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

Annotations already cover the safety profile (readOnlyHint, openWorldHint), and the description adds non-obvious behavioral facts beyond them: per-platform metric differences (TikTok views/shares/reach, YouTube views, Bluesky reposts-as-shares) and the X billing rule that makes broad reads costly. It does not describe result volume, ordering or pagination, so it stops short of full disclosure.

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?

Three sentences, front-loaded with scope, then per-platform metric caveats, then the routing/cost rule. The parenthetical metric clauses are dense but each carries information an agent needs; nothing is redundant filler.

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?

With no output schema and sparse annotations, the description does a fair job on platform behavior and cost, but it omits how many posts are returned, what 'recent' means without any time parameter, and what profileId controls. Those gaps matter for an agent trying to predict result size and correct scoping.

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 has to carry parameter meaning. It explains what platform and accountId do and why to supply them, but the third parameter, profileId, is never mentioned, and the platform list in prose omits enum values such as whatsapp, linkedin, meta_ads and tiktok_ads, so the description is incomplete rather than contradictory.

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 and resource ('List recent ... posts with their engagement') and scopes it to named platforms, so the agent knows it is a cross-platform read rather than a single-platform insight call. It does not name the nearest siblings (get_*_insights, list_comments), leaving some differentiation to inference, but the engagement-per-platform breakdown is distinctive.

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?

It gives actionable guidance: X is listed only when a platform or accountId is explicitly supplied because reads are billed, and filtering by platform or accountId keeps the response small. That is a clear use case plus a cost-driven exclusion, though it never states when to prefer get_instagram_insights or other siblings instead.

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