analyze_run_by_id

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool reads Spark UI or event logs plus cluster config and returns detailed analysis, which is useful, but it does not state whether the operation is read-only, what permissions or access are required, how long it may take, or how errors are handled.

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 a single, front-loaded sentence that efficiently lists the returned analysis dimensions without wasted preamble. It is dense but appropriate for the amount of information conveyed.

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 is complex and has no annotations, but an output schema exists so return values need not be fully explained. The description covers the analysis scope reasonably well, yet it leaves key gaps around parameter meanings, sibling-tool selection, and operational constraints.

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 0%, so the description must compensate for undocumented parameters. It only indirectly implies the required run_id via the tool name and 'one Databricks job run'; it does not explain the optional job_id or stage_plans parameters at all.

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: fetch one Databricks job run and return a complete analysis including anti-patterns, stage metrics, query plans, and sizing. It is clear what the tool does, but it does not distinguish itself from the sibling analyze_run tool or explain how it differs from analyze_stage/diagnose_job.

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 implies usage by saying it fetches one run and returns a complete analysis, but it gives no explicit when-to-use guidance, no exclusions, and no alternatives among the sibling tools such as analyze_run or analyze_stage. An agent must infer when this tool is preferred over the others.

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