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cognitive_solve_word_problem

Solve math word problems (GSM8K/SVAMP/MATH) via topological constraint propagation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionNo
equationsNo
quantitiesNo
target_variableNotarget

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • removedInput schema / properties / quantities / additionalProperties
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "number"
-    },
-    {
-      "type": "integer"
-    }
-  ]
-}
    • addedInput schema / properties / quantities / anyOf
      Added value: +[
+  {
+    "additionalProperties": {
+      "anyOf": [
+        {
+          "type": "number"
+        },
+        {
+          "type": "integer"
+        }
+      ]
+    },
+    "type": "object"
+  },
+  {
+    "type": "null"
+  }
+]
    • addedInput schema / properties / quantities / default
      Added value: +null
    • removedInput schema / properties / quantities / type
      Removed value: -"object"
    • addedInput schema / properties / question / default
      Added value: +""
    • removedInput schema / required
      Removed value: -[
-  "question",
-  "quantities"
-]
  2. Added

TDQS

C2.3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the algorithm ('topological constraint propagation') but does not state whether the tool is read-only, what it returns, any side effects, or permission requirements. The mention of the algorithm is a positive but minimal step; key behavioral details are absent.

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

Conciseness2/5

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

The description is extremely short (one sentence), which is concise, but it under-specifies the tool. Given the tool's complexity (4 parameters, no annotations, no schema descriptions), the description is not appropriately sized—it omits critical information needed for correct invocation.

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

Completeness1/5

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

For a tool with 4 parameters, no annotations, and no schema descriptions, the description is severely incomplete. It covers only purpose and a hint at method, leaving usage, parameter semantics, and behavioral expectations entirely uncovered. The presence of an output schema does not compensate for these gaps.

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

Parameters1/5

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

The input schema has 0% description coverage for its 4 parameters, and the tool description does not mention any of them (question, equations, quantities, target_variable). The description adds no value to parameter understanding, leaving agents to infer all semantics from the schema's type definitions alone.

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

Purpose4/5

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

The description states a clear verb ('solve') and resource ('math word problems') with specific benchmark context (GSM8K/SVAMP/MATH), which makes the tool's purpose clear. However, it does not differentiate this tool from its direct sibling 'cognitive.solve_word_problem', which appears in the sibling list, so an agent cannot tell which to choose based solely on the description.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'cognitive.solve_arithmetic' or 'cognitive.solve_word_problem'. It mentions benchmark datasets but gives no context about the type of problems it is suited for or when to select it over other solving tools.

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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