Audits the current logistics plan and returns SLA, green carbon, and load balance critique scores to guide optimization loop iterations.
Audits current logistics plan and returns SLA, green carbon, and load balance critique scores.
| Name | Required | Description | Default |
|---|---|---|---|
| iteration | No | Optimization loop iteration number |
Changes observed during successful MCP inspections.
v1.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that it returns scored critiques across three named dimensions, which is useful behavioral context, but says nothing about whether it recomputes or reads stored results, cost, or latency.
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?
One sentence, zero waste, with the action front-loaded and the return payload following immediately. Nothing to trim.
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?
There is no output schema, so the description usefully names the three critique dimensions returned. It stops short of describing scale, format, or whether results are per-iteration, but for a single-param read-only audit tool it is largely sufficient.
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 100% for the single 'iteration' parameter, so the schema already documents it; description adds no syntax or semantics beyond that. Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('audits current logistics plan') and even names the return dimensions (SLA, green carbon, load balance critique scores). This is clearly distinguishable from the sibling set (status/optimize/inject/inspect), though it never explicitly names a sibling.
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 phrase 'current logistics plan' implies the tool operates on an existing plan, but there is no explicit when-to-use guidance, no ordering relative to optimize_cvrp_routes or inject_disruption, and no stated prerequisites. Usage is inferable but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.