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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real behavioral context beyond them: every assumption is stated, time for checking the output is deducted, and the agent is told to source inputs from the owner rather than invent them. It doesn't describe the numeric outputs in detail, which keeps it from a 5.

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, front-loaded with the core purpose before the usage triggers and the data-sourcing caveat. No filler or repetition. Slightly long for the value added, but each sentence carries a distinct instruction.

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?

No output schema exists, so the description must carry the return-value burden; it partially does by indicating that assumptions are surfaced and checking time is deducted, implying a payback/ROI style result. Combined with fully documented inputs, an agent has enough to call it correctly, though the exact returned metrics and units are not spelled out.

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 every one of the 6 parameters (including the enum for automatableShare) is already documented in the schema. The description only restates the parameter categories in prose ('owner's own hours, headcount, hourly cost and supplier quote'), adding framing but no semantics beyond the schema. Baseline 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?

States a specific verb+resource ('works out whether automating a task pays for itself') and enumerates the inputs it reasons from (owner's hours, headcount, hourly cost, supplier quote). This distinguishes it plainly from siblings like assess_automation_opportunities or get_sector_playbook, which are discovery/advisory rather than a payback computation.

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 explicit trigger conditions: 'Use when an owner asks if an AI tool or automation is worth the money, how long it takes to pay back, or how to estimate the return before committing.' It also adds a data-sourcing instruction ('ask the owner for the numbers rather than guessing'). It does not, however, name a when-not boundary or point to a sibling alternative, 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.