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AppFactory

by gbatistuta0
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Python
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ASO Niche Score

aso_niche_score
Read-onlyIdempotent

Score an app idea 0-100 on demand, competitor weakness, saturation, and monetization to get a quick go/no-go verdict for ranking ideas.

Instructions

Score an idea 0-100 from demand, competitor weakness, saturation and monetization, with a go/no-go verdict.

Use when: ranking one idea quickly. For the full evidence bundle use idea_evaluate. verdict: GO (>=60), MAYBE (>=40), WEAK, REJECT (median competitor >50k ratings or no demand). Returns: {ok, score, verdict, demand, competitors, ...} (untrusted_content).

Input Schema

NameRequiredDescriptionDefault
termYesSearch term or seed keyword, e.g. 'habit tracker'.
genreNoApp Store category name (e.g. 'photo_video', 'productivity', 'health') or numeric genre id; omit for all/inferred.
countryNoTwo-letter App Store storefront code, lowercase, e.g. 'us', 'gb', 'de'.us

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.1.5
    • addedInput schema / properties / country / description
      Added value: +"Two-letter App Store storefront code, lowercase, e.g. 'us', 'gb', 'de'."
    • addedInput schema / properties / genre / description
      Added value: +"App Store category name (e.g. 'photo_video', 'productivity', 'health') or numeric genre id; omit for all/inferred."
    • addedInput schema / properties / term / description
      Added value: +"Search term or seed keyword, e.g. 'habit tracker'."
  2. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), but the description adds real behavioral value the annotations cannot: the verdict thresholds (GO >=60, MAYBE >=40, WEAK, REJECT conditions) and the untrusted_content flag on output. It omits any latency/cost or source-of-data context, so it is strong rather than complete.

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 short, front-loaded chunks: what it does, when to use it vs the sibling, and the verdict logic. Every sentence earns its place with no filler.

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?

An output schema exists, yet the description still restates the return shape, which is mildly redundant but harmless. The verdict thresholds and untrusted-content warning are useful additions that make the definition callable with confidence; only minor gaps (e.g., what 'demand'/'competitors' contain) remain.

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 fully documents term, genre, and country. The description only implicitly echoes the 'idea' input and adds no syntax, format, or default guidance beyond the schema, so baseline 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 and resource ('Score an idea 0-100') plus the exact scoring dimensions (demand, competitor weakness, saturation, monetization) and a verdict output. It explicitly differentiates itself from the sibling idea_evaluate, so an agent can pick it without opening either schema.

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?

'Use when: ranking one idea quickly. For the full evidence bundle use idea_evaluate' gives both the condition for use and the named alternative with its selecting condition. Nothing is left to inference.

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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