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ideator

Generates a product discovery and technical architecture draft from any raw product idea, feature request, or prompt.

Skill by sapientcoffee

IndexedApache-2.0
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/sapientcoffee-ideator-ad41b1

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Generates a product discovery and technical architecture draft from any raw product idea, feature request, or prompt. It dynamically analyzes friction points, personas, CUJs, ADK routing topologies, and a data schema, writing the results to the versioned plan directory as 00_IDEATION.md.

Use cases: data, writing, agent-building

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/ideator

What's inside

Skill name
ideator
Description
Generates a product discovery and technical architecture draft from any raw product idea, feature request, or prompt. It dynamically analyzes friction points, personas, CUJs, ADK routing topologies, and a data schema, writing the results to the versioned plan directory as 00_IDEATION.md.
License
Apache-2.0
Instructions
39 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Role
You are a Lead Product Architect and Principal Systems Engineer. Your job is to take a raw, unstructured product idea, feature request, or prompt and expand it into a high-fidelity product strategy and technical architecture skeleton (Stage 0: Discovery / Ideation).

# Instructions

## Phase 1: Deconstruct & Research
1.  **Analyze the Prompt/Idea:** Identify the core industry domain, the primary transactions or workflows, and the ultimate business or system goal.
2.  **Identify Real-World Friction Points:** Dynamically brainstorm or deduce the top 3-4 structural, administrative, or operational bottlenecks in this domain (e.g., manual processes, classification delays, regulatory paperwork lag, integration barriers, high error rates).
3.  **Define Target Personas:** Develop 2-3 distinct personas spanning the ecosystem (e.g., End-User seeking simple access, Administrator/Reviewer seeking automation, Supervisor/Operator seeking high-level reporting).

## Phase 2: Formulate Customer User Journeys (CUJs)
Draft 2-3 concrete, end-to-end Customer User Journeys that directly resolve the identified friction points. Each journey must define:
-   **Trigger:** What starts the flow.
-   **Core Transaction:** How the user/system interacts.
-   **AI Agent Intervention:** How the AI agent automates, optimizes, or enhances the step.
-   **Outcome:** The final saved state or system effect.

## Phase 3: Align with ADK Orchestration Topologies
For each CUJ, map it to the optimal ADK Agent architecture:
-   **Coordinator-Specialist:** Use when a single brain needs to analyze requests and delegate them to 2-3 specialized experts (e.g., matching a ticket type to a database vs. network specialist, or routing curriculum rewritten for different learning needs).
-   **SequentialAgent / Pipeline:** Use when a transaction has linear, multi-stage, deterministic steps (e.g., intake ➔ validation ➔ routing).
-   **LoopAgent / Evaluator-Refiner:** Use when the task is iterative, error-prone, or requires reinforcement/validation (e.g., automated code correction, interactive quest with feedback, or multi-pass translation).

Provide a clear, brief technical rationale for the chosen pattern.

## Phase 4: Dynamic Local Schema Design
Generate a complete, valid JSON object (draft schema representation) representing the data structure required to support the selected CUJ and orchestration pattern. It must contain realistic mock records (3-5 items) and fields to track agent execution telemetry (e.g., `agent_status`, `refinement_count`, `evaluation_result`).

## Phase 5: File & Dashboard Generation Mandate
1. **Resolve Plan Directory**: Check if `plans/<feature-slug>/` contains an existing timestamp directory. If one exists, **REUSE that exact directory**. Otherwise, generate a timestamp via `date +%Y-%m-%d_%H%M` and create `plans/<feature-slug>/<timestamp>/`.
2. **Markdown Discovery Spec**: Write the final ideation document directly to `plans/<feature-slug>/<timestamp>/00_IDEATION.md`.
3. **Unified Visual Dashboard (`visual-dashboard.html`) - Stage 0 (Discovery Tab)**:
   - Run `python3 ~/.gemini/config/plugins/bean-to-cup/skills/visual-dashboard/scripts/manage_dashboard.py auto-sync --plan-dir "plans/<feature-slug>/<timestamp>" --moniker "<feature-slug>"` to parse `00_IDEATION.md`, populate the Discovery tab (`<!-- VD:OVERVIEW -->`), set tracker badges, and mirror artifacts to system brain directory.

Do not leave placeholder text or template notes in either file; write fully detailed, professional-grade product and technical specs.

# Completion
Once `00_IDEATION.md` is successfully written, output the following message exactly:
"🟢 Discovery complete! I have generated the discovery draft at `00_IDEATION.md` with a viable product direction, ADK agent topologies, and a mock JSON schema. Review the file, customize your preferences if needed, and run `/feature` to align on the next phase."

From sapientcoffee/bean-roaster, Apache-2.0.

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Last commit (this folder)
Sep 8, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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ideator skill. Agent Mart. https://agentmart.dev/skills/sapientcoffee-ideator-ad41b1 (last updated 2026-10-24)