field_summary

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals what data is included, but does not state whether the tool is read-only, whether the case must already have a run/summary file, or what assumptions it makes about the input. The presence of an output schema mitigates, but does not eliminate, the uncertainty.

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 one compact line with no filler, and the most important qualifier 'Field-level' appears first. It is appropriately sized for a simple tool.

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?

The tool is simple (one required parameter, output schema available), so the minimal description is partly acceptable. However, the lack of any guidance on case_path or on when to use this tool relative to well_summary and read_summary leaves invocation partially to inference.

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?

The schema has 0% description coverage and the tool description never mentions case_path. The parameter name is somewhat self-explanatory, but the description adds no path format, qualification, or behavior hints to help an agent construct valid input.

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 states the delivered result as 'Field-level KPIs' and itemizes the included metrics (cumulative production/injection, pressure, final rates), which makes its purpose clear and differentiates it from well-level or raw-vector tools. It lacks an explicit verb such as 'returns' or 'computes', which prevents a 5.

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 statement about when to prefer this tool over well_summary, read_summary, list_summary_vectors, or summary_tool. The word 'Field-level' is the only selection signal, but it is never framed as guidance or contrasted with alternatives.

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