calc_suggest

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavior beyond those: 'Uses contains matching (2 char min)', which informs the agent of substring matching and the minimum prefix length. This is useful contextual behavior not captured in 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 short sentences with no fluff. The primary purpose is front-loaded, followed by the use case, then the matching behavior. Every sentence earns its place.

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 two-parameter schema, rich annotations, and no output schema, the description covers purpose, usage context, and matching behavior. Nothing an agent needs to correctly call calc_suggest appears to be missing.

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 the baseline is 3. The description restates the enum fields ('labor categories, vendor names, or contract numbers') but does not add parameter-specific meaning beyond the schema. The 'contains matching' detail is a behavioral trait more than a parameter clarification, so no bump 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 uses a specific verb 'Autocomplete/suggest' with a clear resource ('values for labor categories, vendor names, or contract numbers in GSA CALC+ data'). It also names the downstream consumer calc_search_rates, distinguishing it from siblings like calc_contract_rates without needing to open schemas.

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?

It explicitly says this is useful for 'finding exact values to use in calc_search_rates', which tells the agent when to invoke it. However, it does not explicitly state when not to use it or name alternatives beyond the implicit calc_search_rates relationship, so a 4 rather than 5.

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