jpl_sentry

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description mentions 'data' but doesn't specify whether this is a read-only query, what format the data returns (e.g., JSON, risk tables), whether there are rate limits, authentication requirements, or what happens with the various filtering parameters. For a 10-parameter query tool with no annotation coverage, this is a significant gap in behavioral context.

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 a single, efficient sentence that states the tool's purpose and domain. It's appropriately sized for a data query tool and front-loaded with the key information. There's no wasted verbiage or unnecessary elaboration, though it could potentially benefit from slightly more context about the data format or source.

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 complexity (10 parameters, no annotations, no output schema), the description is insufficiently complete. It doesn't explain what kind of data structure to expect, whether results are paginated, what the default behavior is when no parameters are provided, or how the various filters interact. For a rich query tool with multiple filtering options and no output schema, more contextual information is needed to help an agent use it effectively.

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 100%, so all 10 parameters are documented in the schema itself. The description adds no additional parameter semantics beyond the schema's descriptions (e.g., it doesn't explain what 'Palermo Scale' or 'virtual impactors' mean in context). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to since the schema does the heavy lifting.

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 provides 'NEO Earth impact risk assessment data' which specifies the resource (Near-Earth Object risk data) and domain (JPL Sentry system). It distinguishes from siblings like jpl_cad or jpl_horizons by focusing on impact risk rather than orbital data or ephemerides. However, it doesn't specify the exact verb (e.g., 'retrieve' or 'query') which prevents a perfect score.

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 provides no guidance on when to use this tool versus alternatives. With siblings like jpl_neo, jpl_scout, and nasa_neo that might overlap with NEO data, there's no indication of what makes Sentry unique (e.g., focused on impact risk assessment versus general NEO catalog). No explicit when/when-not statements or alternative tool references are provided.

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