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

Annotations already carry safety and idempotency hints, and the description adds the useful rate-limit constraint that annotations do not cover. However, the word 'Read' sits in tension with readOnlyHint=false, and the description never explains what side effect the non-readonly annotation implies (e.g., that the call advances or refreshes research).

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 short sentences, front-loaded with purpose followed by the operational constraint. No filler, no repetition of the tool name.

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 shape need not be described. For a zero-parameter read tool, purpose plus the polling constraint covers what an agent needs to invoke it correctly.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline for a no-parameter tool applies; nothing is missing.

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: reading product facts and onboarding progress for the signed-in account. It distinguishes itself reasonably from siblings like get_product (which returns the product itself) by naming 'real onboarding progress', though the boundary with get_change_status or correct_research is not spelled out.

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?

The description gives a polling cadence ('at most once every 5 seconds'), which is real usage guidance, but it never says when to call this versus get_product or get_change_status, or what condition should trigger a poll. Usage is implied rather than routed.

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