Get DataLens Spark application

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

Excellent value-add beyond annotations: it discloses that the API is experimental and 'not measured,' and, crucially, the unusual error contract that an unknown id returns 403 Permission denied rather than 404. This is exactly the kind of non-obvious behavior an agent needs. Annotations already cover readOnly/idempotent/openWorld, so no contradiction.

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?

Front-loads the purpose in the first sentence, then adds two short caveats. Reasonably tight, though the phrasing is a bit fragmented ('its times and what it runs').

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 2-param read tool with annotations covering the safety profile, the description supplies the key operational caveats (experimental status, misleading 403 on unknown id). An output-shape note is unnecessary since no output schema exists, but could have been more explicit.

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 both cluster_id and application_id are already documented in the schema. The description adds no parameter syntax or format beyond that; 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 a specific verb+resource: retrieves one Spark application, and enumerates what it returns (status, times, runs). This clearly distinguishes it from the sibling datalens_sparkapplications_list, though the sibling isn't named explicitly. Not tautological.

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?

Usage is strongly implied – this is the get vs the list. But the description never explicitly says 'use this to fetch a single application by id, use datalens_sparkapplications_list to enumerate them.' No when-not-to-use guidance.

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