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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context: pagination via limit (max 200) and offset, no API key required, and open data under CC-BY 4.0. It also describes the return fields (code, name, frequency, dimension labels), which goes beyond 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 action ('List all time series...'), then provides useful examples, a forward pointer to fetch_series, and practical details (pagination, licensing). The examples are valuable for grounding provider/dataset codes, and there is no fluff or repetition of schema fields. It is compact for the amount of context it provides.

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 that an output schema exists, the description does not need to explain return values. It covers what the tool does, how pagination works, the licensing/auth situation, and how to follow up with fetch_series. The schema fills in parameter details. The only minor gap is that it does not warn that 'all' series requires iterating through pages, but the pagination mention covers that implicitly.

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, with each parameter (provider_code, dataset_code, limit, offset) already fully documented, including examples like 'WDI for World Development Indicators' and default values. The tool description itself adds minimal parameter meaning—only reinforcing the pagination limits for limit/offset. Since the schema carries the burden, baseline 3 is appropriate.

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 states a specific verb and resource: 'List all time series available in a specific dataset on DBnomics'. It distinguishes itself from the sibling dbnomics.data.fetch_series by clarifying this is for browsing series metadata, not retrieving data. Concrete examples (WB/WDI, OECD/QNA, EUROSTAT) further anchor the tool's purpose.

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 explicitly directs the agent to use returned series codes with dbnomics.data.fetch_series for actual data, providing a clear downstream workflow. It implies this tool is for discovery/browsing rather than data retrieval, but it does not explicitly name upstream tools like dbnomics.data.datasets or dbnomics.data.providers as alternatives (these are mentioned in the schema descriptions, not the main description).

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