Plan an MVP-mode phase — captures an "As a / I want to / So that" user story, runs SPIDR splitting, then delegates to plan-phase
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Orchestrator role: Parse phase argument, validate phase, gather user story, run SPIDR check, persist mode + story to ROADMAP.md, then route to plan-phase. </objective>
<execution_context> @${CLAUDE_PLUGIN_ROOT}/workflows/mvp-phase.md @${CLAUDE_PLUGIN_ROOT}/references/user-story-template.md @${CLAUDE_PLUGIN_ROOT}/references/spidr-splitting.md @${CLAUDE_PLUGIN_ROOT}/references/planner-mvp-mode.md </execution_context>
<runtime_note>
Copilot (VS Code): Use vscode_askquestions wherever this workflow calls AskUserQuestion. They are equivalent — vscode_askquestions is the VS Code Copilot implementation of the same interactive question API.
TEXT_MODE fallback: Set TEXT_MODE=true if --text is present in $ARGUMENTS OR text_mode from init JSON is true. When TEXT_MODE is active, replace every AskUserQuestion call with a plain-text numbered list and ask the user to type their choice number.
</runtime_note>
Flags:
--force — Allow operating on in_progress / completed phases--text — Use plain-text numbered lists instead of TUI menus
</context>
<output_format>
When MVP planning concludes (user story written, ROADMAP.md updated, plan-phase delegated), emit a Next Up continuation block following the pattern in references/continuation-format.md:
## ✓ Phase N MVP-Planned — vertical slice captured)## ▶ Next Up heading with /gsd:execute-phase N (TDD execution)`/clear` then: before the command/clear is safe — /gsd:resume-work restores position from HANDOFF.json if you change your mind)MVP planning is a deliberate slice-of-the-cake exercise; clearing context before execution keeps TDD focused on the captured story rather than the planning conversation. </output_format>
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
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。
Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
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。
Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
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。
Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
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。
Audit whether a website can be found, crawled, and cited by AI answer engines such as ChatGPT Search, Perplexity, Google AI Overviews, and Microsoft Copilot. Use when someone asks why their brand is missing from AI answers, whether AI crawlers can read their site, how to get cited by ChatGPT or Perplexity, or asks for a GEO or AEO (generative / answer engine optimization) review. Produces a citation baseline across buyer-intent prompts, a crawler-access check, a citability review of named pages, and a ranked fix list. Not for keyword rank tracking, paid search, or pages behind a login.
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。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
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。