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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds material context the annotations cannot: the tool is free, every metric carries a source report and year plus a plain-language "why", estimates are flagged as estimates and must be disclosed, and `you` is null when the channel isn't connected. The nullability and estimation caveats directly affect how an agent should report results.

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?

The opening sentence is front-loaded and dense with the right information, and each follow-up sentence earns its place (provenance, estimate caveat, null handling, usage trigger). The usage trigger arriving last, plus the irregular line breaks, makes the ordering slightly less scannable than ideal.

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?

An output schema exists, so return values need no explanation; what the description must cover is data reliability and scope, which it does (source/year provenance, estimated percentiles, null `you`, 30-day window, per-platform breakdown). Nothing an agent needs in order to call and correctly report on this tool 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?

Schema coverage is 100% and both parameters document their defaults, so the schema already carries the load. The description only implicitly reinforces the `platform` dimension ("per platform") and explains what the niche is compared against, adding marginal meaning beyond the schema — the expected baseline of 3.

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 verb and resource: comparing this account's last-30-day engagement rate and posting frequency against niche median and top 10%, broken down per platform. That scope is distinct from siblings such as radar_trends or strategy_plan, so an agent can select it 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?

It gives concrete trigger phrases — "how am I doing?" and "what's good for my niche?" — which map cleanly onto user intent. It stops short of naming exclusions or an alternative tool for adjacent questions (e.g. trend discovery vs. benchmarking), so it lands at a solid 4 rather than a 5.

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