Raw dataset

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

Annotations already cover the safety profile (readOnlyHint, openWorldHint), and the description adds genuinely useful behavior: the return payload ('rows ... plus generation time and source') and the optional limiting of rows. With no output schema, this return-shape disclosure carries real weight; only pagination/error behavior is left unstated.

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?

One compact sentence, front-loaded with verb and resource, with the return shape trailing. It is dense but every clause (source of names, optional limit, return contents) carries information.

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 two-parameter generic fetcher with no output schema and no annotations on return shape, the description covers what comes back (rows, generation time, source) and how to constrain it, plus a pointer for discovering dataset names. Remaining gaps are pagination and failure modes, which matter less here.

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 50%: 'name' is fully exemplified in the schema, while 'limit' has only min/max bounds and no prose. The description's 'optionally limited' gives 'limit' its meaning, which offsets part of the gap, but nothing is said about units, default value, or behavior when omitted.

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?

States a specific verb and resource ('Fetch ... dataset by name') and adds scope ('any Blockchain Lab Open Data API dataset', 'see the catalogue'). It is clearly the generic fetcher among the curated single-dataset siblings (chains_tvl, stablecoins, dex_volumes), though it never names a sibling to sharpen the distinction.

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 only direction is 'see the catalogue' for valid names; there is no guidance on when to prefer this generic tool over the curated siblings that surface many of the same datasets. An agent has to infer selection from the word 'any' alone.

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