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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful facts: it searches only published content, covers blogs and guides, and returns titles, summaries, and URLs. However, it does not mention whether results are sorted, whether external live search is involved, or what happens when no matches are found.

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 verb, object, and content scope appear in the first sentence, followed by concrete use cases and return shape. Every sentence earns its place; there is no 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?

For a simple search tool with three well-documented parameters and no output schema, the description covers the essential caller needs: what is searched, which topics are relevant, and what the result contains. It could improve by noting sorting or empty-result behavior, but nothing critical is missing for correct invocation.

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%, with each parameter already documented with examples and defaults. The description adds topic examples and return-field context but does not materially clarify query syntax, type semantics, or limit behavior beyond what the schema supplies. Baseline 3 is appropriate.

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 ('Search'), a clear resource ('KYMA369 educational content'), and the exact content types covered (published blog posts and healing condition guides). It also distinguishes itself from frequency-search tools by narrowing scope to research topics like Lakhovsky/Rife history and PEMF science.

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 provides explicit use cases ('Use for research, Lakhovsky/Rife history, PEMF science, or a wellness topic') that help an agent decide when to call it. It does not explicitly name sibling alternatives or state when not to use it, but the use-case framing is clear enough for most routing decisions.

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