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

Discloses traits annotations cannot: the DataForSEO envelope layout (data in tasks[0].result, outcome in tasks[0].status_code) and the critical gotcha that a rejected request still returns HTTP 200. It also quantifies payload sizes across the three depth modes (4.8 KB / 57 KB / 2.4 MB) so the agent can predict cost and context consumption. This is exactly the kind of behavioral detail the annotations (readOnlyHint=false, destructiveHint=true, idempotentHint=false) do not convey.

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?

Front-loaded with purpose, then the high-value caveats (size disparity, HTTP 200 envelope). The enumerated return-field list is somewhat padded given an output schema exists, but every other sentence carries weight.

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 live SERP query tool with an output schema present, the description covers the things the schema cannot: failure semantics, response envelope, and the depth/size tradeoff. The remaining gap is the input side — nothing explains how to build the required `body` array — which keeps it from being fully complete.

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% for the top-level parameter, and the description does not compensate: the fields it enumerates (keyword, type, se_domain, location_code, language_code, check_url, ...) are described as return values, not inputs. The fact that the request is a required `body` array of task objects, each needing a `keyword`, is left entirely to the schema, so the agent gets no request-shaping help from the prose.

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: 'Returns the advertisers matching a query in Google's ads transparency data on Google, synchronously.' An agent can immediately tell what class of data comes back. It does not differentiate itself from the sibling post_dataforseo_serp_gads_search_live, which is the nearest ambiguous 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?

Gives explicit selection guidance for the depth variants ('advanced is the default choice; take regular when only the ranked list matters and html only to check what the parser dropped'), which is real decision support. It never says when to prefer this tool over the sibling gads_search_live or over a non-live endpoint, so it stops short of full when/when-not coverage.

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