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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, and the description adds real behavioral context beyond them: the check is deterministic, makes no AI call, and it enumerates the exact classes of findings produced (orphan nodes, dead ends, single-branch decisions, unlabeled branches, ownerless steps, AI-guessed edges, missing_start/missing_end). For a tool with no output schema, that is unusually strong disclosure.

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?

Purpose and the key differentiator are front-loaded in the first clause, with the return enumeration deliberately following. The second half is a single very long comma-separated sentence; every item earns its place given the absence of an output schema, but the structure could be broken up for readability.

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?

With one simple string parameter, rich annotations, and no output schema, the description covers the remaining burden by fully enumerating what the review returns. An agent has everything needed to decide to call it and to interpret the response.

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?

There is a single required parameter whose schema description coverage is 100% ('The id of the flow to review'), so the schema already carries the semantics. The description only refers to 'a Wavelength flow' generically and adds no format or constraint detail beyond the schema, which is the baseline-3 case for a fully documented single parameter.

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 and resource ('Run a deterministic gap check on a Wavelength flow') and immediately differentiates the mechanism from AI-driven siblings with 'with no AI call'. An agent can tell this apart from ask_flow, summarize_flow, or get_flow without opening a schema.

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 'no AI call' / 'deterministic' framing gives clear context that this is the cheap, reproducible alternative to AI-backed analysis, and the closing clause about questions 'an SE can ask on the next call' describes the follow-on workflow. It stops short of naming a specific alternative tool or stating an explicit when-not condition, so it lands at 4 rather than 5.

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