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

The annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. Beyond that, the description discloses the return payload (column names and types); with no output schema, that is genuinely useful. It also adds a trust signal that the results come from a real engine rather than LLM generation. It says nothing about error behavior for invalid or missing file_id values, so it is not 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?

The description is three compact segments: a bracketed label, the use case, and the return value; the purpose is front-loaded. Every clause carries information, and there is no filler. The bracketed tag mildly repeats the annotation title, but that is negligible.

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 one-parameter read tool with complete schema coverage and no output schema, the description covers purpose, the trigger, and the return shape. It is only slightly short of complete because it omits failure modes for invalid file ids and any note on output ordering or size.

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?

There is a single parameter, file_id, and schema description coverage is 100%, so the schema already documents it. The description adds no meaning beyond that: it does not explain how to obtain a file_id, or what happens if the id is unknown. A 3 is the correct baseline when the schema does the work.

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 a specific verb and resource: read the variable column names of a given data file, returning column names and types. It is clearly distinct from analytical siblings such as act_data_quick_stats or act_table_one; those consume the file, while this one only inspects its schema. It does not explicitly name a sibling to avoid, so it falls short of 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?

It gives explicit when-to-use guidance: call it before doing a Table One or modeling, because you must see which variable columns exist. That is a concrete trigger tied to real downstream tasks. It stops short of a 5 because it never states exclusions, such as when to use a quick-stats or profiling tool instead, or which file types are acceptable.

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