suggest_meeting_point

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the two-phase computation (centroid calculation then venue lookup) and sketches the return payload, but says nothing about permission requirements, behavior when no venues match, location-count limits, or how venue_type matching is performed.

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 purpose is front-loaded in the first sentence, followed by mechanism, then usage context, then parameter and return details. Each block adds distinct information with no filler, and the Args example earns its space by showing the nested structure the 0%-coverage schema omits.

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 two-parameter tool with a rich output schema and no annotations, the description covers purpose, mechanism, usage, and parameter formats adequately. The Returns block partially duplicates the output schema, which is redundant but harmless; the real gap is the absence of any edge-case or failure behavior.

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 0%, so the description must compensate, and it does: it defines 'locations' as a list of lat/lon dictionaries and provides a concrete two-entry example, and it explains 'venue_type' with sample values. It stops short of stating the default ('cafe', visible only in the schema) or any constraints on list size.

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 opening sentence gives a specific verb ('Find') and resource ('optimal meeting place'), and the second sentence clarifies the two-step mechanism (compute a central point, then recommend venues). It implicitly separates itself from single-origin siblings like find_nearby_places or geocode_address by emphasizing multi-person convergence, though no sibling is named explicitly.

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 states clear usage contexts ('planning social gatherings, business meetings, or any situation where multiple people need to converge'), which tells the agent when this tool is appropriate. It does not, however, name an alternative tool or state when not to use this one.

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