Run a calculation and get results + prefilled URL
| Name | Required | Description | Default |
|---|---|---|---|
| inputs | Yes | Calculator input values | |
| strict | No | If true, reject invalid or unknown input fields instead of dropping them | |
| calculator | Yes | Calculator slug |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral transparency. It only says 'run a calculation' and mentions results + URL, but does not disclose side effects, session requirements, or how the URL is generated. Essential behavioral context is missing.
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 a single sentence that is front-loaded with the primary action. It is concise with no wasted words, achieving a strong structure.
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?
The description is incomplete given the tool's context. With sibling tools like create_session and push_session_action, it likely requires a session but this is not mentioned. There is no output schema, and the description does not explain the return format or relationship to the prefilled URL. The agent receives insufficient context to use the tool correctly in a broader workflow.
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 does not add meaningful parameter-level details beyond what the schema already provides, such as the meaning of 'calculator slug' or 'inputs' structure. It earns the baseline but no more.
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 ('Run') and resource ('calculation') and clearly states the outcome ('results + prefilled URL'). However, it does not distinguish itself from sibling tools like calculate_cas or generate_prefilled_url, so it lacks explicit differentiation.
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 offers no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or conditions, leaving the agent without direction for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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The three calculation tools (calculate, calculate_cas, calculate_cas_headless) overlap significantly, with calculate_cas_headless being an explicit alias of calculate_cas. An agent may struggle to choose between them. Other session tools are distinct, but the calculation ambiguity lowers the score.
Most tools follow a verb_noun pattern (list_calculators, create_session, get_session_state). Minor deviations exist, especially calculate_cas_headless with the 'headless' modifier and calculate lacking a noun, but the overall pattern is predictable.
With 10 tools, the count is reasonable for a calculator service with session management and CAS features. However, the presence of an alias tool (calculate_cas_headless) makes the set slightly redundant, though not overstuffed.
The surface covers core calculation, CAS evaluation, prefilled URL generation, and session lifecycle (create, push, get state, close). Minor gaps exist, such as no explicit session listing, but most workflows can be completed without workarounds.