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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

A3.8/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive. The description adds useful behavioral context by noting the output is Markdown-formatted and lists the fields returned (name, locales, per-store ids, creation/edit times), exceeding what structured metadata alone provides.

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?

A single front-loaded, information-dense sentence. It opens with the core action, then the result format, with no filler or redundant explanation.

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?

For a low-complexity tool with one parameter and an existing output schema, the description together with annotations and schema covers the essential behavior. It could be slightly more complete by explicitly steering the agent to list_apps, but nothing crucial is missing.

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% and the only parameter appId already includes a meaningful description ('App id (uuid)'). The description doesn't need to add parameter semantics, so a baseline score of 3 is appropriate.

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 ('Fetch'), a resource ('a single Appskyline app'), and the selection criterion ('by id'). It is clearly distinct from list-style siblings like list_apps, though it doesn't name any alternative.

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 context is clear for a direct single-app lookup, and the phrase 'single ... by id' implies when to use it, but no explicit alternatives or exclusions such as list_apps are mentioned. Guidance is implied rather than fully spelled out.

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 cleanly split by entity: apps, keyords, store listing, reviews, search. Potential confusion exists between get_store_isting and get_store_metadata, and show_app_overview vs list_keywords, but the descriptions are sufficiently specific to guide selection.

Naming Consistency4/5

The set uses lowercase snake_case verb_noun patterns, with get_X for single resources, list_X for collections, add_keyword, search_store_results, and show_app_overview. The mixture of show/get is minor inconsistency, and list_google_play_reviews is a nice exception, but overall it's cohesive.

Tool Count5/5

The domain is built around app tracking, keyword research, store data, and engagement, and 13-14 tools is well within the sweet spot. Few tools feel obviously redundant, and each covers a distinct part of the ASO workflow.

Completeness3/5

The core read/query workflows are covered: list apps, list keywords, get rankings/history/volume, fetch store listing/metadata, and search. However, add_keyword is the only keyword mutator — there is no delete_keyword or update_keyword — creating a real dead-end for tracked-keyword management. Also review coverage is limited to Google Play alone.

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