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Get keyword rank

get_keyword_rank
Read-onlyIdempotent

Look up the current ranking of a specific Appskyline app for a keyword in a given store + country. Returns "App X ranks #N of M" or "not in top N" if the app does not appear in the scanned results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numNoHow many results to scan when looking for the app (default 50, max 200)
langNoTwo-letter language code (e.g. en, it)
termYesSearch term
appIdYesAppskyline app id
storeYesWhich store to check
countryNoTwo-letter country code (e.g. US, IT)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
appYes
langYes
rankYes
termYes
storeYes
statusYes
countryYes
resultsScannedYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive behavior, so the description does not need to repeat that. It adds meaningful behavioral context by clarifying that the result is limited to the scanned substring of top results and by defining the exact output phrasing, including the 'not in top N' case.

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 a single tightly written two-sentence passage. It front-loads the core purpose and then gives an exact output format example. There is no fluff or repetition of schema fields.

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?

The behavior is fully specified for an agent: the lookup scope is clear, the result interpretation is provided, and annotations cover safety. The existing input schema and output schema allow a new agent to call this tool without ambiguity. No extra edge cases seem material enough to require mention.

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 coverage is 100%, and each parameter has a description. The tool description adds value by explaining the output in terms of 'scanned results', but it does not add substantial parameter-level semantics beyond the schema; the 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 states a specific verb ('Look up'), a precise resource (current keyword ranking of a specific app), and the exact scope (store and country). It also distinguishes itself from sibling tools like get_keyword_history or get_keyword_overview by calling out 'current' ranking and the output format, so the agent can select it appropriately.

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 implies when to use the tool — checking a current ranking for a keyword — but it does not explicitly name alternatives or state when not to use it. The sibling list is not referenced in the description, leaving the agent to infer the distinction between current ranking and related get_keyword_overview/get_keyword_history tools.

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

A4.1/5.0
Disambiguation4/5

Most tools map to clearly distinct resources and actions, such as listing apps, getting keyword history, fetching store listings, and searching store results. A couple of adjacent getters, particularly show_app_overview vs get_app and get_store_metadata vs get_store_listing, could be confused, but their descriptions are strong enough to keep an agent on the right path.

Naming Consistency5/5

Tool names follow a uniform verb_noun pattern throughout: add_, delete_, get_, list_, search_, show_. Resources such as app, keyword, store, and overview are consistently placed after the verb, making the set predictable and easy to reason about.

Tool Count5/5

Fourteen tools serve the ASO and store-insight domain well without feeling bloated. The count covers app discovery, keyword tracking, store metadata, engagement summaries, live store search, and reviews, so each tool earns a place.

Completeness4/5

The core workflows are well covered: list apps, get app details, track and delete keywords, check current rank and historical rank, look up search volume and difficulty, read store listings, and pull Google Play reviews. Obvious gaps are an update-keyword operation and App Store review listing, but most primary use cases do not hit dead ends.

Resources