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

Annotations already declare readOnlyHint, openWorldHint=false, and idempotentHint, so the safety profile is covered. The description adds meaningful behavioral detail beyond annotations, including creation/expiry timestamps and whether data is truncated relative to the upstream source, which helps agents interpret results correctly.

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 a single dense sentence that front-loads the core action ('List dataframes') and follows with specific, useful detail about sources and returned metadata. Every clause earns its place and there is no filler or repetition.

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 optional parameter, no required inputs, and an output schema already exists. The description identifies the relevant source tools and the metadata fields provided, which is sufficient for an agent to know when and how to invoke it.

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 coverage is 100%, so the single optional 'name' parameter is already fully documented in the schema. The description adds no extra parameter details, but with complete schema coverage the baseline score of 3 is appropriate.

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 opens with a specific verb and resource, 'List dataframes', and clearly scopes which tools' dataframes are included. It also enumerates the fields each entry surfaces, making the tool's purpose unmistakable and differentiating it from query and fetch siblings.

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 gives clear context: this tool is for inspecting materialized dataframes and their metadata, not for transforming or querying them. It does not explicitly name alternatives or state when not to use it, but the contrast with sibling tools like secedgar_dataframe_query and secedgar_fetch_frames is implied strongly enough.

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