compare_viewpoints

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

With no annotations provided, the description carries the full burden of behavioral disclosure. The description only names the scoring dimensions but doesn't explain the weighting/composition of scores, how the ranking output is structured, whether it mutates state, or how scores are derived/combined. For a ranking tool with no output schema and no annotations, this is a significant transparency gap.

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?

A single clear sentence that front-loads the verb and purpose. No wasted words. It efficiently conveys what the tool does and its scoring criteria. Could arguably add a bit more, but the conciseness is appropriate.

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?

This is a moderately complex aggregator tool with no output schema and no annotations. The description does not clarify what the ranking output looks like, how scores are combined/weighted, nor which fields are required vs optional inputs. Given the tool takes an array of candidate objects with multiple optional scoring fields, the description is under-specified for an agent to use it reliably.

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%, but there are individual properties with rich min/max constraints in the schema itself (Bortle class 1-9, scores 0-10). The description names the four scoring dimensions, which helps map concept to fields, but doesn't clarify that candidates need pre-computed accessScore/horizonScore/foregroundScore values (as opposed to the tool computing them). With only one parameter being an array with a fairly self-documenting nested schema, the description adds nominal value.

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 verb 'Rank' and the resource 'candidate viewpoints', and lists the four scoring dimensions (darkness, horizon, access, foreground). It distinguishes this from siblings like assess_dark_sky (which evaluates darkness alone) by implying a comparative ranking of multiple candidates. Directly distinguishing from specific siblings isn't done but the multi-candidate ranking purpose is clear.

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?

No guidance is given on when to use this tool versus alternatives. It doesn't explain when one would want viewpoint ranking vs. the other planning tools, nor mention prerequisites like needing access/horizon scores already computed and provided per candidate. Usage context is entirely implied by the description.

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