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

Annotations declare readOnly=false and destructive=false, so the write nature is known. The description adds meaningful context beyond them: it previews by default and only mutates when confirm is true, which is exactly the safety behavior an agent must understand before calling a mutation tool.

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, front-loaded with the purpose and ending on the critical preview/confirm rule. The middle value-proposition sentence is slightly motivational but earns its place by steering usage, so no material waste.

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 output schema, the description covers the essential calling semantics (what it changes, the preview-by-default contract). It is only incomplete on parameter detail, which the schema largely omits.

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 only 20%, so the description must compensate, but it only reinforces the confirm flag (already documented in the schema) and says nothing about keywords (max 100), match_type (enum with default PHRASE), campaign_id, or customer_id. The low-coverage parameters are left undocumented in both places.

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 (add), resource (negative keywords) and target (Google Ads campaign), and the goal ('stop wasted spend'). Clearly distinguishes from siblings ads_add_keywords and ads_remove_negative_keywords without opening either schema.

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 clear usage context - 'highest-value change available after reading a search terms report' - which tells the agent when to reach for it. It does not explicitly name the removal sibling as the alternative operation, so no exclusions are stated, but the guidance is strong.

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