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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses a non-obvious result-set behavior: campaigns without any language criterion (= all languages) are omitted entirely, and an empty array under a campaign_id is genuinely ambiguous (all languages OR unknown campaign). That is exactly the kind of trap an agent needs warned about before interpreting output.

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-loads the action, then the filtering caveat, then the ambiguity warning, then the parameter note. Every sentence adds decision-relevant information with no padding.

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?

Output schema exists, so return values need no explanation here; the description instead covers the things structured fields cannot: omission semantics, ambiguity of empty results, and workspace optionality. Nothing needed to call or interpret it correctly is missing.

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 0%, so the description carries the burden: it explains that workspace is a customer-workspace slug and optional when only one workspace exists, and it explains campaign_id's filtering semantics plus the ambiguity of []. It stops short of giving the identifier format for campaign_id.

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+resource ('Sprach-Targeting je Kampagne lesen') with explicit scope (per-campaign, optionally filtered). It is clearly distinguished from the sibling ads_update_language_targeting by the read framing, and from ads_list_campaigns which is named as a different tool for verification.

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 context for when to call it (reading language criteria, optionally per campaign) and names ads_list_campaigns as the cross-check when an empty result is ambiguous. It does not explicitly say when to prefer a different tool (e.g., ads_update_language_targeting for writes), but the usage context is unambiguous.

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