gamma_list_series

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

No annotations provided, so description carries full burden. It documents return type as list[dict] and raises HTTPError, but omits details on pagination, rate limits, or authorization requirements. Adequate but not rich.

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?

Well-structured with clear sections (description, usage, args, returns, raises, examples). Front-loaded summary, no redundant information, and every sentence serves a purpose.

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?

Given zero parameters and presence of output schema, the description fully covers return type, error conditions, and provides an example. It is comprehensive for the tool's simplicity.

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 tool has zero parameters, and the description explicitly states 'Args: None.' Since schema coverage is 100% with no parameters, the description adds no semantic value beyond the schema, but baseline 4 is appropriate per guidelines.

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 clearly states the tool lists series metadata for structured discovery, specifying verb and resource. It distinguishes from siblings by contrasting series-oriented vs free-text topic-oriented discovery and naming search_public as an alternative.

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?

Explicitly advises use when the user refers to known series or needs metadata before filtering markets. Provides preference direction over search_public, but lacks explicit when-not-to-use or other sibling comparisons.

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