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

Annotations only supply readOnlyHint/openWorldHint, and the description adds substantial non-obvious behavior: all dates are CONVERSION-dated, offline imports count on the event day, a same-day import lowers last_gap_days, and the window ends yesterday with last_gap_days >= 1. That is real interpretive context beyond the safety flags; only request-size/rate-limit style details are absent.

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-loaded with what is measured and what is returned, then the caveats. It is dense but not padded, though the conversion-date explanation is restated twice (date basis and the import/last_gap_days consequence), costing some economy.

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?

With an output schema present, the description needn't explain the return shape, yet it usefully names the key metrics. It covers the crucial semantic traps (conversion-date basis, all_conversions scope, yesterday cutoff) that would otherwise cause misreading; the only real gap is the days parameter's default and bounds.

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 must compensate: it documents the workspace slug including the single-workspace fallback, and 'letzten N Tage' implicitly defines days. However, the days default (30) and valid range are never stated, leaving half the parameters only loosely covered.

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 measurement ('Conversion-Performance pro Aktion der letzten N Tage') plus the returned fields and daily breakdown, and explicitly distinguishes itself from the campaign-level tools by noting it counts all_conversions including secondary actions. An agent can tell what it computes and how it differs from ads_campaign_performance without opening a 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 a concrete use case ('Prüft so, ob Offline-Importe (z.B. HubSpot-Uploads) tatsächlich ankommen') and names the alternative family it is not comparable to (click-dated campaign conversions). It doesn't spell out a when-not-to-use case, but the comparison guidance is explicit.

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