AgentNASA — NASA Space Intelligence

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

With no annotations, the description carries the full burden. It does disclose the return shape ('image/video with title, explanation, and URLs'), which matters since there is no output schema, but it says nothing about auth requirements, NASA rate limits, or error behavior for out-of-range dates.

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?

Two tight sentences, purpose first, return shape second. No filler and nothing redundant with the schema.

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 simple, no-required-param read tool with 100% schema coverage, the description covers purpose and output content adequately. Only the operational context (rate limits, failure modes) is absent.

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 three parameters (date, count, thumbs) are self-documenting. The description adds no parameter-level meaning beyond the schema, so the baseline 3 applies.

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 and resource ('Get NASA Astronomy Picture of the Day') plus the payload returned. The resource is unique among siblings (near-earth objects, space weather), so differentiation is implicit rather than stated.

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 when-to-use guidance, no exclusions, and no mention of alternatives. The description never addresses the choice between a dated lookup and a random batch of pictures, which the schema handles silently.

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

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

No annotations are provided, so the description must carry the behavioral burden. It discloses what the response contains (size, hazard status, distance, velocity), which is useful, but says nothing about authentication needs, rate limits, pagination, or error behavior for a live third-party API.

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?

Two sentences, zero waste, with the resource clearly front-loaded and the return contents following. Every clause earns its place.

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 low-complexity read tool with three optional, fully documented parameters and no output schema, the description covers what it fetches and what it returns. It is nearly complete, with only API-access and rate-limit behavior unaddressed.

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 three parameters (date, days, hazardous_only) are already fully documented with defaults and ranges. The description adds no parameter-level syntax or format details beyond the schema, so the baseline of 3 applies.

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?

State a specific verb and resource ('Get Near Earth Objects (asteroids)') and names the data source (NASA NeoWs), so an agent knows exactly what it fetches. The resource is clearly distinct from siblings get_apod and get_space_weather, though the differentiation is implied by subject matter rather than stated.

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?

There is no indication of when to use this tool versus the sibling tools, nor any prerequisites, exclusions, or context for selection. Usage is only inferred from the resource name.

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

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

With no annotations provided, the description carries the full behavioral burden, yet it discloses nothing about return format, pagination, rate limits, or auth requirements. The list of event categories hints at response content, but that is minimal disclosure for an unannotated tool.

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?

Two short sentences, no filler, with the core purpose front-loaded and the coverage list following. Every sentence earns its place.

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 simple two-parameter read tool with fully documented schema and no output schema, this is close to adequate, but it omits the return shape and any operational caveats an agent might need before calling a third-party NASA endpoint.

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 both parameters (days and type, including ranges and defaults) are fully documented in the schema. The description only echoes the event categories that the type parameter already enumerates, adding no further semantic 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?

States a specific verb and resource (get space weather events) and names the data source (NASA DONKI), plus enumerates the event categories returned. It does not explicitly differentiate itself from the siblings get_apod or get_near_earth_objects, but those names are self-evidently different resources.

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 says what the tool returns but never states when to use it versus alternatives, nor any prerequisites (e.g., whether a NASA API key is required). Usage is only inferable from the purpose statement itself.

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