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dbonomo
by dbonomo

store_search

Search Pebble store listings by keyword, ranking apps based on matches in titles, authors, and descriptions.

Instructions

Search the store by keyword — CLIENT-SIDE, with real limits.

The live appstore API has NO search endpoint, so this does not do a true full-text search. Instead it fetches a bounded candidate pool from the relevant store listings (the all and most-loved collections for type_string, paged up to a few hundred apps) and ranks them by case-insensitive substring/token matches on each app's title, author, and description. Results carry a score.

Consequences to keep in mind:

  • Coverage is only what those listings return: an obscure app outside the all/most-loved pool can be missed entirely.

  • It matches on stored listing text, not on-device behavior or tags.

  • type_string must be one of apps, watchapps-and-companions, faces, watchfaces. For an exact app you already know, prefer store_app by id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
hardwareNoemery
max_resultsNo
type_stringNowatchfaces

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description carries the full burden and does exceptionally well. It discloses that it is client-side, fetches a bounded pool, ranks by substring/token matches, returns a score, and has coverage limitations. It even warns that matching is on listing text, not behavior or tags.

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 front-loaded with the core purpose, uses a clear 'Consequences' list for limitations, and ends with a practical alternative pointer. Every sentence adds value; no fluff. It's appropriately structured for a tool with behavioral caveats.

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 tool is complex (client-side search with real constraints), and the description addresses all critical context: algorithm, coverage limits, `type_string` constraints, and alternative tool. Since an output schema exists, return values need no explanation. This is a complete, self-sufficient description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must add meaning. It explains `query` as the keyword, `type_string` allowed values, and the ranking algorithm. It doesn't explicitly describe `hardware` or `max_results`, but the parameter names and defaults offer some clarity. Overall, it compensates well beyond the bare schema.

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 opens with 'Search the store by keyword' — a specific verb and resource. It clearly distinguishes itself from sibling tools by explicitly stating 'For an exact app you already know, prefer ``store_app`` by id.' It also clarifies the client-side approach and limitations.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance: it's the keyword search option, while `store_app` is the exact-id alternative. It also explains when not to rely on it (obscure apps outside the bounded pool) and outlines real limits, so the agent can decide accordingly.

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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