List DataLens Spark applications

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

Annotations already cover read-only/idempotent/open-world, so the bar is lower, yet the description adds real behavioral context: auto-pagination, the experimental/unmeasured API status, and the non-obvious quirk that an unknown cluster returns 403 rather than 404. That last point is genuinely useful and not derivable from structured fields.

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?

Reasonably short, but the phrasing is awkward and cryptic ('A cluster nothing knows answers 403 Permission denied, not 404: it is not a lack of rights') forces the reader to decode it. The purpose is front-loaded, but the error note costs more parsing effort than its length suggests.

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 paginated list tool with no output schema and full schema coverage, the description covers pagination and a key error case, which is adequate. It does not describe what an application record contains or how the configured cap interacts with limit, leaving some operational gaps.

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 description coverage is 100%, so limit, filter, and cluster_id are already fully documented in the schema. The description adds nothing about parameter syntax or semantics, so baseline 3 applies.

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 the resource clearly ('the applications of a Spark cluster') and the scope is unambiguous against the sibling datalens_sparkapplications_get, which retrieves one application. The verb is only implied via the name/title, and the sentence is a fragment rather than a full 'lists X for Y' statement.

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?

No statement of when to call this versus datalens_sparkapplications_get or the other datalens_sparkapplications_* siblings. The only contextual note is the 403-vs-404 error behavior, which is diagnostic rather than selection guidance.

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