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

Annotations already declare readOnlyHint=true and openWorldHint=false, consistent with a static official-rules lookup. The description adds real value by disclosing what comes back — the quoted rule, its source, and a compress-to-size tool reference — which goes beyond the annotations. It stops short of stating behavior for unknown or ambiguous queries, which is the main open question for a fixed-dataset lookup.

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?

Two sentences, front-loaded with the purpose and followed by the return content; every phrase carries information. The example list is slightly long and packed into a parenthetical, mildly hurting scanability, but nothing is dead weight.

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 one-parameter read-only lookup with no output schema, the description covers purpose, input shape, and return contents, which is enough to call it correctly. The remaining gap is edge-case behavior (no matching platform, unofficial limits), minor for this tool's complexity.

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 100% and the parameter's schema text already gives the same shape of example ('Gmail attachment', 'UPSC photo', 'Etsy listing photo'). The description's example list adds a bit of breadth (visa photo, avatar) but no new semantics such as required specificity or fallback behavior for unmatched queries, so the baseline of 3 applies.

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 and resource ('looks up official file-size and dimension limits for photo/document uploads') and grounds it with concrete query examples (Gmail attachment, SSC photo, Discord avatar, US visa photo). It does not, however, explicitly distinguish itself from the similarly-scoped sibling get_platform_image_size, leaving the agent to infer the boundary between 'upload limit lookup' and 'platform image size'.

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 shown by example rather than stated as a rule: the agent can infer it should call this when a user asks about an upload constraint for a named service. There is no explicit when-not guidance and no named alternative (e.g. 'for format recommendations use recommend_image_format'), even though several siblings overlap conceptually.

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