返回顶部
t

team-builder

Discover, compose, and activate specialist teams from 3 rosters — OpenClaw Core (CEO/Artist), Agency Division (55+ specialists), and Research Lab (autonomous experiment loops via Karpathy's autoresearch). Planner proposes optimal teams; Reviewer validates deliverables.

作者: admin | 来源: ClawHub
源自
ClawHub
版本
V 2.0.0
安全检测
已通过
202
下载量
0
收藏
概述
安装方式
版本历史

team-builder

# Team Builder Compose the right team for any job by drawing from three rosters of specialists. The Research Lab uses Karpathy's [autoresearch](https://github.com/karpathy/autoresearch) methodology for autonomous experiment loops. ## Quick Start — Scripts ### 1. Browse available agents ```bash bash {baseDir}/scripts/roster.sh # all 3 rosters bash {baseDir}/scripts/roster.sh -r agency # agency only bash {baseDir}/scripts/roster.sh -d engineering # one division bash {baseDir}/scripts/roster.sh -s "frontend" # search bash {baseDir}/scripts/roster.sh -v # verbose descriptions bash {baseDir}/scripts/roster.sh -j # JSON output ``` ### 2. Generate a team proposal ```bash bash {baseDir}/scripts/plan.sh "Build a portfolio dashboard with pie charts" bash {baseDir}/scripts/plan.sh --mode sprint "Optimize image generation prompts using autoresearch" bash {baseDir}/scripts/plan.sh -o proposal.md "Analyze astronomy photos for star classification" ``` The planner auto-detects task domains (engineering, creative, research, marketing, operations, spatial) and proposes the right-sized team (micro/sprint/full). ### 3. Activate a specialist ```bash bash {baseDir}/scripts/activate.sh --division engineering --agent frontend-developer bash {baseDir}/scripts/activate.sh --division testing --agent evidence-collector bash {baseDir}/scripts/activate.sh --division testing --list bash {baseDir}/scripts/activate.sh --file reference/agency-agents-main/design/design-ui-designer.md bash {baseDir}/scripts/activate.sh --division engineering --agent ai-engineer --personality-only ``` Outputs the agent's full personality definition for use in delegation prompts. ### 4. Run QA review ```bash bash {baseDir}/scripts/review.sh --task "Portfolio dashboard" bash {baseDir}/scripts/review.sh --task "Image pipeline" --criteria criteria.txt --pass evidence bash {baseDir}/scripts/review.sh --task "LLM training optimization" --pass reality bash {baseDir}/scripts/review.sh --task "Full product" --pass both -o review.md ``` Generates review checklists (Evidence Collector Pass 1 + Reality Checker Pass 2) and logs to `~/.openclaw/team-reviews/`. ### 5. Run a Research Lab experiment ```bash bash {baseDir}/scripts/experiment.sh --setup /path/to/project # initialize experiment bash {baseDir}/scripts/experiment.sh --run /path/to/project # run one experiment cycle bash {baseDir}/scripts/experiment.sh --status /path/to/project # show ledger ``` See `references/TEAM-RESEARCH.md` for the full autoresearch methodology and working examples. ## The Three Rosters ### 1. Core Team (`references/TEAM-CORE.md`) The permanent OpenClaw agents. Always available, always running. | Agent | Role | Workspace | |-------|------|-----------| | **CEO** | Leader, orchestrator, final authority | `.openclaw/workspace/` | | **Artist** | Image generation, visual analysis | `.openclaw/workspace-artist/` | ### 2. Agency Division (`references/TEAM-AGENCY.md`) 55+ specialist agents across 9 divisions. Activated on demand from `reference/agency-agents-main/`. | Division | Agents | Key Specialists | |----------|--------|-----------------| | Engineering | 7 | Frontend Developer, Backend Architect, AI Engineer, DevOps | | Design | 7 | UI Designer, UX Architect, Image Prompt Engineer | | Marketing | 8 | Growth Hacker, Content Creator, Social Media | | Product | 3 | Sprint Prioritizer, Trend Researcher, Feedback Synthesizer | | Project Management | 5 | Senior PM, Studio Producer, Experiment Tracker | | Testing | 7 | Evidence Collector, Reality Checker, API Tester | | Support | 6 | Analytics Reporter, Finance Tracker, Legal Compliance | | Spatial Computing | 6 | XR Architect, visionOS Engineer | | Specialized | 7 | Agents Orchestrator, Data Analytics, LSP Engineer | ### 3. Research Lab (`references/TEAM-RESEARCH.md`) Autonomous experiment loops adapted from Karpathy's [autoresearch](https://github.com/karpathy/autoresearch). Set up a measurable experiment, run it in a fixed time budget, keep improvements, discard failures, loop forever. Source code reference: `reference/autoresearch-master/` (program.md, train.py, prepare.py) ## Cross-Team Workflow Examples ### Image Analysis + Research Loop ``` Artist (image acquisition) + Research Lab (analysis loop) + AI Engineer (classification) ``` ### Visual Content Pipeline ``` Artist (generation) + Image Prompt Engineer (prompts) + Visual Storyteller (narrative) ``` ### Dashboard / UI Feature Build ``` Senior PM (scope) + Frontend Developer (build) + Evidence Collector (QA) ``` ### Autonomous LLM Training (autoresearch) ``` Research Lab (experiment loop on train.py) + AI Engineer (architecture suggestions) → 12 experiments/hour, ~100 overnight, fully autonomous ``` ### Full Product Launch ``` CEO (orchestrate) + Engineering (build) + Design (UX) + Marketing (launch) + Testing (validate) ``` ## Handoff Protocol When passing work between specialists: ``` ## Handoff | Field | Value | |-------|-------| | From | [Agent Name] | | To | [Agent Name] | | Task | [What needs to be done] | | Priority | [Critical / High / Medium / Low] | ## Context - Current state: [What's been done] - Relevant files: [File paths] ## Deliverable - What is needed: [Specific output] - Acceptance criteria: - [ ] [Criterion 1] - [ ] [Criterion 2] ## Quality - Evidence required: [What proof looks like] - Reviewer: [Who validates] ``` For complete handoff templates: `reference/agency-agents-main/strategy/coordination/handoff-templates.md` ## NEXUS Pipeline Modes | Mode | Scale | Agents | Timeline | |------|-------|--------|----------| | **Micro** | Single task/fix | 1-3 | Hours-days | | **Sprint** | Feature or MVP | 5-10 | 1-2 weeks | | **Full** | Complete product | 10+ | Weeks-months | ## Reference Files | File | Contents | |------|----------| | `SKILL.md` | This file — overview, scripts, quick start | | `scripts/roster.sh` | Browse and search all agent rosters | | `scripts/plan.sh` | Generate team proposals from task descriptions | | `scripts/activate.sh` | Load agent personality definitions | | `scripts/review.sh` | Generate QA review checklists | | `scripts/experiment.sh` | Run autoresearch experiment loops | | `references/TEAM-CORE.md` | CEO/Artist — roles and interactions | | `references/TEAM-AGENCY.md` | All 55+ Agency specialists indexed by division | | `references/TEAM-RESEARCH.md` | Autonomous experiment methodology (autoresearch) | | `references/PLANNER.md` | Job analysis → team proposal workflow (detailed) | | `references/REVIEWER.md` | QA validation workflow with quality gates | | `references/PROOF-OF-WORK.md` | Example proposals showing cross-roster teams |

标签

skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

方式一:安装 SkillHub 和技能

帮我安装 SkillHub 和 oc-team-builder-1776384063 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 oc-team-builder-1776384063 技能

通过命令行安装

skillhub install oc-team-builder-1776384063

下载 Zip 包

⬇ 下载 team-builder v2.0.0

文件大小: 30.13 KB | 发布时间: 2026-4-17 15:34

v2.0.0 最新 2026-4-17 15:34
Rebuild with executable scripts, autoresearch experiment loops, removed trading/IG references

Archiver·手机版·闲社网·闲社论坛·羊毛社区· 多链控股集团有限公司 · 苏ICP备2025199260号-1

Powered by Discuz! X5.0   © 2024-2025 闲社网·线报更新论坛·羊毛分享社区·http://xianshe.com

p2p_official_large
返回顶部