get_series_observations

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description fails to mention any behavioral traits such as whether this is a read-only operation, potential rate limits, authentication requirements, or what the output contains. For a tool with 13 parameters and no annotation coverage, this is a critical omission.

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 extremely concise with a single sentence that directly states the alias relationship. There is no wasted verbiage or unnecessary elaboration, making it front-loaded and efficient. However, this conciseness comes at the cost of completeness.

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 the high complexity (13 parameters, 1 required), 0% schema description coverage, no annotations, and the presence of an output schema, the description is completely inadequate. It fails to explain the tool's purpose, parameter semantics, or behavioral context, leaving the agent unable to use the tool effectively despite the output schema potentially covering return values.

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 schema description coverage is 0%, meaning none of the 13 parameters are documented in the schema. The description adds no information about parameter meanings, usage, or relationships (e.g., what 'series_id' refers to, how date parameters work, or what 'output_type' controls). This leaves all parameters semantically undefined, severely hindering tool invocation.

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 'Alias for get_observations' is a tautology that restates the tool name without explaining what it actually does. It doesn't specify the verb (e.g., 'retrieve' or 'fetch') or the resource (e.g., 'economic data observations for a series'), making the purpose vague. While it references a sibling tool, it doesn't distinguish this tool's specific function from that sibling.

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 provides no guidance on when to use this tool versus alternatives. It mentions 'get_observations' as an alias but doesn't explain if this is preferred over other tools like 'get_release_observations_v2' or 'search_series', nor does it specify any context or prerequisites for usage. This leaves the agent without practical direction.

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