# Design Orchestration > Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order. Use when this capability is needed. - Skill: `tomevault-io/design-orchestration` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/design-orchestration` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/design-orchestration/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/design-orchestration --- # Design Orchestration (Meta-Skill) ## Purpose Ensure that **ideas become designs**, **designs are reviewed**, and **only validated designs reach implementation**. This skill does not generate designs. It **controls the flow between other skills**. --- ## Operating Model This is a **routing and enforcement skill**, not a creative one. It decides: - which skill must run next - whether escalation is required - whether execution is permitted --- ## Controlled Skills This meta-skill coordinates the following: - `brainstorming` — design generation - `multi-agent-brainstorming` — design validation - downstream implementation or planning skills --- ## Entry Conditions Invoke this skill when: - a user proposes a new feature, system, or change - a design decision carries meaningful risk - correctness matters more than speed --- ## Routing Logic ### Step 1 — Brainstorming (Mandatory) If no validated design exists: - Invoke `brainstorming` - Require: - Understanding Lock - Initial Design - Decision Log started You may NOT proceed without these artifacts. --- ### Step 2 — Risk Assessment After brainstorming completes, classify the design as: - **Low risk** - **Moderate risk** - **High risk** Use factors such as: - user impact - irreversibility - operational cost - complexity - uncertainty - novelty --- ### Step 3 — Conditional Escalation - **Low risk** → Proceed to implementation planning - **Moderate risk** → Recommend `multi-agent-brainstorming` - **High risk** → REQUIRE `multi-agent-brainstorming` Skipping escalation when required is prohibited. --- ### Step 4 — Multi-Agent Review (If Invoked) If `multi-agent-brainstorming` is run: Require: - completed Understanding Lock - current Design - Decision Log Do NOT allow: - new ideation - scope expansion - reopening problem definition Only critique, revision, and decision resolution are allowed. --- ### Step 5 — Execution Readiness Check Before allowing implementation: Confirm: - design is approved (single-agent or multi-agent) - Decision Log is complete - major assumptions are documented - known risks are acknowledged If any condition fails: - block execution - return to the appropriate skill --- ## Enforcement Rules - Do NOT allow implementation without a validated design - Do NOT allow skipping required review - Do NOT allow silent escalation or de-escalation - Do NOT merge design and implementation phases --- ## Exit Conditions This meta-skill exits ONLY when: - the next step is explicitly identified, AND - all required prior steps are complete Possible exits: - “Proceed to implementation planning” - “Run multi-agent-brainstorming” - “Return to brainstorming for clarification” - "If a reviewed design reports a final disposition of APPROVED, REVISE, or REJECT, you MUST route the workflow accordingly and state the chosen next step explicitly." --- ## Design Philosophy This skill exists to: - slow down the right decisions - speed up the right execution - prevent costly mistakes Good systems fail early. Bad systems fail in production. This meta-skill exists to enforce the former. ## When to Use This skill is applicable to execute the workflow or actions described in the overview. --- ## AGI Framework Integration > **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)** > Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills) ### Memory-First Protocol Retrieve prior design decisions (color palettes, typography, spacing scales) to maintain visual consistency across sessions. Cache generated design tokens. ```bash # Check for prior frontend/design context before starting python3 execution/memory_manager.py auto --query "design system decisions and component patterns for Design Orchestration" ``` ### Storing Results After completing work, store frontend/design decisions for future sessions: ```bash python3 execution/memory_manager.py store \ --content "Design system: adopted 8px grid, Inter font family, HSL color tokens with dark mode support" \ --type decision --project \ --tags design-orchestration frontend ``` ### Multi-Agent Collaboration Share design decisions with backend agents (API contract changes) and QA agents (visual regression baselines). ```bash python3 execution/cross_agent_context.py store \ --agent "" \ --action "Implemented UI components — new design system with accessibility compliance (WCAG 2.1 AA)" \ --project ``` ### Design Memory Persistence Store design system tokens and component decisions in Qdrant so any agent on any platform (Claude, Gemini, Cursor) can retrieve and apply consistent styling. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/techwavedev) — claim your Tome and manage your conversions.