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sonar

by app.trysonar

ASO Score

sonar_app_aso_score
Read-only

Calculate an ASO (App Store Optimization) audit score (0-100) for an app. Returns the overall score plus an itemized breakdown of checks (title length, keyword usage, screenshots, ratings, etc.) so you can identify what to improve. Works without an API key (free tier, limited daily use per IP).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
storeYesApp store. "ios" for Apple App Store, "android" for Google Play.
countryNoISO 3166-1 alpha-2 country code (e.g. "us", "gb", "de"). Default "us".us
store_idYesStore-specific app identifier. iOS: numeric track ID. Android: package name.

TDQS

A4/5.0
Behavior4/5

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

Annotations provide readOnlyHint=true, and the description adds behavioral context: it works without an API key, has a free tier, and daily usage limits per IP. This goes beyond the annotations. However, it does not disclose what happens on rate limit excess or whether external API calls are made, leaving some gaps.

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?

The description is two sentences: the first clearly states purpose and output, the second adds usage context. Every sentence is valuable, no wasted words, and the most important information is front-loaded.

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 simple read-only tool with three parameters and no output schema, the description adequately explains the return value (score plus itemized breakdown) and free tier usage constraints. It could mention error handling or rate limit specifics, but is largely complete for typical use.

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 schema already documents all three parameters (store, country, store_id) with descriptions. The description adds no additional semantics or syntax details beyond what the schema provides, so a baseline of 3 is appropriate.

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 states the tool calculates an ASO audit score (0-100) for an app and returns the overall score plus an itemized breakdown. It specifies the verb (calculate) and resource (app), and distinguishes from siblings by being the only scoring tool among many other sonar tools.

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 mentions it works without an API key with a free tier and limited daily use per IP, implying usage is free but rate-limited. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites. Usage is implied but not fully guided.

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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TDQS

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct action or data aspect within the ASO domain. Keyword-related tools are clearly separated by purpose (tracked keywords vs. research vs. suggestions vs. metrics), and competitive tools differentiate between reading landscape and generating new analysis. No two tools have overlapping functionality that would confuse an agent.

Naming Consistency3/5

Naming is a mix of verb-first (e.g., sonar_add_screenshot, sonar_create_product) and noun-first patterns (e.g., sonar_app_keywords, sonar_competitor_landscape). While all use snake_case and the 'sonar_' prefix is consistent, the lack of a uniform verb_noun structure makes it harder to predict tool names. The pattern is readable but inconsistent.

Tool Count2/5

With 47 tools, the server is over-scoped for a typical MCP server. Although the ASO domain is broad, many tools are granular (e.g., 10 screenshot tools, 10 keyword tools). This quantity exceeds the 25+ threshold for 'too many' as defined in the calibration, making it heavy for an agent to navigate comprehensively.

Completeness5/5

The tool surface covers the full ASO lifecycle: app discovery, keyword research, tracking and ranking, competitor analysis, revenue estimation, screenshot creation and export, alerts, and product management. There are no obvious gaps—every necessary operation for monitoring and optimizing app store presence is present, including both read and write actions.

Resources