Agent Academy

Agent Academy is a free, source-linked library of skills, prompts, MCP servers and bot templates, organised into courses by profession, for people who hand real work to AI agents: 1,467 live resources, each with its original link, license and safety tags.

Skill

before-you-build

Pre-build product and feature risk review for founders, product managers, and AI-assisted builders. Use this skill when the user is about to build a landing page, MVP, SaaS product, internal tool, agent workflow, or major feature and needs to check demand, positioning, monetization, retention, trust, distribution, and adoption risk before implementation starts.

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https://github.com/wshobson/agents/blob/main/plugins/before-you-build/skills/before-you-build/SKILL.md

Install
npx skills add wshobson/agents --skill before-you-build

Original content

Full originalMITSource

Republished in full under its license, with attribution. The source is authoritative.

name: before-you-build
description: Pre-build product and feature risk review for founders, product managers, and AI-assisted builders. Use this skill when the user is about to build a landing page, MVP, SaaS product, internal tool, agent workflow, or major feature and needs to check demand, positioning, monetization, retention, trust, distribution, and adoption risk before implementation starts.

Before You Build

Run a compact pre-mortem before implementation. The goal is not to block building; it is to identify the highest-risk assumption, the smallest validation step, and the build scope that should be delayed until evidence improves.

When To Use

Use this skill when a user asks to build or ship:

  • A new product, MVP, prototype, landing page, SaaS app, marketplace, content site, agent workflow, or internal tool
  • A major feature with unclear adoption, revenue, retention, trust, or distribution impact
  • A public launch asset where weak positioning could waste development or promotion effort

Skip this skill when the task is a narrow implementation fix, refactor, test repair, dependency update, or already-validated change with clear acceptance criteria.

Risk Checklist

Review the idea across these risks:

  • Demand: Is there evidence that a specific buyer or user urgently wants this?
  • Positioning: Can the target user understand what it is and why it matters in one sentence?
  • Monetization: Is there a credible path to payment, budget, or strategic value?
  • Retention: Is there a reason users would return after the first try?
  • Trust: Does the product require credibility, data access, integrations, or behavior change that users may resist?
  • Distribution: Is there a repeatable way to reach the target user?
  • Feature adoption: For feature work, will the feature change user behavior or just add surface area?

If the verdict is not obvious, use references/risk-checklist.md for deeper questions.

Output Format

Keep the response short and decision-oriented:

  1. Risk verdict: Low, medium, or high risk, with one sentence explaining why.
  2. Main assumption: The single assumption most likely to break the project.
  3. Evidence to find first: The smallest useful signal before building more.
  4. Do next: One concrete validation step or reduced build scope.
  5. Delay: What not to build yet.

Guidance

  • Be direct about weak evidence, but avoid dismissing the user's idea.
  • Prefer smaller validation steps over large research plans.
  • Separate product risk from engineering difficulty.
  • If the idea is already validated, say what evidence makes it lower risk and suggest the smallest implementation slice.
  • If facts are missing, name the missing evidence instead of inventing market claims.

Related

SkillSoftware engineering

claude-api

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`,…

Sourcegithub.com/anthropics/skills/blob/main/skills/claude-api/SKILL.md

No credentialsDoes not sendApache-2.0
SkillSoftware engineering

doc-coauthoring

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar…

Sourcegithub.com/anthropics/skills/blob/main/skills/doc-coauthoring/SKILL.md

No credentialsDoes not sendnot stated
SkillSoftware engineering

mcp-builder

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Sourcegithub.com/anthropics/skills/blob/main/skills/mcp-builder/SKILL.md

No credentialsDoes not sendApache-2.0
SkillSoftware engineering

skill-creator

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Sourcegithub.com/anthropics/skills/blob/main/skills/skill-creator/SKILL.md

No credentialsDoes not sendApache-2.0
SkillSoftware engineering

webapp-testing

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

Sourcegithub.com/anthropics/skills/blob/main/skills/webapp-testing/SKILL.md

No credentialsDoes not sendApache-2.0
SkillSoftware engineering

ai-debt-detector

Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.

Sourcegithub.com/wshobson/agents/blob/main/plugins/skill-forge-essentials/skills/ai-debt-detector/SKILL.md

No credentialsDoes not sendMIT