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HalidSaglam

saglitzdesign-mcp

by HalidSaglam

search_design_knowledge

Search a curated design knowledge base with natural language queries. Retrieve excerpts from expert resources on UI components, UX principles, copywriting, SEO, and design languages.

Instructions

Search the design knowledge base with a natural-language query. Covers web, iOS, Android and macOS design: UI components (buttons, forms, navigation…), UX principles, accessibility, typography, color, spacing, motion, conversion, copywriting, SEO, GEO (AI-search optimization), design languages (Material 3, Apple HIG/Liquid Glass, Fluent 2, iOS/macOS app design), expert craft standards, distilled classic design & marketing books (Norman, Krug, Refactoring UI, Cialdini, StoryBrand, Positioning, Hooked…), design-process roadmaps, and real-world patterns researched from top apps/sites (Mobbin). Returns the best-matching docs with the most relevant section excerpted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 5)
queryYesWhat you need guidance on, e.g. 'primary button size mobile', 'pricing page layout', 'dark mode colors', 'llms.txt'
categoryNoRestrict to one category
platformNoRestrict to one platform
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It only describes content scope and query examples, failing to mention that the tool is read-only (safe), what happens with no results, or any rate limits. The search verb implies reading but is not explicit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the primary action, but it is lengthy and verbose listing multiple topics, design languages, and books. It could be more concise while retaining key information.

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?

Given the tool has 4 parameters and no output schema, the description provides broad context about what the knowledge base covers (platforms, topics, etc.). It lacks details about return format or pagination, but for a search tool the scope explanation is reasonably complete.

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 coverage is 100% (all 4 parameters have descriptions). The description adds example queries and context about the knowledge base scope but does not significantly enhance parameter semantics beyond what the schema already provides. 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 clearly states 'Search the design knowledge base with a natural-language query' – specific verb and resource. It enumerates the covered topics, platforms, and design languages, distinguishing it from sibling tools like get_component_guidance or get_design_doc which target specific resources.

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 searching for design guidance but does not explicitly state when to use this tool vs siblings (e.g., for specific components vs open-ended queries). There are no exclusion criteria or context on preferred scenarios.

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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