Get FCSC dataset observations

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

With no annotations, the description carries the full burden. It discloses that this is a read-only 'fetch' operation, returns a labelled table, and mentions the 'flat flavour' of the API. However, it does not mention pagination behavior, error handling, rate limits, or other side effects, which would be valuable for an agent.

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 exactly two sentences, front-loaded with the core purpose ('Fetches official observations') and includes a key usage instruction (always cite). It is concise with no redundant or filler content.

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 has no output schema, so the description must convey what the return looks like. It says 'labelled table' but does not specify columns or structure beyond that. For a data-fetching tool, this is a moderate gap; more detail about the table's content (e.g., periods, values, dimensions) would improve completeness.

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 input schema has 100% description coverage for all five parameters, so the schema already documents each parameter's meaning. The description adds no extra parameter-level detail, which is acceptable given the high schema coverage.

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 fetches official observations for one FCSC dataset from the UAE statistics SDMX API (flat flavour) and returns a labelled table. This distinguishes it from sibling tools listDatasets and getDatasetStructure, which list datasets and retrieve structure respectively.

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 clear context: use this tool to fetch observations for a specific dataset, and there is an implicit instruction to use listDatasets to find the datasetId. It also includes a citation requirement. However, it does not explicitly name alternatives or exclusion criteria, so it stops short of a 5.

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