merch_roundtable

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

With no annotations provided, the description carries the full behavioral disclosure. It explains the multi-step process (independent evaluation, debate, synthesis) and the 'EXPERIMENTAL' status. It also discloses the caching behavior with scrape_page. This provides substantial insight beyond a simple 'analyzes the page' statement, though it does not explicitly state side-effect-free behavior or referential details like timeout or rate limits.

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 a well-structured paragraph with front-loaded purpose, followed by persona details, process, and caching behavior. Each sentence adds informative value, though it is slightly longer than necessary. For a complex tool, this level of detail is justified, and it remains concise overall.

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?

Given the tool's complexity, the description covers the key contextual elements: personas, process, output (prioritized recommendations with endorsements), and cache reuse. There is no output schema, so the description's mention of the output format partially compensates. Missing details about edge cases (e.g., invalid URL) or auth are not critical for an experimental analysis tool. It is reasonably complete.

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 description coverage is 100% for all three parameters, so the baseline is 3. The description adds no additional meaning beyond the schema; it does not elaborate on how 'depth' or 'max_products' affect the analysis, nor does it clarify the 'url' parameter beyond its schema definition. The description relies on the schema for parameter semantics.

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 clearly states the tool's specific verb and resource: 'Run a multi-perspective merchandising analysis' with three named personas. It distinguishes from siblings by describing the unique multi-persona debate and consensus process, and the output of prioritized recommendations. This is a specific, non-tautological purpose.

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 provides clear context for when to use the tool: for a multi-perspective merchandising analysis. It also hints at the relationship with scrape_page by mentioning cache reuse. However, it does not explicitly contrast with sibling tools like ask_page or compare_storefronts, nor does it state when not to use it. Clear context but no exclusions.

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