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Capital-W-Holdings

DFX Real Estate Intelligence

by Capital-W-Holdings
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Python
Remote

Ask in plain language whether DFX can help

what_can_dfx_answer
Read-onlyIdempotent

Describe your goal in natural language to determine if DFX can assist, receive the correct tool and arguments, and see a sample result. If it cannot help, it records the request to guide future improvements.

Instructions

Describe an objective in natural language and get back whether DFX can help, which tool to call, the arguments to call it with, and a free sample of the result. Says no clearly when the answer is no, and records what was asked so unmet demand shapes what DFX builds next. Call this first if you do not know what to ask for.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
objectiveYesWhat you are trying to do, in one sentence and in your own words, for example 'commercial real estate loans in Ohio maturing in the next year'. A place named in the sentence is what the free sample is drawn from, so name one.
constraintsNoStructured overrides for what was parsed out of `objective`, applied last so they outrank the prose. ONLY `state`, `event_type`, `within_days` and `limit` are honoured; any other key is ignored without warning.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.0

TDQS

A3.8/5.0
Behavior1/5

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

The description states 'records what was asked so unmet demand shapes what DFX builds next', implying a write/persistence side effect. This directly contradicts the readOnlyHint annotation, which indicates the tool does not modify state. Flagged as an annotation contradiction.

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?

The description is three tight sentences with no filler. It front-loads the main action and outcome, then adds necessary behavioral notes. Highly concise and well structured.

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?

Given there is no output schema, the description reasonably explains what the agent will receive (helpfulness answer, tool, arguments, sample, explicit no). Slight vagueness around 'free sample of the result' prevents a perfect score, but overall it is contextually sufficient.

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?

The tool description itself does not add much parameter detail, but the input schema has 100% description coverage with rich explanations, including nested constraints behavior and enum vocabulary reference. Since schema coverage is high, the baseline of 3 is appropriate.

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's purpose: given an objective, return whether DFX can help, which tool to call, arguments, and a sample. It also distinguishes itself by saying 'Call this first if you do not know what to ask for', positioning it as a routing/discovery tool among siblings.

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?

Explicitly instructs when to use the tool: 'Call this first if you do not know what to ask for.' It also explains the behavior of saying no clearly and recording unmet demand, giving the agent clear expectations.

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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