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Spark - AI Assets Marketplace

List popular assets

list_popular
Read-onlyIdempotent

List the most popular Spark assets by download count, optionally filtered by type.

For when browsing without a text query; search_assets finds text matches. Returns numbered summaries with outcomes, price, tags and URLs, or 'No assets found.' Downloads measure acquisitions, not successful applications or ratings. Public catalog lookup, no login or download recorded.

For example, list_popular(type='skill', limit=5).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional asset type: agent, skill, prompt, prompt_chain, mcp_connector or bundle; omitted means all types.
limitNoMaximum results; clamped to 1-20, default 10.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / limit / description
      Previous value: -"Number of results (1-20, default 10)"New value: +"Maximum results; clamped to 1-20, default 10."
    • changedInput schema / properties / type / description
      Previous value: -"Filter by asset type (agent, skill, prompt, prompt_chain, mcp_connector, bundle)"New value: +"Optional asset type: agent, skill, prompt, prompt_chain, mcp_connector or bundle; omitted means all types."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety and idempotency are covered. The description adds genuinely non-obvious context beyond that: downloads measure acquisitions rather than successful applications or ratings, and no login or download is recorded. It stops short of describing pagination or ordering ties, which keeps it at 4.

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

Conciseness4/5

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

Front-loaded with purpose, then routing, then return format and caveats, then example. Every sentence carries information, though the return-value sentence partially duplicates a schema that already exists, making it slightly longer than strictly needed.

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 list tool with full schema coverage and an output schema, the description covers purpose, alternative, semantic caveats on the popularity metric, and the empty-result case. An agent has everything needed to call it correctly.

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 both params (type, limit) including enum values and the 1-20 clamp are already documented. The description only restates 'optionally filtered by type' and adds a sample call, which adds little beyond the schema; 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?

States a specific verb and resource ('List the most popular Spark assets by download count') with an explicit optional scope ('filtered by type'). It also names the sibling search_assets and the distinction between browsing and text matching, so an agent can route without opening either schema.

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?

Explicit 'For when browsing without a text query; search_assets finds text matches' gives both the when-to-use condition and the alternative tool. Nothing is left to inference.

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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