get_flow_results

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

Beyond the readOnlyHint annotation, the description discloses the specific return content per job type (terminal stats, percentile bands, sample paths, price_history) and behavioral traits such as the ~60% size reduction from summary_only. It also reveals preconditions (job completion) and scenario-specific fields, adding substantial context not present in 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 information-dense but well-organized by job type and usage scenarios. Every sentence conveys a distinct fact—alternatives, output composition, size optimization, and prerequisites. No fluff or redundancy; the length is justified by the tool's complexity.

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 the output schema and readOnly annotation, the description covers all necessary aspects: return contents for all job types, usage of summary_only, alternative tools, and the prerequisite of checking job completion. It is complete without unnecessary enumeration of fields.

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 100%, so baseline is 3. The description adds contextual meaning by explaining how job_type affects output (generate vs validate), the effect of summary_only, and the source of job_id. It also clarifies that sample paths are dropped with summary_only, enriching the parameter definitions.

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 clearly states the tool retrieves results of a completed Flow job, with explicit breakdown for generation, scenario, and validation outputs. It distinguishes itself from siblings by naming check_flow_job (verify completion) and download_flow_paths (full raw CSV), so the agent knows exactly what this tool does.

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?

Provides explicit usage guidance: 'Use check_flow_job first to verify the job is completed', 'Use download_flow_paths to get full raw path data as CSV', and explains when to set summary_only=true. It also clarifies which job types are supported and the default behavior.

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