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

Annotations already declare read-only, non-destructive, and non-open-world behavior. The description adds useful context beyond that: it excludes patterns already recorded with meta.research and products removed via research_skip, and states the study is free and reports current run status.

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 definition is a single dense paragraph with nested parentheses and jargon such as 'same_job', 'meta.research', and 'the move it becomes'. It front-loads the resource but then becomes difficult to parse; restructuring into shorter sentences or bullets would preserve the content with far less cognitive load.

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?

For a complex research tool with no output schema and zero parameters, the description does cover substantial return content: peer lenses, public evidence, early history, patterns, exclusions, run status, and pricing. Still, it does not clarify the shape or ordering of the returned study, leaving an agent unsure how to consume the result.

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 has zero input parameters, so the baseline is 4. References to peers[].lens, founder, meta.research, and research_skip are stored-data fields rather than call parameters, so no additional parameter semantics are required.

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 identifies a specific resource: the latest peer study of up to 8 products, scoped by lenses and pattern types. However, the core action is implied rather than stated with a clear verb, and the dense noun-heavy phrasing makes it harder to distinguish from siblings such as research_run.

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?

There is no explicit instruction on when to call this tool versus research_run or research_skip. The note that it reports whether a study is running, when the next free one is, and its price hints at pre-run checks, but the agent must infer the decision rule.

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