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

Annotations already establish readOnly, non-destructive, and closed-world behavior, so the description's job is to add context — which it does by listing the data returned per well (max temperature, lithology, failure modes, root cause, lessons, induced seismicity, sources). It does not mention result limits or ranking behavior, which keeps it short of 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?

Two sentences with the searchable corpus front-loaded and the use cases appended. The parenthetical well list is dense but earns its place by signaling coverage; otherwise there is no wasted text.

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 no output schema, the description compensates by enumerating the returned fields per well, which is exactly what an agent needs to judge relevance. A note on result volume or ranking would have made it fully complete.

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%, and both parameters are well documented in the schema, including the 374 °C supercritical convention. The description adds no parameter-level detail beyond what the schema already provides, 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?

The description names a specific verb and resource (search documented superhot/high-temperature geothermal wells) and enumerates concrete example wells and the attributes indexed, so the agent knows exactly what corpus is being queried. It does not explicitly contrast itself with siblings like ask_superhot or search_library, so differentiation is left partly to inference.

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?

"Use it for drilling, completion, materials, site-comparison, or risk questions" gives clear positive usage contexts. However, it offers no exclusions or guidance on when a sibling such as ask_superhot would be the better choice.

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