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

With annotations already declaring a non-destructive, open-world, write-style async operation, the description adds substantial behavioral detail: runs in the background for a few minutes, costs 12 credits charged only on return, free when fewer than 2 products can be read, weekly free tier for Builder/Growth, and one paid study per day. These are exactly the traits an agent needs before invoking a costly async job.

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 whole definition is a single dense run-on paragraph that packs purpose, cost, gating, and parameter semantics into one block, which hurts scanability. Most sentences carry real information, but pricing and tier rules could be broken out or tightened.

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?

There is no output schema, but the description tells the agent to call research afterwards for results, and it covers async timing, cost, gating, and the sole parameter's persistence. That is nearly complete for an agent deciding and calling the tool; only the exact return shape is left implicit, which is acceptable given the explicit retrieval step.

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%, so the baseline is 3; the description earns extra by explaining that domains are studied first and persist into every later study, with at most 5 kept newest-last, adding persistence and ordering semantics the schema does not convey. It also clarifies to leave it out when none were named.

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 uses specific verbs and resources — find up to 8 products a step ahead, read what each shows publicly and how it started, read this site, and surface learnings with evidence and a first step. An agent can tell this is the 'deep peer study' tool. It doesn't name sibling alternatives (e.g. research_skip) explicitly, though 'call research afterwards' implicitly distinguishes the retrieval step.

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?

Explicit prerequisites and constraints: 'Needs a finished AI visibility check', 'call research afterwards', 'At most one paid study a day', and 'State the price before a paid one.' This gives clear when-to-call and gating context. It lacks an explicit statement of when NOT to use it versus siblings like research_skip.

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