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by com.interzoid
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interzoid_custom_data

Read-onlyIdempotent

AI Custom, Self-Defined Data Enrichment. Define your own data API: describe a topic, provide a lookup value, and specify the output fields you want. Returns real-world data as a JSON object with your self-defined fields. Example: topic='detailed information about companies', lookup='IBM', output='["headquarters","ceo","website"]'. Premium API, cost varies by model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoAI model to use (optional: 'default', 'model-a', 'model-a-premium', 'model-x')default
topicYesDescription of the data domain (e.g. 'detailed information about companies', 'healthcare data by city')
lookupYesThe lookup value to retrieve data for (e.g. 'IBM', 'Las Vegas', '85250')
outputYesJSON array of desired output field names (e.g. '["headquarters","ceo","website"]')

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • addedInput schema / properties / lookup / examples
      Added value: +[
+  "IBM"
+]
    • addedInput schema / properties / model / default
      Added value: +"default"
    • addedInput schema / properties / model / enum
      Added value: +[
+  "default",
+  "model-a",
+  "model-a-premium",
+  "model-x"
+]
    • addedInput schema / properties / model / examples
      Added value: +[
+  "default"
+]
    • addedInput schema / properties / output / examples
      Added value: +[
+  "[\"headquarters\",\"ceo\",\"website\"]"
+]
    • addedInput schema / properties / topic / examples
      Added value: +[
+  "detailed information about companies"
+]
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the bar is lower. The description adds useful context beyond the annotations: it is a premium API, cost varies by model, and results are returned as a JSON object with self-defined fields. There is no contradiction with the annotations.

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 description is compact, front-loaded with purpose, and includes a concrete example and cost caveat. There is minor redundancy among 'Custom, Self-Defined,' 'Define your own,' and 'self-defined fields,' but every sentence contributes.

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?

For a 4-parameter tool with no output schema, it explains the data flow, gives a usable example, and warns about premium cost and model variability. Remaining gaps such as error handling and absent-field behavior are partially covered by the openWorldHint and the tool's self-describing output.

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 100%, so the baseline is 3. The description's example mirrors the schema's own examples and adds little new meaning about the parameters or their interaction beyond what the schema already provides.

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 identifies the action and resource: define your own data API by supplying topic, lookup, and output fields, and receive real-world data as a JSON object. It also separates this tool from the many specialized Interzoid siblings by emphasizing self-defined/custom behavior.

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?

The description implies when to use it—for flexible, self-defined data enrichment—but it does not explicitly name alternatives or state when not to use it. Given the large sibling set, explicit routing guidance would improve the definition.

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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