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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds useful context: it is a paid resource with a specific price ($0.002 USD per call), and it returns either an execution order or blockers. It doesn't disclose side effects, but the annotations cover the safety profile. No contradiction with 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?

Three sentences, all informative: purpose, exclusions, and pricing. The key purpose is front-loaded. The pricing sentence is useful but could be considered secondary; still, it earns its place for a paid resource. No fluff or repetition.

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 validation tool with no output schema, the description tells the agent what it returns (execution order or blockers) but not the structure of that return. It also doesn't explain edge cases like cycles, missing nodes, or how constraints combine. Given the tool's complexity (graph input, 4 params, no output schema), the description is adequate but leaves the agent to infer return format and failure semantics.

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. It mentions 'workflow dependencies and execution constraints' which maps to nodes/edges and max_total_cost/max_total_latency_ms, but it doesn't explain the meaning of individual parameters or how they interact. The schema itself has decent property names and constraints, but the description adds only high-level context. Baseline 3 is appropriate because the schema carries the parameter meaning.

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 ('validates') and resource ('caller-supplied workflow dependencies and execution constraints'), and specifies the output ('deterministic execution order or concrete blockers'). It distinguishes itself from siblings by naming the reliability quality domain and explicitly excluding legal/identity/sanctions/fraud/contractual/regulatory adjudication. However, it doesn't name a specific sibling alternative, and the title is a near-tautology of the name, so it loses a point.

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 gives clear context: it is for reliability quality / result unverifiable scenarios, and explicitly says do not use for legal, identity, sanctions, fraud, contractual, or regulatory adjudication. This is a strong exclusion list. It doesn't name a specific alternative tool to use instead, but the exclusions plus the domain framing provide adequate routing guidance.

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