"name":219,"nameZh":6,"description":220,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":221,"categories":222,"keywords":224,"publishedAt":104},"01M71PAM19Z1XTV9NPCFSE2MY8","workflow-architect","Org role guidance for a workflow architect: map full workflow trees for systems, user journeys and agents, covering every branch and failure. Covers discovering workflows from code, handoff contracts, timeouts, recovery paths and observable state.","https:\u002F\u002Fgithub.com\u002Fmonoes\u002Fmonomind\u002Fblob\u002Fmain\u002Fpackages\u002F@monomind\u002Fcli\u002Forg-skills\u002Fworkflow-architect\u002FSKILL.md",[223],{"categoryNo":201,"categoryName":202,"taxonomyType":116,"taxonomyTypeDesc":117},[206,225,226,227,228,229,230,181,231,232,131,233,234,235,96,29,236,237,187,238],"workflow architect","architect","trees","user journeys","branch","planning","map","workflows","architecture","state","leadership","recovery","operations","systems"]