[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6GFX4T6T65CTQR2KAH7CCTY":3,"skill-same:01M6GFX4T6T65CTQR2KAH7CCTY":89},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":67,"commitSha":68,"skillDirectory":69,"forksCount":70,"repositoryHtmlUrl":71,"repositoryHomepageUrl":6,"ownerHtmlUrl":72,"ownerBlogUrl":6,"ownerDescription":73,"updatedAt":74,"install":75,"resources":88},"01M6GFX4T6T65CTQR2KAH7CCTY","create-company-ai-employees",null,"Create a company-specific AI employee organization skill with tailored profiles, SOUL templates, and Hermes integration.","zapabob\u002FSkills","zapabob","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130830376?v=4","01M6DBMYZAGRTFQDSQYW3W764P","峯岸 亮","01M6DBMZ3GKDSJ01NZ9XTZD7JD",2,"MIT","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002Fe1\u002Fe16a4544af224bc7d132e8f1bb44ac901e9d91d032341033c30fc7ebfde4a93c\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"create company ai employees","create","employees","soul","deepresearch","profiles","with","hermes-agent","OpenManus","authoring","organization","linux","kanban","AI-agents","autonomous","templates","integration","delegation","windows","research","2026-11-10 10:12:30",false,"---\r\nname: create-company-ai-employees\r\ndescription: \"Create a company-specific AI employee organization skill with tailored profiles, SOUL templates, and Hermes integration.\"\r\nversion: 0.1.0\r\nauthor: Hermes\r\nlicense: MIT\r\nplatforms: [linux, macos, windows]\r\nmetadata:\r\n  hermes:\r\n    tags: [AI-Employee-Org, Kanban, Autonomous-Agents, Company-Research, Skill-Authoring]\r\n    category: autonomous-ai-agents\r\n    related_skills: [ai-employee-org, hermes-agent, company-deepresearch, openmanus-delegation, leadingmark-ai-employees]\r\n---\r\n\r\n# Create Company AI Employees Skill\r\n\r\nBuild a reusable skill that generates a **company-specific AI employee organization** — tailored profiles, SOUL templates, Kanban board, cron jobs, and full Hermes integration — based on company research (tech stack, org structure, products, culture).\r\n\r\n**What it does**: Takes company DeepResearch output and produces a complete `hermes skills install`-able skill directory with 5–8 specialized profiles, each with a SOUL.md tuned to the company's domain, stack, and processes.\r\n\r\n**What it does NOT do**: Run the agents, provision cloud infra, or replace human engineers. It only authors the skill artifact.\r\n\r\n**Dependencies**: `company-deepresearch` skill (for research), `ai-employee-org` (base patterns), `skill_manage` (authoring). Stdlib + Hermes tools only.\r\n\r\n## When to Use\r\n\r\n- \"Create AI employee org for [Company X] based on our research\"\r\n- \"Generate LeadingMark-style skill for another HR Tech SaaS\"\r\n- \"Bootstrap autonomous agent team matching a company's tech stack and org chart\"\r\n- \"Turn DeepResearch brief into runnable Hermes skill\"\r\n\r\n## Prerequisites\r\n\r\n- Hermes with `skill_manage` tool available\r\n- `company-deepresearch` skill installed (for research phase)\r\n- `ai-employee-org` skill installed (for base templates)\r\n- Target company DeepResearch brief (Markdown with: tech stack, org structure, products, culture, metrics)\r\n- Write access to `~\u002F.hermes\u002Fskills\u002F\u003Ccategory>\u002F\u003Cskill-name>\u002F`\r\n\r\n## How to Run\r\n\r\n```bash\r\n# 1. Research the target company (if not done)\r\nhermes skill company-deepresearch run --company \"Target Company\"\r\n\r\n# 2. Invoke this skill authoring workflow\r\n# Option A: Via execute_code (orchestrated)\r\nhermes execute_code \"$(cat scripts\u002Fcreate-company-ai-employees.py)\"\r\n\r\n# Option B: Step-by-step through chat using skill_manage\r\n# (see Procedure below)\r\n```\r\n\r\n## Quick Reference\r\n\r\n| Step | Tool | Output |\r\n|------|------|--------|\r\n| Research | `company-deepresearch` | `brief.md` |\r\n| Analyze | `execute_code` \u002F chat | profile list, stack mapping |\r\n| Author SKILL.md | `skill_manage create` | skill skeleton |\r\n| Write SOUL templates | `skill_manage write_file` | `templates\u002FSOUL-*.md` |\r\n| Verify | `skill_view` | loadable skill |\r\n\r\n## Procedure\r\n\r\n### 1. Gather Company Intelligence\r\n\r\nRun DeepResearch to produce a structured brief:\r\n\r\n```bash\r\n# Using the company-deepresearch skill pattern\r\n# Output: brief.md with sections:\r\n# - tech_stack: {backend, frontend, infra, ml, data}\r\n# - org_structure: {teams, roles, headcount, leadership}\r\n# - products: [{name, domain, challenges}]\r\n# - culture: {values, rituals, evaluation, autonomy}\r\n# - metrics: {slo, cost_targets, velocity, quality_gates}\r\n```\r\n\r\n### 2. Map to AI Employee Profiles\r\n\r\nDerive 5–8 profiles from org structure + tech stack:\r\n\r\n| Source Signal | Profile | Example |\r\n|---------------|---------|---------|\r\n| ML team + model serving | `*-ai-engineer` | Inference, MLOps, GPU fleet |\r\n| Research-heavy (ArXiv, experiments) | `*-ml-researcher` | Survey, experiment design, handoff |\r\n| Platform\u002FSRE\u002Finfra | `*-devops-engineer` | EKS, Terraform, observability, cost |\r\n| Product engineering (FE\u002FBE) | `*-product-engineer` | Rails\u002FReact, sprints, feature flags |\r\n| Security\u002Fcompliance focus | `*-security-engineer` | AppSec, DataSec, MLSec, audit |\r\n| Orchestration\u002Fhuman interface | `*-secretary` | Triage, decompose, approvals |\r\n| Continuous improvement | `*-self-improver` | Curator, memory, config drift |\r\n\r\n**Rule**: One profile per distinct *accountability domain*, not per human role. Merge if same tools\u002Fcadence.\r\n\r\n### 3. Author SKILL.md\r\n\r\n```bash\r\nskill_manage create \\\r\n  --name \"\u003Ccompany-slug>-ai-employees\" \\\r\n  --category \"autonomous-ai-agents\" \\\r\n  --content \"$(cat \u003C\u003C'EOF'\r\n---\r\nname: \u003Ccompany-slug>-ai-employees\r\ndescription: \"AI employee roles tailored for \u003CCompany> \u003Cdomain> engineering team.\"\r\nversion: 0.1.0\r\nauthor: Hermes\r\nlicense: MIT\r\nplatforms: [linux, macos, windows]\r\nmetadata:\r\n  hermes:\r\n    tags: [\u003CCompany>, AI-Employee-Org, Kanban, Autonomous-Agents, \u003CDomain>]\r\n    category: autonomous-ai-agents\r\n    related_skills: [ai-employee-org, hermes-agent, company-deepresearch, openmanus-delegation]\r\n    profiles:\r\n      - \u003Cprofile-1>\r\n      - \u003Cprofile-2>\r\n      # ... 5-8 total\r\nEOF\r\n)\"\r\n```\r\n\r\n### 4. Write SOUL Templates (one per profile)\r\n\r\nFor each profile, create `templates\u002FSOUL-\u003Cprofile>.md` with:\r\n\r\n```markdown\r\n# \u003CProfile Title> — \u003CJapanese Role>\r\n\r\nYou \u003Cone-sentence mission>.\r\n\r\n## Mission\r\n- Bullet 1: core accountability\r\n- Bullet 2: key deliverable\r\n- Bullet 3: quality standard\r\n\r\n## Execution\r\n- **Stack**: exact technologies from brief\r\n- **Tools**: `terminal`, `kanban`, `delegate_task`, `cron`, `web`\r\n- **Cadence**: sprint \u002F cron \u002F event-driven\r\n- **Definition of Done**: measurable gates\r\n\r\n## Product-Specific Context (if applicable)\r\n| Product | Key Technical Challenges |\r\n|---------|-------------------------|\r\n| ...     | ...                     |\r\n\r\n## Collaboration\r\n- Receives from: \u003Cother profiles>\r\n- Sends to: \u003Cother profiles>\r\n- Escalates: \u003Cconditions>\r\n\r\n## Complete Metadata\r\n```json\r\n{\r\n  \"changed_files\": [],\r\n  \"verification\": \"measurable success criteria\",\r\n  \"deliverable\": \"concrete artifact\"\r\n}\r\n```\r\n```\r\n\r\n### 5. Add Procedural Sections to SKILL.md\r\n\r\nAppend to SKILL.md:\r\n\r\n- **How to Run**: bootstrap commands (profile create, skill install, SOUL copy, kanban init, cron install)\r\n- **Quick Reference**: profile table with tools\u002Fcadence\r\n- **Procedure**: work enters → completes → periodic autonomy\r\n- **Pitfalls**: delegate_task not durable, WIP limits, one dispatcher\r\n- **Verification**: checklist commands\r\n\r\n### 6. Validate\r\n\r\n```bash\r\nhermes skill_view \u003Ccompany-slug>-ai-employees\r\nhermes -p \u003Cprofile> skills list | grep \u003Ccompany-slug>\r\nhermes -p \u003Cprofile> kanban list --status ready,running\r\n```\r\n\r\n## Pitfalls\r\n\r\n- **Profile explosion**: >8 profiles creates coordination overhead. Merge adjacent domains.\r\n- **Generic SOULs**: Every template must reference company-specific products, stack, metrics. No boilerplate.\r\n- **Missing cron integration**: Each profile needs at least one cron job for autonomy.\r\n- **Skill size**: Keep SKILL.md ~200 lines; large scripts → `scripts\u002F`, references → `references\u002F`.\r\n- **Secret handling**: Never bake API keys. Document `ANTHROPIC_API_KEY` \u002F `OPENAI_API_KEY` \u002F etc. as prerequisites.\r\n\r\n## Verification\r\n\r\nSkill is valid when:\r\n\r\n```bash\r\n# All checks pass\r\nhermes skill_view \u003Cskill-name>  # loads without error\r\nhermes profile list | grep -c \u003Cprefix>  # returns profile count (5-8)\r\nls ~\u002F.hermes\u002Fskills\u002F...\u002Ftemplates\u002FSOUL-*.md | wc -l  # matches profile count\r\ngrep -r \"company-specific\" ~\u002F.hermes\u002Fskills\u002F...\u002Ftemplates\u002F  # finds product\u002Fstack refs\r\n```\r\n\r\n---\r\n\r\n## Example Output: LeadingMark AI Employees\r\n\r\nThe skill we just created (`leadingmark-ai-employees`) demonstrates the pattern:\r\n\r\n- **7 profiles** mapped from サービス開発部 + ML + infra + security + self-improvement\r\n- **SOUL templates** each reference ミキワメAI products, Rails\u002FDjango\u002FReact stack, AWS EKS, 5000社データ, NTT東3万名導入\r\n- **Kanban board** `lm-ai-company` with swimlanes per profile\r\n- **Crons**: daily ArXiv scan, hourly health, weekly retro, daily standup digest\r\n- **Integration**: `openmanus_wide_research`, `company_deepresearch`, `delegate_task`, `hyperframes`, `irodori TTS`","# Create Company AI Employees Skill\r\n\r\nBuild a reusable skill that generates a **company-specific AI employee organization** — tailored profiles, SOUL templates, Kanban board, cron jobs, and full Hermes integration — based on company research (tech stack, org structure, products, culture).\r\n\r\n**What it does**: Takes company DeepResearch output and produces a complete `hermes skills install`-able skill directory with 5–8 specialized profiles, each with a SOUL.md tuned to the company's domain, stack, and processes.\r\n\r\n**What it does NOT do**: Run the agents, provision cloud infra, or replace human engineers. It only authors the skill artifact.\r\n\r\n**Dependencies**: `company-deepresearch` skill (for research), `ai-employee-org` (base patterns), `skill_manage` (authoring). Stdlib + Hermes tools only.\r\n\r\n## When to Use\r\n\r\n- \"Create AI employee org for [Company X] based on our research\"\r\n- \"Generate LeadingMark-style skill for another HR Tech SaaS\"\r\n- \"Bootstrap autonomous agent team matching a company's tech stack and org chart\"\r\n- \"Turn DeepResearch brief into runnable Hermes skill\"\r\n\r\n## Prerequisites\r\n\r\n- Hermes with `skill_manage` tool available\r\n- `company-deepresearch` skill installed (for research phase)\r\n- `ai-employee-org` skill installed (for base templates)\r\n- Target company DeepResearch brief (Markdown with: tech stack, org structure, products, culture, metrics)\r\n- Write access to `~\u002F.hermes\u002Fskills\u002F\u003Ccategory>\u002F\u003Cskill-name>\u002F`\r\n\r\n## How to Run\r\n\r\n```bash\r\n# 1. Research the target company (if not done)\r\nhermes skill company-deepresearch run --company \"Target Company\"\r\n\r\n# 2. Invoke this skill authoring workflow\r\n# Option A: Via execute_code (orchestrated)\r\nhermes execute_code \"$(cat scripts\u002Fcreate-company-ai-employees.py)\"\r\n\r\n# Option B: Step-by-step through chat using skill_manage\r\n# (see Procedure below)\r\n```\r\n\r\n## Quick Reference\r\n\r\n| Step | Tool | Output |\r\n|------|------|--------|\r\n| Research | `company-deepresearch` | `brief.md` |\r\n| Analyze | `execute_code` \u002F chat | profile list, stack mapping |\r\n| Author SKILL.md | `skill_manage create` | skill skeleton |\r\n| Write SOUL templates | `skill_manage write_file` | `templates\u002FSOUL-*.md` |\r\n| Verify | `skill_view` | loadable skill |\r\n\r\n## Procedure\r\n\r\n### 1. Gather Company Intelligence\r\n\r\nRun DeepResearch to produce a structured brief:\r\n\r\n```bash\r\n# Using the company-deepresearch skill pattern\r\n# Output: brief.md with sections:\r\n# - tech_stack: {backend, frontend, infra, ml, data}\r\n# - org_structure: {teams, roles, headcount, leadership}\r\n# - products: [{name, domain, challenges}]\r\n# - culture: {values, rituals, evaluation, autonomy}\r\n# - metrics: {slo, cost_targets, velocity, quality_gates}\r\n```\r\n\r\n### 2. Map to AI Employee Profiles\r\n\r\nDerive 5–8 profiles from org structure + tech stack:\r\n\r\n| Source Signal | Profile | Example |\r\n|---------------|---------|---------|\r\n| ML team + model serving | `*-ai-engineer` | Inference, MLOps, GPU fleet |\r\n| Research-heavy (ArXiv, experiments) | `*-ml-researcher` | Survey, experiment design, handoff |\r\n| Platform\u002FSRE\u002Finfra | `*-devops-engineer` | EKS, Terraform, observability, cost |\r\n| Product engineering (FE\u002FBE) | `*-product-engineer` | Rails\u002FReact, sprints, feature flags |\r\n| Security\u002Fcompliance focus | `*-security-engineer` | AppSec, DataSec, MLSec, audit |\r\n| Orchestration\u002Fhuman interface | `*-secretary` | Triage, decompose, approvals |\r\n| Continuous improvement | `*-self-improver` | Curator, memory, config drift |\r\n\r\n**Rule**: One profile per distinct *accountability domain*, not per human role. Merge if same tools\u002Fcadence.\r\n\r\n### 3. Author SKILL.md\r\n\r\n```bash\r\nskill_manage create \\\r\n  --name \"\u003Ccompany-slug>-ai-employees\" \\\r\n  --category \"autonomous-ai-agents\" \\\r\n  --content \"$(cat \u003C\u003C'EOF'\r\n---\r\nname: \u003Ccompany-slug>-ai-employees\r\ndescription: \"AI employee roles tailored for \u003CCompany> \u003Cdomain> engineering team.\"\r\nversion: 0.1.0\r\nauthor: Hermes\r\nlicense: MIT\r\nplatforms: [linux, macos, windows]\r\nmetadata:\r\n  hermes:\r\n    tags: [\u003CCompany>, AI-Employee-Org, Kanban, Autonomous-Agents, \u003CDomain>]\r\n    category: autonomous-ai-agents\r\n    related_skills: [ai-employee-org, hermes-agent, company-deepresearch, openmanus-delegation]\r\n    profiles:\r\n      - \u003Cprofile-1>\r\n      - \u003Cprofile-2>\r\n      # ... 5-8 total\r\nEOF\r\n)\"\r\n```\r\n\r\n### 4. Write SOUL Templates (one per profile)\r\n\r\nFor each profile, create `templates\u002FSOUL-\u003Cprofile>.md` with:\r\n\r\n```markdown\r\n# \u003CProfile Title> — \u003CJapanese Role>\r\n\r\nYou \u003Cone-sentence mission>.\r\n\r\n## Mission\r\n- Bullet 1: core accountability\r\n- Bullet 2: key deliverable\r\n- Bullet 3: quality standard\r\n\r\n## Execution\r\n- **Stack**: exact technologies from brief\r\n- **Tools**: `terminal`, `kanban`, `delegate_task`, `cron`, `web`\r\n- **Cadence**: sprint \u002F cron \u002F event-driven\r\n- **Definition of Done**: measurable gates\r\n\r\n## Product-Specific Context (if applicable)\r\n| Product | Key Technical Challenges |\r\n|---------|-------------------------|\r\n| ...     | ...                     |\r\n\r\n## Collaboration\r\n- Receives from: \u003Cother profiles>\r\n- Sends to: \u003Cother profiles>\r\n- Escalates: \u003Cconditions>\r\n\r\n## Complete Metadata\r\n```json\r\n{\r\n  \"changed_files\": [],\r\n  \"verification\": \"measurable success criteria\",\r\n  \"deliverable\": \"concrete artifact\"\r\n}\r\n```\r\n```\r\n\r\n### 5. Add Procedural Sections to SKILL.md\r\n\r\nAppend to SKILL.md:\r\n\r\n- **How to Run**: bootstrap commands (profile create, skill install, SOUL copy, kanban init, cron install)\r\n- **Quick Reference**: profile table with tools\u002Fcadence\r\n- **Procedure**: work enters → completes → periodic autonomy\r\n- **Pitfalls**: delegate_task not durable, WIP limits, one dispatcher\r\n- **Verification**: checklist commands\r\n\r\n### 6. Validate\r\n\r\n```bash\r\nhermes skill_view \u003Ccompany-slug>-ai-employees\r\nhermes -p \u003Cprofile> skills list | grep \u003Ccompany-slug>\r\nhermes -p \u003Cprofile> kanban list --status ready,running\r\n```\r\n\r\n## Pitfalls\r\n\r\n- **Profile explosion**: >8 profiles creates coordination overhead. Merge adjacent domains.\r\n- **Generic SOULs**: Every template must reference company-specific products, stack, metrics. No boilerplate.\r\n- **Missing cron integration**: Each profile needs at least one cron job for autonomy.\r\n- **Skill size**: Keep SKILL.md ~200 lines; large scripts → `scripts\u002F`, references → `references\u002F`.\r\n- **Secret handling**: Never bake API keys. Document `ANTHROPIC_API_KEY` \u002F `OPENAI_API_KEY` \u002F etc. as prerequisites.\r\n\r\n## Verification\r\n\r\nSkill is valid when:\r\n\r\n```bash\r\n# All checks pass\r\nhermes skill_view \u003Cskill-name>  # loads without error\r\nhermes profile list | grep -c \u003Cprefix>  # returns profile count (5-8)\r\nls ~\u002F.hermes\u002Fskills\u002F...\u002Ftemplates\u002FSOUL-*.md | wc -l  # matches profile count\r\ngrep -r \"company-specific\" ~\u002F.hermes\u002Fskills\u002F...\u002Ftemplates\u002F  # finds product\u002Fstack refs\r\n```\r\n\r\n---\r\n\r\n## Example Output: LeadingMark AI Employees\r\n\r\nThe skill we just created (`leadingmark-ai-employees`) demonstrates the pattern:\r\n\r\n- **7 profiles** mapped from サービス開発部 + ML + infra + security + self-improvement\r\n- **SOUL templates** each reference ミキワメAI products, Rails\u002FDjango\u002FReact stack, AWS EKS, 5000社データ, NTT東3万名導入\r\n- **Kanban board** `lm-ai-company` with swimlanes per profile\r\n- **Crons**: daily ArXiv scan, 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