hybridlabor-api

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production.

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AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.

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。

Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.

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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.

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AI-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your task.

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Use when generating 3D meshes, executing text-to-CAD, or reconstructing scenes via TRELLIS, TripoSR, or Text-to-CAD local engines.

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Use for real-time performance and multimedia operator work: technical show-control execution (signal flows, OSC/DMX, MCP orchestration, hardware limits) for tools like grandMA3, Resolume, Unreal, Rhino, Vectorworks, and Adobe MCP.

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Ask which skill or flow fits your situation. A route through AOS's skills for work that travels idea to ship, plus a catalogue of the available options for lookup. Use when unsure where to start, or when picking between overlapping choices.

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Standards and workflows for writing, formatting, sanitizing, and publishing high-quality GitHub repositories, complementing openwiki-skill.

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Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

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Linear multi-agent build pipeline with file hand-offs in production_artifacts/, run after /bdbrainstorm or /grill-me. This is the linear variant — no state.json, no repair loop, no dispatcher graph — distinct from startcycle-graph, which adds durable state and automated escalation. Use when an approved plan should be built, when the user types /startcycle or "run a startcycle", or when you pick a startcycle variant from the situation yourself (no user prompt needed).

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Use when running the autonomous multi-agent build pipeline after /bdbrainstorm or /grill-me, when the user types /startcycle-graph or "run a startcycle", or when a task needs durable state, a review repair loop and an automated quality gate. Routes to the startcycle-dispatch Dynamic Workflow, which reads production_artifacts/state.json and invokes Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, and Shipping in turn per .agents/graph.md's edge table — the agents never invoke each other.

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Use when a task needs a small, throwaway multi-agent fan-out (a couple of parallel workers plus a review pass) in ANY project — trigger phrases "spawn a few parallel agents", "fan out", "quick worker team" — without the full /startcycle-graph contract, no .agents/graph.md bootstrap, no state.json schema, no persistent files. Roles run on the session model unless `.aos/pipeline.json` overrides one (an external CLI can take the worker step) and portable across machines that may not have Antigravity/OpenCode/Codex installed.

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Use when one Claude Code session must supervise several others on this machine — adopting sessions the user started by hand, or spawning workers itself. Covers roster, status requests, a GO board, idle notices, and the GO-token protocol. Works with AOS alone; the AO daemon is optional.

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Use before starting any significant build or before shipping: problem-framing pre-flight, one-way/two-way door classification, ADR-lite decision logging, and post-ship outcome loop. Complements godmode-shipping (technical gate) and bdbresilience (error recovery).

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Utilizes the DaVinci Resolve MCP servers to control timeline editing, media analysis, color grading, and Fusion/Fairlight scripting.

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Use when acting as the authoritative design lead for all frontend work, enforcing brand discovery, Anti-Slop rules, DTCG design tokens, fluid motion, and data-driven design generation.

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Use when global skill for BDB Synapse (3D Codebase Visualizer) integration.

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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.

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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.

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Utilizes the Blender MCP server and addon to build 3D assets, apply materials, inspect scenes, and script bpy.

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BDB Shipping Godmode, the final gatekeeper for production releases. Use when running pre-launch checks, feature-flag rollouts, or rollback planning under Spec-Driven Development before a release ships.

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Use when acting as the multi-project orchestrator and lead coordinator across repositories using the Agent Orchestrator (AO) daemon. Spawns, inspects, coordinates, and reviews parallel coding agents in isolated Git worktrees.

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。