research_market

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

With no annotations, the description carries full responsibility for disclosing behavioral traits. It fails to state whether this is a read-only operation, if there are side effects, rate limits, or any costs. It only describes the action without revealing operational characteristics.

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 description is concise: a one-sentence purpose statement followed by a brief args block. Every sentence adds value, and the purpose is front-loaded with no filler.

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?

The tool has no output schema and no annotations, yet the description does not describe what the aggregated research returns or any side effects. Given that this tool orchestrates research across all data sources, the lack of output or outcome information is a significant gap.

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 schema has 0% description coverage, so the description must compensate. It fully explains the sole parameter 'niche' by defining it as 'The niche or keyword to research' and providing an example ('notion templates for students'). This is clear and sufficient for the single parameter.

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 verb 'run' plus the resource 'full aggregated market research' with scope 'for a niche across all data sources' clearly articulates the tool's function. It distinguishes itself from sibling tools like find_trending_niches or analyze_competition, which are more focused.

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 implies this is the go-to for comprehensive research through 'full aggregated market research', but it never explicitly states when to use it over alternatives or when not to use it. No exclusions or comparisons are provided, leaving usage guidance at the implied level.

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