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Search app-store results

search_store_results
Read-onlyIdempotent

Run a live ranked search against the iOS App Store, macOS App Store, Google Play, or Microsoft Store via Appskyline without storing a search snapshot. Returns a Markdown table of rank, id, title, score, and developer for each result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numNoNumber of results to return (default depends on store)
langNoTwo-letter language code (e.g. en, it)
termYesSearch term
storeYesWhich store to search
countryNoTwo-letter country code (e.g. US, IT)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
langYes
termYes
storeYes
statusYes
countryYes
resultsYes
truncatedYes

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, idempotentHint=true, and openWorldHint=true. The description adds valuable context beyond these: the search is live, results are not saved as a snapshot, and the output is a Markdown table with specific fields. This makes the behavior understandable without contradicting 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?

The description is two well-structured sentences. The core behavior, scope, major constraint, and return format are all front-loaded with no filler or repetition of schema/annotation details.

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?

For a read-only, idempotent search tool with a full input schema and an output schema, the description covers what the tool does, which stores it queries, the live behavior, and the response shape. There are no significant gaps that would prevent correct invocation or result interpretation.

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 of 3 applies. The description does not add new semantics for store, term, num, lang, or country beyond what the schema already states, but it does clarify the output format (rank, id, title, score, developer), which gives some context for what parameters influence.

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 ('Run'), a precise resource ('live ranked search'), the four stores supported, and the key constraint ('without storing a search snapshot'). This clearly distinguishes it from sibling tools like get_keyword_rank or list_apps, so an agent can tell what it does without inspecting the schema.

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 gives useful context: it is a live, ranked, non-persisting search across four named stores. The phrase 'without storing a search snapshot' implicitly tells agents not to use this for historical keyword-rank lookups, but it does not explicitly name alternatives or state when-not-to-use conditions.

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