top_terms

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context about tokenization via jieba/fugashi/pythainlp, a script-aware fallback, and merging terms across spellings, but it does not disclose auth requirements, rate limits, or data freshness handling.

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 first sentence front-loads the tool's purpose, and the follow-up sentence gives relevant language-processing context in a compact form. The pip-install detail is somewhat implementation-oriented but still brief and not excessively verbose.

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?

With 9 parameters at 0% schema coverage, the description omits nearly all parameter semantics, leaving an agent unable to know what top, days, source, or query_filter control. An output schema exists, so return values need not be explained, but the input side is substantially incomplete for a moderately complex tool.

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 0% across 9 parameters, and the description does not mention any parameter names, meanings, formats, or defaults. For a tool with top, days, source, dates, max_rows, search_type, query_filter, and site_url, the description provides no compensating semantic detail.

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 identifies the tool's output as 'most demanded words across all queries,' which is a clear resource and scope, and the name top_terms reinforces it. It distinguishes itself from generic search analytics tools by noting language support for Chinese/Japanese/Thai, but it does not explicitly state a verb like 'extract' or 'list' or name a sibling alternative.

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 gives no explicit guidance on when to use top_terms versus siblings like query_search_analytics or query_variants. The language-support notes imply it is useful for non-space-delimited languages, but that is not framed as a usage condition or alternative selection rule.

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