On-Demand Skill Files

Pattern for keeping service-specific CLI/API guidance out of the always-loaded project context until the agent actually needs that service.

Key points

  • A skill file can teach an agent exact commands, flags, and output formats without requiring a full MCP server [src-041].
  • In the article's GitHub CLI experiment, the skill costs about 480 tokens when loaded and steers the agent toward structured --json output [src-041].
  • The efficiency depends on invocation timing: on-demand skill loading costs once when needed, while putting the same guidance in CLAUDE.md or .cursorrules makes it an always-on context cost [src-041].
  • On-demand skill files are strongest for low-frequency services that need reliable structured output, such as GitHub, Kubernetes, cloud CLIs, Stripe, or DNS tooling [src-041].
  • This complements Progressive Context Loading: a project can carry many skills as long as the full instructions are loaded only when selected.

Related entities

Related concepts

Source references

  • [src-041] Marco Mornati — "The Future of Agentic Tooling: MCP Servers vs. CLI A Data-Driven Comparison" (2026-04-27)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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