test-backend-router

What problem does it solve?

This skill addresses the challenge of high token usage in AI agents by demonstrating a "thin router" pattern. It proves that documentation can be loaded on-demand, significantly reducing context window size and processing costs compared to automatically injecting full documentation.

Core Features & Use Cases

• Thin Router Pattern: Provides a proof-of-concept for routing tasks to either the skill itself (for simple, focused tasks) or a full agent (for complex, multi-step work), optimizing resource allocation.
• On-Demand Documentation: Utilizes doc-lookup to retrieve only the necessary documentation sections for CLI commands, FastAPI server, database, and MCP integration, avoiding large context windows and irrelevant information.
• Token Efficiency Analysis: Explicitly highlights the substantial token savings (up to 90% reduction) achieved by using this progressive disclosure model compared to traditional automatic documentation injection.
• Use Case: If you need to understand "what columns are in the executions table," this skill demonstrates how to use doc-lookup to retrieve just that specific database schema section, rather than loading the entire backend documentation, saving tokens and processing time.

Quick Start

Example: Understanding CLI Flags

User request: "How do I add a --json flag to dipeo run?"

Router workflow:

1. Assess: Simple task, need CLI context

2. Load doc-lookup for CLI commands section:

python .claude/skills/doc-lookup/scripts/section_search.py
--query "cli-commands"
--paths docs/agents/backend-development.md
--top 1