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

Annotations already mark this read-only and non-destructive, so the description does not need to restate safety. It adds meaningful behavioral context beyond annotations: search is non-billable, returns full JSON schemas ready for use, supports distinct query forms, and uses a ranked match for free-text queries. No contradiction 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 key guidance is front-loaded, with the prefer-this directive and purpose in the first few words. The rest is organized compactly: when-to-use, query forms with concurrent examples, and bundle names. Every sentence adds value and there is little redundant 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?

Given the low complexity of the tool (two parameters, one required, 100% schema coverage) and simple input schema, the description covers everything needed to invoke it correctly: query formats, behavior of max_results, what to do about skill bundle names, and expected output nature. The lack of an output schema is mitigated by explicitly revealing that it returns full JSON schemas for matched tools.

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%, but the description goes further by giving concrete query form syntax including 'skill:<name>', 'select:name1,name2', and real free-text examples like 'cancel run' or 'trigger url'. It also clarifies the relationship between query forms and max_results, noting it is ignored for select and skill forms.

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 opens with 'PREFER THIS...' and clearly identifies the resource being searched ('Flow Studio MCP tools'), the action ('Searches by keyword, skill bundle, or explicit selector'), and the deliverable ('returns full JSON schemas for matched tools'). It explicitly differentiates itself from the other tools on the server by framing itself as the meta-search tool for choosing among them.

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 gives explicit when-to-use guidance: whenever you are not 100% sure how to map a user request to functionality, and when loading a whole skill bundle. It also names the three supported query forms with examples and directs users to use list_skills first for bundles, making alternative and prerequisite behavior clear.

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