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tresor4k

macalc

call_any_calculator

Read-onlyIdempotent

Invoke any of 446 calculators from the macalc catalog by specifying the exact tool name and its arguments. Returns JSON with result, formula, source, and reference URL.

Instructions

Invoke ANY of the 446 calculators of the hosted macalc catalog by name — not just the core tools listed by this server. Workflow: 1) list_bundles to find the right domain, 2) get_bundle_tools(bundle_id) to get the exact tool name and its parameters, 3) call_any_calculator with that tool_name and its arguments object. The call is forwarded verbatim to the hosted macalc API (network request, no authentication, nothing stored beyond anonymous usage counters). Read-only and deterministic for a given catalog version. Returns the target calculator's JSON result ({result, formula, source, reference_url}) or a clear error if the tool name is unknown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsNoArguments object for the target calculator, matching the parameter names given by get_bundle_tools. Pass {} if the tool takes no parameters.
tool_nameYesExact name of the target calculator as returned by get_bundle_tools (e.g. 'calculate_french_notary_fees').
Behavior5/5

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

Beyond annotations (readOnlyHint, etc.), the description adds: network request, no authentication, anonymous usage counters, verbatim forwarding, deterministic per catalog version, return structure ({result, formula, source, reference_url}) and error behavior. This fully discloses operational traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences with no waste: first sentence states core purpose, second gives workflow, third adds implementation details, fourth describes output. Perfectly front-loaded and every sentence adds essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (dispatcher to 446 calculators) and absence of output schema, the description fully covers: what it does, how to use it, what to expect in return, safety/behavioral notes, and edge cases (unknown tool name). No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema already covers both parameters with descriptions (100% coverage). Description adds workflow context and the explicit hint to pass {} if no parameters, marginally improving clarity beyond schema. The additional value is modest, so 4 rather than 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool invokes any of 446 calculators by name, distinguishing it from the specific calculator siblings via 'not just the core tools listed by this server'. The verb 'Invoke' combined with 'ANY' and the catalog size makes the scope unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides an explicit three-step workflow: list_bundles → get_bundle_tools → call_any_calculator, telling the agent exactly how to discover and call the correct tool. Also implies the specific calculator tools are alternatives for common cases, giving clear when-to-use guidance.

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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