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

llm_output_validator

Read-onlyIdempotent

Validate an LLM response against QA criteria: format checks (JSON, code, markdown), content rules (must-include, must-not-include), length constraints, language detection, and safety patterns. Essential for QA testing LLM-powered features.

Input Schema

Name	Required	Description
`output`	Yes	The LLM output text to validate
`max_length`	No	Maximum character length for the output
`min_length`	No	Minimum character length for the output
`check_safety`	No	Check for PII patterns (emails, phones, SSN), profanity signals, and prompt leakage
`must_include`	No	Comma-separated strings that MUST appear in the output
`expected_format`	No	Expected output format
`must_not_include`	No	Comma-separated strings that must NOT appear (e.g. "TODO, FIXME, undefined, NaN")
`check_json_schema`	No	If expected_format is JSON, provide required keys as comma-separated list to validate the structure
`expected_language`	No	Expected language of the output (en, fr, es, de…). Checks for common words.

Output Schema

Name	Required	Description	Default
`total`	No
`checks`	No
`failed`	No
`passed`	No
`verdict`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 31, 2026

addedInput schema / examples

Added value: +[
+  {
+    "expected_format": "json",
+    "must_include": "a",
+    "must_not_include": "TODO",
+    "output": "{\"a\":1}"
+  }
+]

Changed1 schema field changedJul 7, 2026

changedInput schema / properties / expected_language / description

Previous value: -"Expected language of the output (en, fr, es, deâ€¦). Checks for common words."New value: +"Expected language of the output (en, fr, es, de…). Checks for common words."

Changed1 schema field changedJun 21, 2026

addedOutput schema / properties

Added value: +{
+  "checks": {},
+  "failed": {},
+  "passed": {},
+  "total": {
+    "type": "number"
+  },
+  "verdict": {}
+}

Changed1 schema field changedJun 10, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}

First observedMay 26, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description adds useful scope detail (that it checks safety patterns and language detection) but says nothing about failure behavior — whether it stops at the first failed check, returns per-check results, or how severity is reported.

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?

Two dense sentences, front-loaded with the verb and the resource, followed by a compact capability list. The closing 'Essential for QA testing' sentence is somewhat promotional filler but does establish context, so it only mildly dilutes.

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, return values need not be explained, and annotations cover the read-only/idempotent profile. The description accounts for all nine parameters at a category level and is adequate for calling the tool, though it omits failure semantics and sibling differentiation.

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% and every parameter carries its own description, including the comma-separated semantics of must_include and must_not_include and the enum for expected_format. The description merely echoes those categories at a high level, adding no syntax or interaction details (e.g. how check_json_schema relates to expected_format) beyond the schema.

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 and resource ('Validate an LLM response') and enumerates the check families it covers: format, content rules, length, language, and safety. However, it never distinguishes itself from very close siblings such as llm_format_check, llm_json_schema_check, or response_quality_score, so an agent cannot tell which of these to reach for.

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?

'Essential for QA testing LLM-powered features' implies the context of use but gives no explicit when-to-use/when-not, no prerequisites, and no named alternatives. With several overlapping validator tools in the sibling list, this leaves routing to inference.

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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