Cost of one task, one market

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

Annotations already declare readOnlyHint=true, and the description adds meaningful behavioral context: the exact output components (human/AI cost, ratio, source) and the important market naming exception. This goes beyond the structured fields without contradicting them.

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?

Two sentences, both information-dense: the first defines the output, the second explains market values and a critical caveat. No wasted words or redundancy with the schema.

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?

Given the simple read-only nature, two parameters, and no output schema, the description fully covers the return values and the market ambiguity. It leaves no significant gaps for a caller to understand what they will receive.

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 coverage is 100%, so baseline is 3. The description adds country names for market codes and explicitly warns that 'uk' means Ukraine, enhancing the schema's terse alias list. This extra clarity justifies a score above baseline.

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 clearly states the tool's function: retrieving the cost of one unit of a task in a specific market, and enumerates the returned figures (human cost, AI cost, ratio, source). This distinguishes it from sibling tools like estimate_annual_cost, which implies a broader annual scope.

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 implies usage for single task-market unit costs but does not explicitly contrast with sibling tools like estimate_annual_cost or get_cost_of_work_index. It offers useful context about market codes and the 'uk' caveat, but no when-to-use/when-not-to-use guidance relative to alternatives.

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