autocomplete

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds the context that the tool suggests completions, which aligns with readOnlyHint. No further behavioral traits (e.g., return format, pagination) are disclosed, but the safety profile is clear.

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 extremely concise: three sentences that state the purpose, the utility case, and an example. No unnecessary words, every sentence earns its place.

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 simple tool with 100% schema coverage and no output schema, the description is adequate but lacks any mention of the return format (e.g., list of strings). This is a minor gap that could help the agent understand the output.

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%, so parameters are already well documented. The description adds value with an example illustrating how kind and query work together, which enhances understanding beyond the schema descriptions alone.

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 it autocompletes names of datasets, organizations, groups, and tags. The example with kind='organization', query='hacienda' shows it resolves partial names to full slugs, distinguishing it from sibling tools like search_datasets or list_organizations.

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?

The description explains it is useful for resolving slugs when the user provides only a partial name, with a concrete example. However, it does not explicitly state when not to use it or mention alternatives among siblings, which is a minor gap.

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