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by app.trysonar

Analyze Competitors (AI)

sonar_analyze_competitors

WRITE tool — generates a fresh AI competitive insight for one of your own apps: clusters the keyword gaps vs your competitors into named opportunity themes (with a why-now narrative and per-keyword metrics), writes threat narratives for competitors climbing on your keywords, and diffs against the previous analysis. At most one analysis per app per 7 days (429 with the next available time while in cooldown — use sonar_competitor_landscape to read the current one). Requires a paid (non-trial) Indie plan and an API key with the write scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_idYesSonar app UUID of YOUR OWN tracked app to analyze. NOT a store id, NOT a competitor id.

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint=false, but the description goes further by labeling the tool 'WRITE tool', detailing the generation/diff behavior, the 7-day cooldown, rate-limiting (429), and access requirements (paid plan, write scope). This adds significant context beyond the annotations without contradicting them.

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?

The description is dense but not overly long, front-loading the 'WRITE tool' label and core function. Each sentence adds value: generation, clustering, narratives, diff, rate limit, alternative tool, and requirements. It could be slightly more streamlined, but it's well-structured and scannable.

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 the absence of an output schema, the description does well by summarizing what the tool produces (themes, narratives, diff) and covering rate limits, alternatives, and prerequisites. It doesn't specify the exact return format, but it's sufficient for a complex generative tool with a clear usage pattern.

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?

The single parameter app_id is fully described in the schema (including that it must be your own tracked app, not a store or competitor ID). The description reinforces this 'your own apps' requirement but does not add new semantic details beyond the schema, so it meets the baseline for 100% schema coverage.

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 generates a fresh AI competitive insight for your own app, clustering keyword gaps into opportunity themes, writing threat narratives, and diffing against previous analysis. It distinguishes itself from the sibling tool sonar_competitor_landscape by explicitly contrasting read vs. write behavior.

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

Usage Guidelines5/5

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

Explicitly provides when to use: at most one analysis per app per 7 days, and directs users to sonar_competitor_landscape to read the current analysis. Also outlines prerequisites (paid Indie plan, write-scope API key) and the 429 cooldown behavior, giving clear guidance on alternatives and constraints.

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