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

Annotations already declare readOnly, idempotent, non-destructive behavior, so the bar is lower; the description still adds real context: AND-combination of filters, facet behavior when unfiltered, the include_facets default shift, and the 'No AI cost' operational trait. It does not discuss result shape or any rate/pagination limits beyond the limit parameter.

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-loaded with purpose, then filter capability, examples, combination rule, facet mode, and cost note — every sentence carries information. The example list is a little long and the sentence structure dense, which keeps it from a 5.

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 9-parameter, no-required-args query tool with no output schema, the description explains both query modes (filtered results vs. facets) and when each applies, which is what an agent needs to choose arguments. It does not describe the shape of returned flows/nodes/edges, leaving some ambiguity about the result payload.

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 3 is the baseline, and the description exceeds it: it explains that node filters cover type/name/owner/connected-to and connection filters cover type/label/AI-inferred, maps these onto the concrete parameters, and clarifies the include_facets default-when-filtered behavior. Only minor syntax details (e.g. comma-separated node_type) are left to the schema.

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 with scope: 'Structured query across every Wavelength flow the user can open (owned, shared, team, organization).' The word 'structured' plus 'No AI cost' implicitly separates it from AI-driven siblings like ask_flow, search_flows, and list_flows, which only list or summarize.

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?

Gives four concrete when-to-use examples (flows using Snowflake, systems connected to Tableau, steps owned by Finance, unconfirmed AI connections) and states that filters combine with AND and that an unfiltered call returns facets. It never explicitly names an alternative tool or a when-not condition, so it stops short of a 5.

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