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

Beyond the annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false), the description discloses three useful traits: content is transmitted to an external AI provider, the call consumes the MCP AI quota, and the saved draft is not modified. That is real operational context an agent needs before invoking. It stops short of noting whether results are cached or how quota exhaustion manifests.

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?

Three short sentences, each carrying distinct information (what it returns, what it does externally, what it does not change), with the core purpose front-loaded. Nothing is padded or repeated.

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?

There is no output schema, so the description should characterize the return value; it only gestures at 'editorial issues and suggested replacements' without describing shape, granularity, or how to apply the replacements. It also omits that the required content.body is the review target, leaving the agent to reverse-engineer the nested payload.

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% and the nested content object carries roughly twenty undocumented fields, including the required body. The description only implies that the 'manuscript' is the payload; it explains nothing about plan, language, or which content fields drive the review, so it fails to compensate for the coverage gap.

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 gives a specific verb and resource: it finds editorial issues and suggested replacements in a press release manuscript using the same AI review as Vokolla. That is concrete enough to distinguish it from a status or listing tool, but it never names or contrasts with the closest siblings (check_release, get_editorial_guidelines), so the agent must infer the boundary.

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: 'Does not modify the saved draft' and the quota note suggest this is a non-persisting pre-publish review step. There is no explicit when-to-use or when-not-to-use guidance and no pointer to check_release or get_editorial_guidelines as alternatives for lighter validation.

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