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Mobbin

by com.mobbin

Search Flows

search_flows
Read-only

Search Mobbin for multi-step user flows (e.g. onboarding, checkout) using natural language. Returns evenly-spaced preview images inline along with metadata for each flow, including per-screen previews. Examine the returned images to understand each flow's actual content — do not describe screens based solely on metadata. On hosts that support MCP Apps, also renders an interactive gallery of the results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for paginating through results. Maximum 20.
limitNoMaximum number of flows to return. Lower limits are recommended to manage context size.
queryYesDescribe one user journey in plain language — the steps and what you'd see along the way. Be specific; detail helps. Good: "onboarding with personalization steps", "checkout with payment method selection". Avoid: combining multiple flows (search separately), negations, vague style words, disconnected keyword lists. Name a specific app to filter results to it (e.g. "Duolingo onboarding"). Do not include platform (ios/web) — use the dedicated parameter.
platformYesPlatform to search.
task_intentNoOne short sentence summarizing the user's overall task. Helps return more relevant results. Write it in English even when the conversation is in another language. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data.
image_formatNoImage format. Use jpg if your client does not support webp.webp

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYes1-based page number of search results.
flowsYes
queryYesThe natural language query used for this search.
has_next_pageYesWhether more pages of results are available.

TDQS

A4.3/5.0
Behavior5/5

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

The description adds meaningful behavioral context beyond the readOnlyHint annotation: it discloses that results include inline evenly-spaced preview images, metadata, per-screen previews, and an interactive gallery on MCP Apps. It also instructs the agent to examine images rather than rely solely on metadata, which is valuable operational guidance.

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 concise and front-loaded with the core action, then adds only high-value behavior and usage details. Every sentence earns its place.

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 description, combined with the rich schema and output schema, gives an agent everything needed to call the tool correctly. It covers what the tool does, how results are returned, how to interpret them, and platform-specific gallery behavior.

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?

With 100% schema description coverage, the schema already documents every parameter thoroughly, including guidance for query, platform, page, limit, task_intent, and image_format. The tool description itself adds no parameter-specific semantics beyond what the schema provides.

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 action ('Search Mobbin for multi-step user flows') with concrete examples like onboarding and checkout, and clearly frames the tool as a flow-focused search rather than a screen or section search. This distinguishes it from the sibling tools search_screens and search_sections.

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 — when looking for multi-step flows — but it never explicitly contrasts it with search_screens or search_sections. The query guidance in the schema adds helpful do's and don'ts, but no direct 'use this instead of X' guidance is present.

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

A4.4/5.0
Disambiguation5/5

Each tool searches a distinct content type—flows, screens, and sections—so an agent can clearly choose based on what kind of result is needed. The entity types are separate enough that there is no meaningful overlap or ambiguity.

Naming Consistency5/5

All three tools follow the exact same search_<plural-noun> pattern. This is a perfectly consistent and predictable naming convention.

Tool Count5/5

Three tools is well-scoped for a search-only server. Each tool covers one core Mobbin content category, and none feel redundant or unnecessary.

Completeness5/5

The server's apparent purpose is to search Mobbin's design content, and it covers the three primary content types: flows, screens, and sections. There are no obvious missing operations for this read-only search domain.

Resources