light_pollution_map

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

With no annotations, the description carries the full burden and does most of it: it discloses required inputs, the shape of the response (data.grid points with brightness, Bortle class, SQM, bounds, zoom), and that zoom controls granularity. It does not mention rate limits, cost, or caching behavior for what is presumably a remote data fetch, which keeps it short of a 5.

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?

Front-loaded with the core action, followed by tightly labeled Use/Do not use/Requires/Returns/Follow-up sections that are easy to scan. The only waste is the redundant restatement of the return value later in the description ('Returns a grid of light pollution data points...'), which repeats the earlier 'Returns' line.

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 5-parameter read tool with an output schema, the definition covers purpose, preconditions, response shape, granularity control, and follow-up routing. An agent has everything needed to decide to call it and to invoke it correctly without further inference.

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 largely does: it identifies south/west/north/east as bounding-box coordinates and explains zoom as grid resolution where higher means more detail (the default is already visible in the schema). It does not specify accepted coordinate ranges or zoom bounds, so a small gap remains.

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?

States a specific verb+resource ('Get light pollution data') and immediately narrows scope to a 'bounding-box grid of light pollution measurements'. It also explicitly names siblings it is not (ranked places, complete observing decision), so an agent can separate it from analysis_area and plan_stargazing_session without opening schemas.

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?

Provides explicit 'Use when' and 'Do not use when' conditions, plus a 'Follow-up' line routing to analysis_area, submit_area_analysis, and plan_stargazing_session for the cases this tool does not cover. This is exactly the when/when-not/alternatives structure that earns top marks.

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