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maiconfz--feature-exploration-planner--feature-exploration-planning

Orchestrates feature intake, landscape research, options analysis, and feature-brief synthesis.

3|1|Updated May 2, 2026
Search Tags:#requirements#feature planning#options analysis#product discovery#multi-agent workflow#feature brief#landscape research
One-click install
npx skills add https://github.com/agents-repo/registry --skill maiconfz-feature-exploration-planner-feature-exploration-planning-agents-repo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: maiconfz--feature-exploration-planner--feature-exploration-planning
Source: https://github.com/agents-repo/registry/tree/main/.cursor/skills/maiconfz/feature-exploration-planner/maiconfz--feature-exploration-planner--feature-exploration-planning
Command: npx skills add https://github.com/agents-repo/registry --skill maiconfz-feature-exploration-planner-feature-exploration-planning-agents-repo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Turning a rough feature idea into a structured, decision-ready brief requires coordinated research and analysis that is easy to skip or do inconsistently. This Skill orchestrates that entire planning workflow so ideas are clarified, researched, compared, and documented before any code is written. ## Core Features & Use Cases - Ask-first intake: Clarifies the feature idea through structured intake with a single clarification loop, carrying unresolved blockers into open questions. - Routed landscape research: Supports interactive, automatic, or skip research modes, invoking the appropriate researcher agent and logging assumptions in automatic mode. - Options and definition synthesis: Runs an options analyst and a feature-definition planner to produce a final feature-brief, optionally written to a workspace file. - Use Case: You have a vague idea for a new dashboard feature. Provide the idea text, choose automatic research mode, and receive a feature-brief with intake summary, landscape report, options comparison, and open questions ready to paste into a GitHub issue. ## Quick Start Ask the agent to plan a new feature by providing your feature idea text and choosing a research mode of interactive, automatic, or skip.

Frequently Asked Questions about maiconfz--feature-exploration-planner--feature-exploration-planning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn a feature idea into a structured feature brief?▼

Provide the feature idea as prompt text or a workspace file path, then choose a research mode. The workflow runs intake, landscape research, options analysis, and definition planning, returning a feature-brief plus supporting artifacts.

What research modes are available for feature landscape analysis?▼

Three modes exist: interactive, automatic, and skip. Interactive asks you questions during research, automatic runs autonomously and records an assumption log, and skip produces an empty landscape report.

Can this workflow write the feature brief to a file?▼

Yes. Set the optional output-path input and the workflow writes the feature-brief to that workspace file. If omitted, the brief is returned as text in the flow outputs.

Does the feature exploration planner implement code?▼

No. This is a planning-only workflow and refuses implementation requests. It suggests next steps such as creating a GitHub issue from the brief and running a separate implementation planner.

What happens if I provide a GitHub issue URL instead of an idea?▼

The workflow stops and points you to the github-interactive-issue-implementation-planner package instead. It does not invoke that package from within this flow.

What happens when intake blockers cannot be resolved?▼

The workflow asks clarifying questions once and re-runs intake a single time. If blockers remain, it carries them into open-questions at handoff rather than looping indefinitely.

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