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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds scope (100+ collections), what fields are returned (id, title, description, keywords, geographic extent), and that it's a directory lookup. This adds context beyond the annotations without contradicting them.

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?

Two compact sentences plus an example line. Purpose is front-loaded, the example is illustrative and not redundant, and every sentence earns its place. Zero filler.

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?

For a discovery tool with 2 optional parameters, rich annotations, and no output schema, the description fully covers what the tool does, what it returns, when to use it, and how to use the search parameter. An agent could successfully invoke this tool without further clarification.

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 coverage is 100% for both parameters, with detailed descriptions (e.g., 'case-insensitive substring', default/max for limit). The description enriches this by providing real-world usage examples and clarifying the search semantics ('substring matched against...'). It adds value beyond the schema, though the schema already covers the mechanics.

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's purpose: it is a directory of datasets published by Environment and Climate Change Canada via MSC GeoMet, returning collection metadata. It distinguishes itself from purpose-built tools by explicitly positioning itself as a discovery step, and it's easy to tell apart from siblings like current_observations or hydrometric_realtime which focus on specific datasets.

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 instructs to use it to find datasets and collection IDs before reaching for a purpose-built tool, and provides concrete search examples (hydrometric, cmip5, swob). It implies when not to use it (when you already know the specific dataset), though it doesn't name specific alternative tools. This is clear and actionable.

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