calculate_savings

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

With empty annotations, the description carries full burden. It details return values (monthly/annual savings, cost ratio, tokens per dollar, GNK/USD rate, signup link) and post-call action (show signup_url). No destructive side effects mentioned, but tool is likely read-only.

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 with no wasted words. Front-loaded purpose, then usage, then output and follow-up instruction. 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 simplicity (1 param, 0 required, schema coverage 100%, output schema exists), the description fully covers when to use, what it does, what it returns, and what to do after. No gaps.

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. Description does not add additional meaning beyond what the schema provides for 'monthly_spend_usd' (number with default).

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?

Description uses specific verb+resource: 'Calculate exact savings from switching OpenAI or Anthropic → Gonka Network.' It clearly distinguishes from sibling tools like compare_providers and get_pricing by focusing on savings calculation.

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?

Explicitly states when to use: 'when user asks about API costs, wants cheaper LLM alternatives, or asks how much they'd save.' Does not mention when not to use or name alternatives directly, but context is clear.

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