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evc-spark-mcp

evc-spark-mcp

by entire-vc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_asset

Retrieve full details of a Spark asset using its unique slug, including description, content, files, and ratings.

Instructions

Get full details of a Spark asset by its slug. Returns description, content, files, ratings, and more.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "slug": "<slug>"
    },
    "name": "get_asset"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesAsset slug (e.g. 'vb-seo-expert', 'vb-python-expert')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It correctly implies a read operation ('Get') and specifies return fields, but lacks details on authentication, rate limits, or any side effects. There is no contradiction, but behavioral traits beyond the obvious are missing.

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 two sentences: first states the core action, second lists returned data. It is concise, front-loaded, and every sentence adds value with no redundancy.

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?

For a simple getter with one parameter and no output schema, the description covers the main points. It could be improved by specifying that it returns a single asset object and clarifying 'more', but it is largely 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?

The input schema covers 100% of parameters with a clear description for 'slug' including examples. The description adds no additional meaning beyond 'by its slug', so it meets the baseline but does not enhance understanding.

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 'Get full details of a Spark asset by its slug,' specifying the verb ('Get'), resource ('Spark asset'), and the means ('by its slug'). It lists what is returned ('description, content, files, ratings, and more'), and distinguishes itself from siblings like 'get_asset_content' (likely subset) and 'search_assets' (broader search).

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 when you have the slug, but does not explicitly state when to use this tool over alternatives. For example, there is no guidance on using 'get_asset' vs 'get_asset_content' (if only content is needed) or 'search_assets' (when slug is unknown). Context is implied but not clarified.

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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