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

Given readOnlyHint=true is annotated, the description correctly implies a read-only operation (calculating scores) without contradiction. It adds the scoring criteria breakdown, which provides behavioral insight into how the score is computed, exceeding what annotations provide. However, it doesn't disclose details like rate limits or data scope beyond the description.

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 well-structured: a clear purpose statement, a scoring criteria list, and the Args section are all front-loaded and easy to parse. Every sentence adds value—no filler or redundancy. The format is scannable for an agent.

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?

Given the tool has an output schema, the description need not explain return values, but it does summarize the return as 'JSON with scores, distribution, top/bottom performers, and recommendations,' which adds context. With readOnlyHint annotation, no safety disclosure needed. The description covers the scoring logic and key parameters, making it complete enough for an agent to use the tool effectively, though it doesn't fully describe pagination context.

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%, so the description must explain parameters. It does explain section_id and max_items in Args, but page and page_size are only in the schema without added meaning. The description adds semantic context for two of four parameters, partially compensating for the schema 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 clearly states the tool computes a 0-100 AI Discoverability Score for videos, measures how well content is discoverable by AI systems, and lists specific criteria. It distinguishes itself from siblings like audit_metadata_quality and get_series_seo_map by focusing on AI discoverability scoring with a clear numeric output.

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 its use for evaluating content discoverability by AI, but does not explicitly state when to use it versus alternatives like audit_metadata_quality or get_series_seo_map. It's clear it's a scoring tool, but no explicit 'use when' or 'not for' guidance is given.

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