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Inspect a keyword

inspect_keyword

Analyze any App Store or Google Play keyword, tracked or not, to get difficulty, traffic, KEI scores, top 20 ranking apps, related suggestions, and tracking status.

Instructions

Deep-analyze any keyword (even ones you don't track). Returns difficulty_score (0-100), traffic_score (0-100), KEI with score and level (e.g. "good"), the top 20 apps currently ranking for it (with rank, app_id, title, icon, genre, rating), related keyword suggestions from search and keyword sources, and whether you already track this keyword. Inspecting a keyword you already track does not consume the inspection quota.

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)
countryYesISO country code (e.g., US, FR, DE)
keywordYesThe keyword to analyze

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

A3.5/5.0
Behavior4/5

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

The annotations declare readOnlyHint=false and openWorldHint=true, and the description adds important behavioral context: inspection can consume an inspection quota, unless the keyword is already tracked. It also enumerates the returned data, which is necessary because no output schema exists. It does not discuss permissions or idempotency, so it is not exhaustive.

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 purpose is front-loaded, and the two sentences are dense but mostly earn their place because the tool has no output schema and needs to advertise its return fields. The return-value list is long, but it is useful for agent selection and invocation.

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 thoroughly explains what the tool returns and includes the important quota nuance. It is largely complete for an agent to call it correctly, though it does not address when to prefer it over sibling tools, which is a usage-guideline gap rather than a completeness failure.

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 baseline is 3. The description adds only marginal semantic detail by implying that the keyword parameter can refer to an untracked keyword, but it does not explain store, country, or lang beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Deep-analyze any keyword (even ones you don't track).' The scope is clear, including that the keyword need not be tracked. It does not explicitly differentiate this tool from sibling analysis tools like run_niche_analysis or run_autocomplete, so it falls short of a 5.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance, and no named alternatives. The note about tracked keywords and quota is contextual but does not tell the agent when this tool should be selected over siblings such as run_autocomplete or list_keyword_inspections.

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