/agent-evals
Use when measuring how well an AI agent handles a recurring kind of task. Builds a small eval set, runs it, and raises the difficulty once the agent passes.
erkamyaman/dhh-p-bloom-agent-skills
DHH's Rails World 2026 opening keynote, turned into agent skills for working with AI coding agents
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Indexed skills
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Skills
9 total/agent-security-basics
Use when letting AI agents run code, install packages or touch real systems. Covers sandboxing, least privilege and quarantine basics.
/architecture-for-agents
Use when structuring a codebase that AI agents will edit heavily. Weighs duplication against abstraction now that repeating code and keeping copies in sync is cheap.
/async-delegation
Use when you have several independent jobs for AI agents. Splits work into parallel tasks, hands them off like to coworkers, and reviews results in batches.
/black-box-review
Use when reviewing code an AI agent wrote, especially in a language or area you don't know well. Judges the result through tests and behaviour instead of reading every line.
/cli-for-your-app
Use when making an app or library usable by a person's own AI agent. Designs a command-line interface so agents can drive the app without a built-in chatbot.
/native-vs-web
Use when deciding whether an app should be native, web, or hybrid (Ionic/Capacitor) now that agents make native code cheaper to produce.
/outcome-prompting
Use when giving an AI coding agent a job. Turns a task into a problem-and-outcome brief with acceptance checks, instead of step-by-step instructions.
/overnight-optimization
Use when you want an AI agent to improve performance, size or startup time of a project over a long unattended run, with tests as a safety gate.
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