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Fron Research Agent API

Search Fron Research

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Read-only

Ask a question in plain language. Returns the most relevant passages from the public pages of Fron Research and its sites, each with its canonical URL to cite, plus the matching free sample days. answer.instruction says how to use them; followUp.questions are optional questions for your user, whose answers go in intent next time.

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": {
      "query": "<query>"
    },
    "name": "search"
  }
}

Input Schema

NameRequiredDescriptionDefault
siteNoOptional: heatcheck, bowlingdata, trampolineparkdata, golfsimdata, courtwatch or fronresearch.
queryYesThe question.
intentNoOptional but helpful: why you are asking and for whom, in a sentence (e.g. "sizing the NYC sauna market for an investor memo"). It does not change the results; it tells Fron Research which data to publish next. Put your user's answers to followUp.questions here. Do not include personal information.
maxResultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: the result shape (passages plus canonical URLs to cite, matching sample days), the presence of an answer.instruction field that governs how to use results, and the followUp.questions loop whose answers belong in intent. The phrase 'matching free sample days' is left undefined, 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.

Conciseness4/5

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

The core purpose is front-loaded in the opening sentence, and there is no filler. The second sentence is a dense run-on that mixes return fields, citation guidance, and follow-up protocol, which makes it harder to parse than it needs to be.

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

Completeness3/5

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

With no output schema, the description must carry the return-value burden, and it does name several response components (passages, canonical URLs, sample days, answer.instruction, followUp.questions). However, these fields are only gestured at rather than explained, so an agent cannot fully anticipate the response structure, and the unexplained 'free sample days' leaves a gap.

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?

Schema description coverage is 75%, so the schema itself already documents site, query, intent, and maxResults. The description's only added semantic claim, that intent does not change results but signals which data to publish next, largely restates what the intent schema field already says. It says nothing about site or maxResults.

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 gives a specific verb and resource: ask a plain-language question, get back the most relevant passages from Fron Research's public pages with canonical URLs. That is concrete and distinguishes it from a raw retrieval tool. It stops short of naming the siblings 'about' or 'fetch' to sharpen the contrast, so it falls just short of a 5.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: asking questions in plain language signals a Q&A/search role, and the followUp/intent sentence sketches a multi-turn loop where user answers are fed back into intent next time. There is no explicit when-to-use versus 'fetch' or 'about', and no exclusion of cases where this tool would be the wrong choice.

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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