Score draft

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly states the tool is mechanical, makes no external API calls, and explains the conditional nature of the citation provenance and feature-image checks. It does not describe the full output structure, but 'Verdict blocked' hints at the verdict format.

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 three sentences with no filler. It front-loads the core purpose and enumerates checks efficiently, then adds conditional behavior in a compact em-dash clause. Every sentence earns its place.

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?

The tool has no output schema and multiple nested optional parameters, but the description covers the key behavioral aspects: what is scored, when verdicts matter, and what happens when optional inputs are omitted. It lacks explicit thresholds and return-format details, but the guidance is sufficient for an agent to select and invoke the tool correctly.

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 75%, so the schema already documents most parameters. The description adds meaningful context for the two optional parameters: findings enables the citation_provenance check, and feature_image is invisible to the tool unless supplied. This goes beyond the schema's field-level descriptions and helps the agent decide whether to pass them.

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 opens with a specific verb+resource ('Mechanically score a draft') and enumerates the exact scoring dimensions (burstiness, AI-tell phrasing, paragraph uniformity, etc.), making the tool's purpose unmistakable and clearly distinguishing it from sibling tools like create_post or health_check.

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?

The description implies usage context: it is meant for evaluating a draft before publishing, as shown by 'Verdict blocked means fix before publishing.' It also clarifies optional behavior with findings and feature_image. However, it does not explicitly state when not to use this tool or name alternative tools for related tasks.

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