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search_assets

Find AI agents, skills, prompts, MCP connectors, and bundles from a curated marketplace. Search by query, filter by type or domain.

Instructions

Search the Spark AI assets marketplace. Returns matching agents, skills, prompts, MCP connectors, and bundles.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by asset type
limitNoNumber of results (1-50, default 10)
queryYesSearch query (title, description)
domainNoFilter by domain slug (e.g. 'development', 'marketing')
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses the return types but omits details like pagination, sorting, authorization requirements, or side effects, leaving gaps for an AI agent.

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 one sentence, front-loaded with the action and result, with no unnecessary words. Every part earns its place.

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 there is no output schema, the description could be more complete by mentioning the structure of results (e.g., names, descriptions, IDs). However, the listed asset types and the presence of a query parameter provide adequate context for a search tool.

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 each parameter is already documented. The description adds marginal value by stating the return types, but does not enhance parameter meaning beyond the 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 clearly states the verb 'Search' and the resource 'Spark AI assets marketplace', and enumerates the returned asset types (agents, skills, etc.), distinguishing it from siblings like get_asset (single asset) or list_categories.

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 usage for general searching but does not explicitly state when to use this vs. siblings like get_asset or list_popular, nor any exclusions or prerequisites.

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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