set_conversion_action_primary_status

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

With no annotations, the description must carry the full behavioral burden. It explains the effect of the boolean: associate = campaign optimizes to the goal; disassociate = falls back to account-level goals. It also states 'Live-verified 2026-07-30, both directions,' indicating reliability. However, it does not disclose whether the operation is immediate or a draft requiring confirmation (suggested by the word 'Draft' but not elaborated), nor does it mention idempotency, side effects on existing associations, or permission requirements.

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 very concise, at two substantive sentences plus a verification note. It front-loads the core purpose and then explains the semantics clearly. There is no fluff or redundant information. The only minor issue is the word 'Draft' which might cause confusion but is followed by clarification. Overall, it is efficient and well-structured.

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 no output schema, the description should cover operational details. It explains the core behavioral effect and the association model, which is the most important part. However, it lacks information about the draft/confirmation nature (there is a sibling 'confirm_and_apply'), potential error conditions, and return values. Given the moderate complexity (3 params, no nesting), the description provides adequate but not comprehensive context, leaving gaps around execution flow.

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%, so the description must compensate. It explains the primary boolean parameter semantically (associate/disassociate) and implies the roles of campaign_id and goal_id through the phrase 'campaign-goal association.' However, it doesn't explicitly define each parameter's type or format, and the explanation is primarily targeted at the primary flag. While this adds meaning beyond the bare schema, it leaves campaign_id and goal_id to be inferred from 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 states the tool's purpose: setting the primary status of a conversion action for a campaign, modeled as a campaign-goal association. It explains the semantics (associate/disassociate) which distinguishes it from siblings like create_conversion_action. However, the opening phrase 'Draft a campaign-goal association' is slightly ambiguous because it could be interpreted as creating a new association rather than updating an existing one, and it doesn't explicitly name the tool's action (set primary status).

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: to make a conversion action primary for a campaign, use this tool. The description explains the meaning of 'primary' but does not explicitly state when to use this tool vs alternatives, such as update_campaign or create_conversion_action. There are no exclusions or conditions, and no mention of prerequisites or confirmation steps, relying on the agent to infer timing.

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