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

Annotations already establish a safe read-only, non-open-world profile, and the description adds real value on top: results carry a 'door' (analysis), a `notes` field explains what was not understood, the `like` anchor is echoed back, and several parameters are gated on subscriber sign-in. It does not discuss pagination depth or result size limits beyond what the schema states.

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?

Four sentences that are front-loaded with the capability and then the operational caveats; every sentence carries information. Some phrasing is idiosyncratic ('each result carries its door'), which slightly costs first-read clarity but is not wasted text.

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 20-parameter tool with nested axis/irritant objects and an output schema, the description covers the non-obvious operational needs: empty-result recovery via `notes`, auth-gated options, and conversational presentation. Combined with 95% schema coverage and an output schema, an agent has what it needs to call this 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 coverage is already 95%, so baseline is 3, but the description adds cross-parameter semantics the schema cannot express: `like` is incompatible with `text`, `exclude`, and `profile`, results are similarity-ordered unless `sort` overrides, and other filters narrow the similar set. That is genuine meaning beyond the field-level docs.

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 ('Films and series by ...') plus the full breadth of filterable dimensions (genre, country, years, age rating, score, tags, axes, irritants, similarity to one title). An agent can distinguish this filtered-discovery tool from lookup-style siblings like find_title or profile_titles without opening the 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 concrete operating guidance: read `notes` first, loosen filters after an empty answer, and in voice conversations offer two or three titles with reasons. It also flags that personal options require sign-in. It stops short of explicitly routing away from find_title or profile_titles, so no exclusion rule is stated.

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