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Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order.
--- name: design-orchestration-c318765e032e description: Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order. risk: unknown source: community date_added: '2026-02-27' --- # 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-INTEGRATION-START --> ## 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 <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 "<your-agent>" \ --action "Implemented UI components — new design system with accessibility compliance (WCAG 2.1 AA)" \ --project <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. <!-- AGI-INTEGRATION-END -->--- name: design-orchestration-c318765e032e description: Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order. risk: unknown source: community date_added: '2026-02-27' --- # 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-INTEGRATION-START --> ## 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 <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 "<your-agent>" \ --action "Implemented UI components — new design system with accessibility compliance (WCAG 2.1 AA)" \ --project <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. <!-- AGI-INTEGRATION-END -->
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.