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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so the safe-read profile is covered. The description adds two useful facts beyond that — the 200 KB payload limit and the shape of the analysis (statistics, errors, recommendations, savings estimate). It does not say how malformed or oversized G-code is handled, nor whether the analysis is deterministic or model-generated, so it adds context without being rich.

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 entire definition is a single front-loaded sentence that leads with what the tool is and what it returns, with the size constraint appended last. It is dense and unusual to read, but every clause carries information and there is no filler.

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?

An output schema exists, so return values need not be spelled out, and annotations cover the safety profile for a 2-parameter tool. The description supplies the payload limit and the nature of the analysis, leaving only minor gaps such as error behavior on invalid input.

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%, so both parameters (gcode, machine) are already documented with types, requiredness, and the 200 KB limit. The description restates the size cap but adds nothing about the optional machine-model parameter or how it influences the analysis, so the baseline of 3 applies.

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 names a specific verb+resource pair (analysis/optimization of a CNC control program) and enumerates the concrete outputs: statistics (lines, moves, feeds), typical errors, AI-driven optimization recommendations, and a savings estimate. No sibling tool (machines, orders, guides, leads) does anything comparable, so an agent can route to it unambiguously without opening the 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?

Usage is only implied: 'if you have G-code, send it here for analysis.' There is no explicit when-to-use, when-not-to-use, or prerequisite/permission statement, and no alternatives are named. The 200 KB input cap is the only boundary given, and it functions as a constraint rather than selection guidance.

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