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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety is covered. The description adds genuinely new behavioral context beyond the annotations: canvas tokens are process-local capabilities and inspection is confined to the supplied canvas, which tells the agent about scoping and side-effect boundaries it could not infer from structured fields.

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, front-loaded with what is inspected, followed by the scoping constraint. No filler, though the phrase "original scientific provenance" is slightly abstract and could be tightened.

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?

With an output schema present, return values need not be explained, and the description covers scope, content (schemas, units, provenance), and token semantics. It is complete enough to call correctly, with only the sibling-routing guidance left unstated.

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 are already documented, including the table parameter's "omit to inspect this canvas" behavior. The description adds no syntax, token lifecycle, or multi-table semantics beyond what the schema states, so 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?

The description uses a specific verb ("Inspect") against specific resources ("table schemas, physical units and original scientific provenance") within a named scope ("canvas_id"). It is clearly distinguishable from data-fetching siblings like nasa_power_dataframe_query, but it never names or contrasts them explicitly.

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?

Usage is implied through the prerequisite "a canvas_id returned by a producing POWER tool," which tells the agent this is a follow-up step to another call. However, there is no explicit guidance on when to choose this over nasa_power_dataframe_query or when inspection is unnecessary.

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