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LLM & Agentic

Agent Skills

Package know-how as Agent Skills: the SKILL.md format, progressive disclosure, writing a description that triggers, attaching Anthropic and custom skills to API requests, and auditing a skill before you trust it.

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After this section you can

  • Write a SKILL.md whose description fires on the right requests, and test it
  • Explain what progressive disclosure keeps out of context, and what it costs when a skill fires
  • Attach Anthropic and custom skills to an API request, and audit a skill before trusting it
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Agent Skills: Expertise That Loads on Demand

A skill is a folder of instructions, scripts and reference files. Claude sees one line about it until a request needs it, then reads the rest from disk. That is how an agent carries dozens of procedures without paying for them on every call.

Key idea

A skill moves know-how out of the system prompt and onto a filesystem. Only its name and description sit in context. When a request matches the description, Claude reads SKILL.md, then opens further files or runs scripts only if the task needs them. The description is the trigger, so it decides whether the skill is ever used.

Three levels: what is in context before, during and after a skill fires
WHAT ONE SKILL COSTS IN CONTEXT 1 · Name + description always loaded, at startup ~100 tokens per skill matched against every request 2 · SKILL.md body read with bash when it matches ~5,000 tokens or less, then it stays the procedure itself 3 · Files and scripts opened only if the task needs them 0 until used a script’s output, never its code Install thirty skills and only thirty descriptions are in every request; one body arrives when one is needed. Figures are the docs’ approximations (Agent Skills overview, read 2026-10-27).

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