writing-for-agents

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

10|3|Updated Aug 10, 2026
One-click install
npx skills add https://github.com/baiqigo/baiqi-redteam-lab --skill writing-for-agents-baiqigo
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: writing-for-agents
Source: https://github.com/baiqigo/baiqi-redteam-lab/tree/main/.agents/skills/writing-for-agents
Command: npx skills add https://github.com/baiqigo/baiqi-redteam-lab --skill writing-for-agents-baiqigo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Documents written for AI agents often trigger unreliably, bury key steps, or bloat the context window. This Skill provides a reference framework for writing any agent-consumed document so the agent follows the same process every run. ## Core Features & Use Cases - Context pointer design: Write descriptions and pointer lines with front-loaded trigger words and one trigger per branch so agents reach material reliably. - Information hierarchy: Apply progressive disclosure, co-location, and splitting rules to keep documents legible and steps visible. - Completion criteria and pruning: Define checkable, exhaustive step completion criteria and remove duplication, no-ops, and stale content. - Use Case: When creating a new skill or editing an AGENTS.md file, use this Skill to decide what stays inline, what moves behind a pointer, and how to word the description for reliable invocation. ## Quick Start Ask the agent to review your draft skill or AGENTS.md file using the writing-for-agents guidelines and suggest improvements to its description and structure.

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 skill description that agents trigger reliably?

Front-load the leading trigger word, list one trigger per distinct branch the document handles, and cut identity the body already carries. The description's wording, not its target, decides when the agent reaches the material.

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

A model-invoked skill keeps a description so the agent and other skills can fire it autonomously, at the cost of permanent context load. A user-invoked skill sets disable-model-invocation: true, so only a human typing its name can reach it.

When should I split a skill into multiple documents?

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

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 legible.

Why should I avoid negative instructions in prompts for agents?

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