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IA-QA — 152 QA & Dev Tools for AI Agents

by io.github.JcJamet
OverviewDiscussionsAdmin

generate_json_ld

Read-onlyIdempotent

Generate a ready-to-paste snippet for GEO / structured data optimization. Supported types: WebSite, FAQPage, Article, Person, Organization, SoftwareApplication, HowTo.

Input Schema

NameRequiredDescriptionDefault
typeYesSchema @type: "WebSite", "FAQPage", "Article", "Person", "Organization", "SoftwareApplication", "HowTo"
fieldsNoSchema fields as key-value pairs (name, url, description, author, datePublished, etc.)
faq_itemsNoFor FAQPage/HowTo: array of { question, answer } objects

Output Schema

NameRequiredDescriptionDefault
nameNo
schemaNo
snippetNo
acceptedAnswerNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "faq_items": [
+      {
+        "answer": "A.",
+        "question": "Q?"
+      }
+    ],
+    "type": "FAQPage"
+  }
+]
  2. Changed1 schema field changed
    • addedOutput schema / properties
      Added value: +{
+  "acceptedAnswer": {
+    "type": "object"
+  },
+  "name": {
+    "type": "string"
+  },
+  "schema": {},
+  "snippet": {
+    "type": "string"
+  }
+}
  3. Changed1 schema field changed
    • addedInput schema / properties / fields / additionalProperties
      Added value: +true
  4. Changed1 schema field changed
    • addedInput schema / properties / faq_items / items
      Added value: +{
+  "properties": {
+    "answer": {
+      "type": "string"
+    },
+    "question": {
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  5. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}
  6. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the generator's safety profile is known. The description adds that output is a 'ready-to-paste' snippet (return-format context), but doesn't say whether output is validated against schema.org or how missing/unsupported fields are handled.

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 tightly-packed sentences with the action and output form front-loaded, followed by the supported-type list. No filler.

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?

With an output schema present and 100% parameter coverage, the description only needs to frame purpose and supported types, which it does. Complete enough for an agent to call correctly, with minor room for noting type-to-parameter mapping (e.g., faq_items only for FAQPage/HowTo).

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 applies. The description repeats the supported type values that the schema already enumerates for the 'type' parameter, adding no new semantics for 'fields' or 'faq_items' beyond what the schema documents.

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?

States a specific verb (Generate) and resource (ready-to-paste JSON-LD script snippet) plus the domain purpose (GEO/structured data optimization). An agent can immediately tell it produces structured-data markup, though it doesn't distinguish itself from nearby generators like json_schema_generate.

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 phrase 'for GEO / structured data optimization' implies when to use it, but there are no explicit conditions, exclusions, or named alternatives among the many sibling generators. Usage is inferrable rather than stated.

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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