cadc_observations

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

With no annotations, the description carries the whole burden and does well: it discloses no-auth requirement, that unknown object names are resolved via SIMBAD/NED (Sesame) and that it will not guess, and that Japanese names are expanded to English. It omits return format and result ordering, which keeps it from 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 purpose and examples, then a clean Args block. Every line adds information; it is somewhat long but no sentence is wasted, and the examples genuinely clarify usage.

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?

There is no output schema, yet the description never says what a result record contains (observation IDs, instrument, date, data access links), so an agent cannot anticipate the response shape. Everything needed to make the call is present; what comes back is not described.

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 documents all six parameters, including units (degrees), precedence (object_name over ra/dec), the co-usage rule (ra with dec when object_name omitted), defaults (radius 0.5, limit 8, max 20), and telescope examples.

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: search CADC (Canadian Astronomy Data Centre) observation data, with a note that no authentication is required, and three concrete example queries. It is clear what the tool does, though it never differentiates itself from archive-overlapping siblings like mast_observations or eso_seeing.

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 Japanese example queries ('Hubble shots of NGC 300', 'Orion nebula observations', 'Gemini observation list') implicitly convey the intended use cases and query style. There is no explicit when-not or a named alternative, so it stops short of a 5.

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