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Get app

get_app
Read-onlyIdempotent

Fetch a single Appskyline app by id. Returns the app metadata formatted as Markdown (name, locales, per-store ids, creation/edit times).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appIdYesApp id (uuid)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
appYes
statusYes

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by disclosing the return format (Markdown) and the fields included (name, locales, per-store ids, creation/edit times), which is useful and not contradictory to the annotations.

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?

One sentence with no filler, front-loaded with the core action first, then concise return details. Every word contributes value.

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?

This is a simple get-by-id tool with comprehensive annotations, full parameter documentation, and an output schema present. The description covers the purpose, scope, and return representation, so an agent has enough to invoke this tool 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?

The input schema already describes the single parameter (appId) with 'App id (uuid)', and schema coverage is 100%. The description's 'by id' wording reinforces but does not add new semantic information beyond the schema. Baseline 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 ('Fetch'), a precise resource ('a single Appskyline app'), and the lookup key ('by id'). It clearly distinguishes from sibling tools that list, summarize, or analyze apps, so an agent can identify what this tool does without ambiguity.

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

Usage Guidelines4/5

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

The description makes the use case clear: retrieve one app's metadata by app ID. It does not explicitly exclude alternatives like list_apps or show_app_overview, but the singular-by-id framing provides sufficient context for when to choose this tool.

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