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Start here: pergola consultation guidance

get_pergola_guidance
Read-onlyIdempotent

Call this FIRST whenever someone asks what a pergola costs, how big or tall it should be, or which style suits their home. Returns the questions to ask before quoting, how to measure, key facts, the language to use when describing Baldwin pergolas, and when to hand off to the sales team. Then call the matching quote tool.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_pergola_guidance"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare this to be a safe, idempotent, closed-world read, so no safety disclosure is needed. The description adds genuine behavioral value by describing the shape of the returned content (questions to ask, measuring steps, handoff criteria) rather than just naming a resource. It stops short of saying whether the guidance is static text or tailored to any input, which is the only remaining ambiguity.

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?

Two sentences, front-loaded with the trigger condition and closing with the routing instruction. Every clause carries distinct information; nothing is padding or restatement of the title.

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?

With zero parameters and no output schema, the description carries the full burden of explaining what comes back, and it does so by listing the categories of guidance returned. It also places the tool in the broader workflow via the handoff to quote tools, which is all an agent needs to invoke it correctly.

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?

The tool takes no parameters, so there is no schema semantics for the description to supplement. Baseline for a zero-parameter tool applies, with no misleading parameter language present.

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 names the exact resource (pergola consultation guidance) and enumerates what it returns: pre-quote questions, measuring method, key facts, brand language, and sales handoff criteria. It also distinguishes itself from the quote tools by routing forward to them, so an agent knows this is the entry point rather than a quoting tool.

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?

"Call this FIRST whenever someone asks what a pergola costs, how big or tall it should be, or which style suits their home" gives explicit trigger conditions, and "Then call the matching quote tool" supplies the follow-on step. Both when-to-use and sequencing are stated outright rather than inferred.

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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