google_ads_negative_placements_remove

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

With no annotations provided, the description fully carries the burden of disclosing behavior. It explicitly states that the operation is mutating ('lifting an exclusion lets the placement serve again'), describes the safety verification ('Ids are verified against the live criteria first'), and clarifies that invalid IDs are skipped, never removed. It also documents the return structure (removed, removed_count, skipped entries with reasons).

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 well-structured and front-loaded with the primary action. Every sentence contributes unique value: purpose, return values, mutating effect, safety verification, and ID source. It is concise enough despite being longer than one sentence, with no fluff or repetition.

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?

The description is complete given the moderate complexity and lack of an output schema. It covers the operation's purpose, the exact return data, the mutation warning, the validation/skip behavior, and how to obtain valid IDs. It provides enough context for an agent to invoke the tool correctly and interpret results.

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?

The schema provides 100% coverage with detailed descriptions for all four parameters, including the relationship between campaign_id and ad_group_id and the source of criterion_ids. The description adds almost no new parameter-level semantics beyond what the schema already states; it reinforces the batch/verification behavior but that is more about tool behavior than parameter meaning.

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 clearly identifies the action ('Lifts delivery-surface exclusions by criterion_id, in one batch'), the resource (negative placements), and the specific use case ('a bad exclusion pass can be reverted in a single call'). It distinguishes itself from sibling tools like google_ads_negative_placements_add and google_ads_negative_placements_list by focusing on removal/reversion.

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 clear context for when to use the tool (reverting exclusions, batch removal) and directs users to google_ads_negative_placements_list for obtaining IDs. However, it does not explicitly mention alternative tools or when not to use this tool, such as distinguishing from negative keyword removal tools, though the name and scope make the intended use fairly obvious.

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