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

Annotations already disclose readOnlyHint=false, openWorldHint=true, idempotentHint=false and destructiveHint=false. The description adds genuinely useful non-obvious context beyond that: the 30-day analysis window and, critically, that each call counts against the monthly AI allowance. The phrase 'Changes nothing' reads as 'no content mutation' and is reconciled by the quota-cost disclosure, so it is not a contradiction of readOnlyHint=false. It does not describe return format or rate-limit behavior, hence a 4.

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 tightly written sentences: the first front-loads what it analyses and returns, the second delivers the key behavioral caveat. No filler or redundancy.

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, the description helpfully enumerates the returned insight types, states the analysis window, and flags the AI-allowance cost. It is nearly complete for a single-parameter analysis tool; only explicit differentiation from sibling analytics tools is missing.

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?

There is a single optional platform parameter whose enum and 'Omit for all platforms' semantics are fully documented in the schema (100% coverage). The description adds no parameter detail, so the schema carries the burden and 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 (Analyse), resource (last 30 days of post metrics) and enumerates concrete outputs (best time of day, best tone, top hashtags, prompt suggestions, per-platform insights). It is clearly distinguishable from generic siblings like get_stats or get_analytics_trends by its optimization framing, though it never names those siblings explicitly.

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 implied by the output list (you call it to learn optimal posting time/tone/hashtags), and the closing clause warns that each call consumes the monthly AI allowance, which nudges the agent to call sparingly. However, there is no explicit when-to-use vs alternatives guidance and no stated conditions for choosing this over get_analytics_trends or get_growth_overview.

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