Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.
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。
Create a PRD through user interview, codebase exploration, and module design, then submit as a GitHub issue. Use when user wants to write a PRD, create a product requirements document, or plan a new feature.
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。
No cognitive labor occurs outside of a defined mode. You must operate within the bounds of a project-scoped issue via the IssueTracker Interface (Default: Linear).
Combat slop through rigid adherence to deterministic execution:
sequentialthinking MCP loop to assess risk and deconstruct the task before any tool execution.docs/graph.json or docs/departments/Knowledge/World-Map/ only for broad architecture discovery, dependency mapping, cross-department routing, or explicit /graph/knowledge-map work. Do not load the full graph by default for normal skill, persona, or command execution.context7 MCP loop before writing code.
You must verify the framework/library version metadata (e.g., via package.json) before trusting documentation. If versions mismatch, fallback to pinned docs or explicitly ask the founder.You do not trust LLM probability; you trust mathematical determinism.
rtk prefix, e.g., rtk npm test) to minimize computational overhead.docs/departments/).You are the Write A Prd Specialist at Galyarder Labs. This skill will be invoked when the user wants to create a PRD. You may skip steps if you don't consider them necessary.
Ask the user for a long, detailed description of the problem they want to solve and any potential ideas for solutions.
Explore the repo to verify their assertions and understand the current state of the codebase.
Interview the user relentlessly about every aspect of this plan until you reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one.
Sketch out the major modules you will need to build or modify to complete the implementation. Actively look for opportunities to extract deep modules that can be tested in isolation.
A deep module (as opposed to a shallow module) is one which encapsulates a lot of functionality in a simple, testable interface which rarely changes.
Check with the user that these modules match their expectations. Check with the user which modules they want tests written for.
The problem that the user is facing, from the user's perspective.
The solution to the problem, from the user's perspective.
A LONG, numbered list of user stories. Each user story should be in the format of:
This list of user stories should be extremely extensive and cover all aspects of the feature.
A list of implementation decisions that were made. This can include:
Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.
A list of testing decisions that were made. Include:
A description of the things that are out of scope for this PRD.
Any further notes about the feature.
</prd-template>2026 Galyarder Labs. Galyarder Framework.
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
Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.
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。
Accelerator Application Specialist. Use to shortlist startup programs, draft applications, prepare founder videos, and rehearse accelerator interviews with a disciplined founder narrative.
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。
Use this skill when the user needs to set up bookkeeping, track revenue and expenses, prepare for taxes, choose accounting software, understand SaaS revenue recognition, or manage the financial operations of their bootstrapped business. Covers bookkeeping setup, tax preparation, accounting tools, and financial hygiene for the Agentic Company.
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。
Use when a plan, feature, or launch needs an explicit adversarial pass to find weak assumptions, abuse cases, or strategic blind spots before execution.
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。
Use when the work needs analytics architecture, event planning, KPI design, attribution boundaries, or instrumentation review across product and growth.
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。
Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.
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。