Deep Thought Consultech

which_product

Given a problem described in the user's own words, recommend which DTC product(s) or service(s) address it and explain why. Use this when someone describes a situation rather than naming a product. It matches on the description only and says so when nothing fits — it never invents a capability.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "problem": "<problem>"
    },
    "name": "which_product"
  }
}

Input Schema

Name	Required	Description	Default
`problem`	Yes	The situation, in plain language — what material they have and what they cannot do with it.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses the matching basis ('matches on the description only'), the empty-result behavior ('says so when nothing fits'), and the fabrication guardrail ('never invents a capability'). It does not cover latency, permissions, or result ranking, which keeps it from a 5.

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?

Three short sentences with the core behavior front-loaded, followed by the selection condition and the guardrail. No filler or repeated restatements of the tool name.

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

Completeness4/5

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

No output schema exists, and the description compensates by indicating the response contains recommendations plus reasoning, and what happens when nothing matches. That covers the main gaps for a single-parameter recommendation tool, though it could say more about what a recommendation entry contains.

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

Parameters3/5

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

Only one parameter, and the schema already documents it at 100% coverage. The description's 'in the user's own words' phrasing reinforces the expected free-text style but adds no new syntax, format, or constraint details beyond the schema.

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?

States a specific verb and resource — 'recommend which DTC product(s) or service(s) address it' — plus the mechanism ('explain why'). It also distinguishes itself from name-based lookup siblings by saying it's for when someone 'describes a situation rather than naming a product.'

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

Usage Guidelines4/5

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

Gives a clear when-to-use condition ('someone describes a situation rather than naming a product'), which implicitly routes product-name queries to the lookup siblings. It stops short of naming an explicit alternative or stating exclusions beyond that contrast.

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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