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

Annotations already declare readOnly/idempotent/non-destructive/no-open-world, so the safety profile is covered. The description still earns credit by adding two genuinely non-obvious traits: 'Coverage is a model, not a rank prediction' (sets expectations on output trust) and 'Stores nothing' (confirms no side effects or persistence). It does not mention rate limits, auth, or what the response shape looks like.

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 the verb and resource, and every clause names a distinct check rather than padding. It is a single dense run-on sentence with a long enumeration, which costs some readability, but nothing is redundant with the schema or annotations.

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 7-parameter modeling tool with no output schema, the description carries the necessary burden: it enumerates what gets computed, clarifies the covered/uncovered keyword logic and the coverage score, and flags the model-vs-rank caveat. The main remaining gap is that, with no output schema, the actual response shape is only inferable from the check list.

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 100%, so every parameter already carries limits and semantics (30-char title, 100-char comma-separated keyword field, 4000-char description, up to 50 candidates). The description reinforces the role of candidates ('which tracked or candidate keywords become covered or uncovered') and notes Google Play indexes the description, but adds little syntax or format detail beyond the schema. Baseline 3 is appropriate.

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 ('check...and simulate') against a specific resource ('proposed listing copy for a tracked application') and enumerates the exact checks performed (character counters, duplicate words, competitor brands, Google Play density, keyword coverage). An agent knows precisely what this does. It stops short of naming the near-identical siblings check_listing_metadata or compare_metadata_draft, so the boundary between them is not spelled out.

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 is implied rather than stated: 'Check proposed listing copy' plus 'Stores nothing' signals a dry-run/validation use case, which implicitly contrasts with save_metadata_draft. But there is no explicit when-to-use, when-not-to-use, or named alternative — the agent must infer the split with check_listing_metadata and compare_metadata_draft on its own.

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