Get Best Practices

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context: a proprietary data notice (licensed registry, non-extraction requirement) and a usage limit. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: purpose first, then usage guidelines, then an important notice, then a usage limit. Each sentence adds value, and the total length (~150 words) is appropriate.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 parameters, no output schema, and no nested objects, the description covers usage guidelines, behavioral restrictions, and parameter context sufficiently. The proprietary notice adds necessary completeness for legal/compliance awareness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with descriptions for all 4 parameters. The description adds meaningful context beyond the schema, such as the possible formats for libraryId (from gt_resolve_library, npm:pypi:, or library name) and that topic can be left empty.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches best practices, patterns, and guidelines for a library or framework, targeting specific content types (best-practices pages, guides, migration docs, performance tips) while excluding generic reference docs. It distinguishes from the sibling tool gt_search by specifying when to use each.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises preferring this tool over gt_search when the question centers on one resolvable library, and using gt_search for cross-cutting or non-library topics. Also includes a hard usage limit of 3 calls per question, providing clear when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.