get_rate_card

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

With no annotations, the description carries the full burden. It discloses key behaviors: country aliases are resolved safely ('never uses an ambiguous substring match'), fallback to Constants sheet occurs when no country sheet exists ('clearly identified as USD day-rate fallback'), and it states the return format ('compact JSON with the selected country sheet/fallback metadata and the exact quote rows'). The read-only nature is implied by 'look up' but not explicit; still, it provides solid behavioral context.

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 description is well-structured as a docstring with clear sections: a one-line purpose, Args bullet points with concise explanations, and a Returns note. It is front-loaded with the main purpose and every sentence adds value. Slightly verbose due to parameter details, but efficiently organized.

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?

For a read/lookup tool with three parameters and an output schema, the description covers all critical aspects: parameter semantics, fallback behavior, and return format. It does not discuss error handling for invalid countries or authentication, but these are minor for a read-only tool. The description is complete enough for an agent to call it correctly.

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 0%, so the description must compensate. It does so thoroughly: country explains expected format ('verified country') and alias resolution; roles explains it's optional, provides an example, and states omission yields all roles; level explains exact seniority filter with examples ('Junior', 'Mid Senior', 'Senior'). This adds meaning beyond the bare schema properties.

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 purpose: 'Look up quote-ready manpower rates for the verified client country.' This is a specific verb and resource (look up rates for a country). It does not explicitly name alternative tools, so it doesn't fully distinguish from siblings like list_rate_card_countries, but the purpose is unambiguous enough for an agent to select it.

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 context is implied: the tool is used when needing rates for a verified country. It does not explicitly state when NOT to use it or mention alternative tools (e.g., list_rate_card_countries for listing countries, create_project_rate_card for creation). There are no exclusions or comparisons, so guidance is minimal but not misleading.

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