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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety and repeatability are covered structurally. The description's added value is limited to saying results are ranked and include snippets, which the output schema likely already conveys; it says nothing about result caps, ranking behavior, or what happens when nothing matches.

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 sentences, no filler, and the scope statement is front-loaded before the usage trigger. Every clause earns its place by naming either a source or a question type the tool handles.

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 single-query search tool with an output schema and fully documented parameters, the description supplies what structured fields cannot: the corpus being searched and the class of questions it answers. A note that results are capped at 10 with no pagination (so the agent should refine the query rather than page) would close the remaining gap.

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% and every parameter (query, section, limit) carries its own description with defaults and bounds, so the schema does the heavy lifting. The description's parenthetical listing of the handbook, droplet pages, DroppyKit docs and blog loosely glosses the section enum values but adds no new constraint or syntax guidance.

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?

States a specific verb and resource ('Search everything on getdroppy.app') and enumerates the four content sources covered, plus what comes back ('ranked pages with a snippet'). It does not name or contrast with fetch_droppy_page or list_droplets, so the agent must infer the difference from 'everything' vs. a single page/list, but the core purpose is unmistakable.

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?

Gives a clear use condition: 'any question about how Droppy works, its settings, shortcuts, permissions, pricing or problems,' which is a concrete and broad trigger set. It stops short of an explicit exclusion or a named alternative ('for a specific known URL, use fetch_droppy_page instead'), which keeps it out of the top band.

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