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

Beyond the readOnly/idempotent annotations, the description adds substantial behavioral context: match ordering ('exact ticker, exact CIK, name prefix, name contains'), entity priority ('companies with tickers before other filers such as individuals'), empty-result behavior ('no match is an empty list, not an error'), and accessibility ('no API key or payment needed'). It contradicts nothing in the annotations.

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 front-loaded with the core purpose, then uses compact parentheticals to encode the matching priority and return fields. Each sentence contributes either usage guidance, result semantics, or operational context; there is no filler.

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 lookup tool with only two parameters, the description plus schema fully covers input formats, result selection, ordering, empty results, output fields, and free access. An agent can correctly decide to call it and interpret its response without additional documentation.

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 baseline is 3. The description adds value by explaining how the query is ranked and interpreted into exact vs prefix vs contains matches, and how the limit applies to the returned ordering. This goes beyond the schema's basic type and length descriptions.

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: 'Find a company's SEC CIK from its ticker, CIK or name.' It also distinguishes this tool from the sibling data tools by stating that every company tool takes a CIK, so this lookup is the prerequisite step.

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 clear context by saying 'call this first when you only have a ticker (AAPL) or a name (apple).' It does not explicitly name a sibling alternative or state 'do not use when you already have a CIK,' but that exclusion is strongly implied by the CIK prerequisite framing.

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