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MCP Tool-Definition Linter & Annotation Designer

lint_mcp_tool_definition
Read-onlyIdempotent

Validate an MCP tool definition against JSON Schema 2020-12 and current naming, output-schema, and annotation rules; returns findings, a conformance score, and a recommended annotation set. Use when a developer wants to check an MCP tool definition before publishing. Renders the interactive AINumbers tool as a widget; inputs are applied via the AIN Bridge and the tool runs client-side (zero PII, zero network). Output schema: call describe_tool("lint_mcp_tool_definition").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNoMap of tool input element IDs to values (see manifest input_schema). Applied via AIN Bridge prefill.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "annotations": {
-      "type": "object"
-    },
-    "findings": {
-      "items": {
-        "type": "object"
-      },
-      "type": "array"
-    },
-    "score": {
-      "type": "number"
-    }
-  },
-  "type": "object"
-}New value: +null
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "annotations": {
+      "type": "object"
+    },
+    "findings": {
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "score": {
+      "type": "number"
+    }
+  },
+  "type": "object"
+}
  3. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds substantial behavioral context: the tool renders an interactive widget, applies inputs via AIN Bridge, and runs client-side with zero PII and zero network. This goes well beyond what annotations provide and makes execution expectations clear.

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?

Three sentences, with purpose front-loaded, followed by usage trigger and behavioral execution details. Every sentence earns its place; there is no filler, and the output-schema pointer is compact.

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 no output schema, the description helpfully states the return items (findings, conformance score, recommended annotation set) and points to describe_tool for the output schema. It could describe the structure of findings in more detail, but for selection and invocation the definition is complete enough.

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% for the single parameter, so the baseline is 3. The description repeats the AIN Bridge prefill mechanism and points to the manifest input_schema, but it does not enumerate the dynamic input element IDs. It adds some context without substantially exceeding what the schema already documents.

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 opens with a specific verb ('Validate'), a precise resource ('an MCP tool definition'), and the standards applied (JSON Schema 2020-12, naming, output-schema, annotation rules). It names concrete return artifacts (findings, conformance score, recommended annotation set), which clearly distinguishes it from sibling linters like lint_mcp_server_conformance.

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

Usage Guidelines4/5

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

The description gives an explicit trigger: 'Use when a developer wants to check an MCP tool definition before publishing.' It does not mention when not to use it or name alternative linters, so it falls just short of a 5.

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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