get_telescope_targets

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a ranked list with suitability scores and describes the output structure. However, it does not mention any side effects, authentication needs, rate limits, or limitations (e.g., dependency on input accuracy). The behavioral transparency is good but not exhaustive.

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 well-structured with a clear purpose, then 'Args' and 'Returns' sections. It is somewhat lengthy due to the detailed parameter list, but every sentence adds value. The front-loading of the purpose sentence is good. Minor redundancy could be trimmed, but overall it is appropriately sized for a complex tool.

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 (15 parameters, no schema descriptions, no annotations, but with an output schema), the description is remarkably complete. It explains all parameters, the return value structure with key fields (suitability_score, fov_fit_score, etc.), and assumes the output schema covers additional details. It lacks error handling guidance but meets the bar for a recommendation tool.

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 input schema has 0% description coverage, but the description provides detailed, clear explanations for every parameter, including examples (e.g., 'focal_length_mm: Telescope focal length in mm (e.g. 250 for RedCat51)') and context. This adds significant meaning beyond the schema's type/default information, fully compensating for the lack of schema descriptions.

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 purpose: 'Recommend astrophotography targets for a telescope setup.' It uses a specific verb ('Recommend') and specifies the resource ('astrophotography targets for a telescope setup'). Among sibling tools like 'get_best_stargazing_plan' and 'get_shooting_plan', this tool's focus on telescope-specific recommendations distinguishes it well.

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 usage context (when you have a telescope setup and want target recommendations) but does not provide explicit guidance on when to use this tool versus siblings like 'get_best_stargazing_plan' or 'get_shooting_plan'. No exclusions or alternatives are mentioned, which leaves some ambiguity for an AI agent.

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