aso-audit-mcp

Optimize the iOS keyword field

keyword_field_check

Optimize iOS keyword fields by removing duplicate terms and excess spaces, then report characters saved and remaining capacity.

Instructions

Clean up an iOS 100-character keyword field: remove spaces after commas, de-duplicate terms, and report characters saved and capacity remaining. Built by asoagency.io.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "keywords": "<keywords>"
    },
    "name": "keyword_field_check"
  }
}

Input Schema

Name	Required	Description	Default
`keywords`	Yes	The comma-separated iOS keywords field to optimize.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 9, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations provided, the description carries full burden. It lists the transformations (remove spaces, de-duplicate) and reporting, but does not clarify if the tool modifies data permanently or returns only a report. The behavioral scope is partially disclosed.

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 sentences, 20 words, with no filler. The action is front-loaded ('Clean up') and every sentence provides essential information. Highly efficient.

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 single-parameter tool with no output schema, the description adequately covers input format, operations, and output (report on savings). Minor non-essential detail (vendor name) does not detract. Completeness is high for the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description covers 100% of the parameters but is minimal ('The comma-separated iOS keywords field to optimize'). The tool description adds significant meaning by detailing the cleaning and reporting operations, going beyond what the schema 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 uses a specific verb ('Clean up') and clearly identifies the resource ('iOS 100-character keyword field') along with concrete actions (remove spaces after commas, de-duplicate terms, report savings). This distinguishes it well from sibling tools like 'audit_metadata' or 'check_field'.

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 usage for optimizing iOS keyword fields but does not explicitly state when to avoid using it or mention alternative tools. The context is clear but lacks explicit exclusionary guidance.

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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