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

Annotations cover the safety profile (readOnly, openWorld, non-destructive), and the description adds substantial behavior beyond them: cross-language topic matching, type-word prioritization, ranking with exact matches first and 'match: partial' for weaker hits, a cap of 15 results, and a no-match rephrase message. This is unusually rich disclosure for a search tool.

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 definition is a single dense paragraph but is well front-loaded, opening with what it searches before moving to usage, matching mechanics and return shape. It is on the long side, though nearly every clause carries actionable information.

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?

With no output schema, the description carries the full burden of describing returns and does so: up to 15 matches with code, title, type, language, licence, author, rows, description and page URL, plus the empty-result behavior. An agent has everything needed to call and interpret it.

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%, so the baseline is 3, and the description earns above it by adding usage semantics the schema lacks: write the topic in a few words, English or the content language, and a type word such as 'dataset' or 'prompt' forces that type first. It reinforces rather than merely repeats the schema.

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 gives a specific verb (Search) plus the resource (the ContexteTech catalogue of AI building blocks) and enumerates the content types it covers (datasets, prompts, contexts, MCP servers, models). It differentiates itself from the follow-up sibling load_resource by naming it, but does not distinguish itself from the sibling `search`, leaving one ambiguity.

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?

It states clearly when to reach for it ('Use it first when the user needs AI training or evaluation data, a prompt, a context or an AI component') and what to do next ('then call load_resource with a returned code'). It gives no explicit when-not or guidance for choosing between it and the sibling `search`/`fetch`.

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