writing-for-agents

Write skills, AGENTS.md, and CLAUDE.md documents that agents follow predictably.

10|3|Updated Jul 18, 2019
One-click install
npx skills add https://github.com/tanqimin/MyFavsORM --skill writing-for-agents-tanqimin
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: writing-for-agents
Source: https://github.com/tanqimin/MyFavsORM/tree/main/.agents/skills/writing-for-agents
Command: npx skills add https://github.com/tanqimin/MyFavsORM --skill writing-for-agents-tanqimin

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Documents written for AI agents often fail unpredictably: agents miss referenced material, rush steps, or ignore instructions. This Skill provides a systematic reference for writing any document an agent consumes—skills, AGENTS.md, CLAUDE.md, or pointer-reached docs—so the agent follows the same process every run. ## Core Features & Use Cases - Context pointer design: Rules for writing descriptions and pointer lines that reliably trigger the agent to reach out-of-context material, with branch-based trigger wording. - Information hierarchy guidance: A ladder model (in-file steps, in-file reference, disclosed reference) plus progressive disclosure and co-location principles to keep documents legible and focused. - Completion criteria and splitting: Techniques for writing checkable, exhaustive step completion criteria, and deciding when to split documents by sequence or invocation. - Use Case: When authoring a new agent skill, use this reference to write a tight description, structure steps with clear completion criteria, prune no-op instructions, and decide between model-invoked and user-invoked invocation. ## Quick Start Ask the agent to review your draft SKILL.md or AGENTS.md using the writing-for-agents principles and suggest improvements to its description, structure, and wording.

Frequently Asked Questions about writing-for-agents

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

FAQPage Schema
How do I write a good skill description for an AI agent?▼

Front-load the leading word that triggers the skill, list one trigger per distinct branch the document handles, and cut identity the body already carries. Every word of an always-loaded description costs context on every turn, so prune it harder than body text.

What is the difference between model-invoked and user-invoked skills?▼

A model-invoked skill keeps a description so the agent can fire it autonomously, paying permanent context load. A user-invoked skill sets disable-model-invocation: true, removing the description from the agent's reach so only a human typing its name can invoke it.

When should I split a skill into multiple documents?▼

Split by sequence when visible later steps tempt the agent to rush the current step, and split by invocation when a distinct trigger word should fire a skill independently. Splitting spends context or cognitive load, so the cut must earn it.

Why do agents ignore instructions written as negations?▼

Negation drags the forbidden behavior into context and makes it more available, since the strongly-activated concept overruns the weak negation modifier. State the positive target behavior instead so attention lands on what to do.

What is progressive disclosure in agent documentation?▼

Progressive disclosure moves reference material out of the main file and behind a context pointer, loaded only when the pointer fires. Inline what every branch needs and disclose what only some branches reach, keeping the top-level document legible.