Alias of calculate_cas. Headless MCP-only CAS evaluator; if unsupported features are requested, returns GUI handoff details.
| Name | Required | Description | Default |
|---|---|---|---|
| strict | No | If true, reject unknown fields and malformed expressions instead of dropping them | |
| expression | No | Single CAS expression to evaluate | |
| expressions | No | Optional ordered list of CAS expressions to evaluate in one isolated context (supports assignments across the batch) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden. It reveals a non-obvious fallback behavior (returning GUI handoff details for unsupported features), which is useful. However, it does not mention side effects, read-only status, error handling, or other behavioral traits.
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 front-loads the alias relationship and then states the core function. It is concise with no padding, though 'Alias of calculate_cas' is partly redundant given the tool name.
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 3-parameter tool with full schema documentation and no output schema, the description gives basic context but omits details like return structure or how 'GUI handoff details' appear. It is adequate for a simple evaluator but leaves some gaps for an AI agent.
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?
The input schema covers 100% of parameters, so the baseline is 3. The description adds no parameter-specific details; the schema already explains strict, expression, and expressions. No additional semantic value is provided.
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 identifies the tool as a 'Headless MCP-only CAS evaluator' and an alias of calculate_cas, making the core purpose clear. It differentiates from siblings by emphasizing the headless MCP-only nature, though the action verb is implied ('evaluator') rather than explicit.
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 in MCP-only/headless contexts and mentions fallback to GUI handoff details, but does not explicitly state when to use this over calculate_cas or other siblings. The alias reference gives some context, but there are no clear exclusions or alternative recommendations.
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.