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

Annotations only declare a safe, non-open-world read; the description adds real operational context: API-key or consented-OAuth auth, per-call quota cost, pagination semantics, confirmation that no scraping fires, unresolved redistribution rights, and an explicit prompt-injection warning about untrusted source text. It does not contradict the annotations and materially fills in consequences the agent needs.

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?

It is front-loaded with purpose and most sentences carry signal, but the rights/licensing boilerplate is dense and unstructured, and several clauses could be compressed into a clearer list. The length is defensible for a tool with legal and injection risk, yet the presentation is flat.

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 no output schema and six undocumented parameters, the description does well on safety, cost, auth and return-value character, but leaves include_changes and query semantics undefined. An agent could call it, but not configure it confidently.

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 0%, so the description carries the full burden, and it only partially does: 'twelve dietary labels' maps to needs, and pagination hints map to cursor/limit. query and especially include_changes are never explained, and there is no guidance on limit bounds or slug format.

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 names a specific resource and its contents (saved menu detail, twelve dietary labels, provenance, freshness, explicit unknowns), so an agent knows what it retrieves even though the sentence is a noun phrase rather than a verb. It never distinguishes itself from the overlapping sibling place_vegan_options, which is the main clarity gap.

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?

Operational hints exist (one trial or paid request per call, follow pagination even when filtered pages are empty), but there is no statement of when to choose this over place_vegan_options or place_vegan_options-style siblings. The agent must infer the selection rule from the name alone.

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