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Run a niche analysis

run_niche_analysis

Analyze a niche to discover keywords, cluster sub-niches, and score opportunities, returning app concept suggestions.

Instructions

Run a niche analysis on a topic: discovers relevant keywords, clusters them into sub-niches, and scores each cluster's opportunity. Returns clusters with their keywords, opportunity scores, intent type, and an app concept suggestion. Cache hits (recent identical analyses, less than 7 days old) are returned instantly without consuming the niche analysis quota. Fresh analyses can take a few minutes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langYesBCP-47 language-region code (e.g., en-US, fr-FR, de-DE)
storeYesApp store: GPLAY (Google Play) or ITUNES (App Store)
topicYesNiche topic to analyze (2-100 characters, e.g. "meditation")
countryYesISO country code (e.g., US, FR, DE)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.6.1
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv1.4.0

TDQS

A4/5.0
Behavior4/5

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

Annotations give the safety profile (readOnlyHint false, openWorldHint true, non-idempotent, non-destructive), and the description adds genuinely new behavioral context: quota consumption on cache miss, instant cache hits, and multi-minute latency. It stops short of describing auth/permission requirements or what happens on partial failure.

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?

Three sentences, front-loaded with the action, then the result shape, then the cost/caching notes. Efficient, though the opening 'Run a niche analysis on a topic' partially restates the title before adding new information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description compensates by enumerating what is returned (clusters, keywords, opportunity scores, intent type, app concept suggestion). Combined with the latency and quota notes, an agent has everything needed to call this correctly.

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 all four parameters (topic, store, country, lang) are already fully documented in the schema, including the enum for store. The description contributes no additional parameter semantics, so the baseline of 3 applies.

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?

States a specific verb (run) and resource (niche analysis on a topic) and unpacks the internal workflow: keyword discovery, clustering into sub-niches, opportunity scoring. It is clearly distinguishable from the sibling list_niche_analyses, which merely reads history.

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?

It discloses quota consumption, caching (identical analyses under 7 days return instantly), and latency (a few minutes), which helps an agent decide whether the call is cheap. However, it never names when to prefer this over siblings like list_niche_analyses or run_autocomplete, so usage is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.