search_flet_source

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful behavioral detail: scope is every .py file in the package, matching is case-insensitive, and results are ranked by type. This goes beyond the structured annotations and helps the agent predict behavior.

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 compact and front-loaded: the scope and ranking appear first, followed by use cases, then parameter details. Every sentence adds value, and there is no filler or repetition.

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 an output schema and only two parameters, the description covers everything an agent needs to select and call it correctly: the search scope, ranking rules, parameter semantics, and intended use. No critical information is missing.

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?

The schema has 0% description coverage, so the description fully carries parameter meaning. It explains the query is a case-insensitive substring with concrete examples, and it clarifies max_results as the maximum match count with default 25. This is strong compensation for the empty schema descriptions.

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 states a specific verb and resource: search the installed flet source code across every .py file. It also defines the ranking (definitions first, then assignments, comments) and names the intended use (find where things are defined, which modules exist, or how a feature is implemented), clearly distinguishing it from docs/examples/icon searches.

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 clearly says when to use this tool: to find definitions, modules, or actual implementation details in the current version. It does not explicitly list when-not-to-use or name alternative sibling tools, but the context is sufficiently clear to route an agent appropriately.

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