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

With no annotations, the description carries the full disclosure burden and does well: it explains the data source cadence (FINRA settlement dates, twice a month), ordering (newest first), and the no-symbol fallback behavior. It does not detail edge cases or exact return field names, but for a read-only data lookup it is reasonably transparent.

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 dense sentences, no filler. The core metric set is front-loaded, followed by the important no-symbol behavior. Every phrase earns its place.

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 tool with two fully documented optional parameters and no output schema, the description is complete: it tells the agent what data fields are returned, the update frequency, the sort order, and the unparameterized fallback. An agent can invoke it correctly with the information provided.

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 the baseline is 3. The description adds extra value by explaining what happens when symbol is omitted, which directly clarifies the optional symbol parameter, while limit's meaning and default are already fully documented in the schema.

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 resource (FINRA short interest for US stocks), lists concrete metrics (shares short, average daily volume, days to cover, change), and clarifies the no-symbol fallback. This clearly separates it from siblings like short_volume or fails_to_deliver.

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 rather than stated: the description makes clear this is for short-interest data, but it never explicitly says when to choose this over siblings such as short_volume or threshold_list. No exclusions or alternative tool mentions are provided.

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