add_keywords

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, and it delivers the key safety trait: 'Dry run unless confirm=true.' This makes the default non-destructive behavior explicit, which is critical for a mutation tool. Less-critical details like permission requirements or duplicate handling are omitted, but the most important behavior is disclosed.

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?

Three short sentences, each earning its place: purpose first, then the keyword payload format, then the safety warning. There is zero filler, and the most important information is front-loaded.

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 mutation tool with no annotations and 0% schema coverage, the description covers the essential ground: what it does, the keyword payload format, and the dry-run safety valve. Return values are handled by the output schema, and the remaining parameters are self-evident from their names, leaving only minor gaps such as batch limits or deduplication behavior.

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%, and the description compensates for the most complex parameter by showing the keyword payload shape, including the required text field and the match_type enum values ('PHRASE|EXACT|BROAD'). It also clarifies the effect of confirm, though customer_id, ad_group_id, and status are left to inference from their names.

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 uses a specific verb+resource: 'Add positive keywords to an ad group.' The word 'positive' clearly distinguishes this tool from its sibling add_negative_keywords, so an agent can tell them apart without inspecting schemas.

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?

Usage context is implied by the phrasing 'positive keywords' — an agent can infer when to choose this over add_negative_keywords — but there is no explicit statement of when to use it versus alternatives, nor any exclusions or prerequisites. The guidance is present only by implication, not stated.

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