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steam_app_intel

Full Steam app intelligence: details, live player count, review summary, owner estimate. Paid: $0.005 per call via x402.

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": {
      "appid": "<appid>"
    },
    "name": "steam_app_intel"
  }
}

Input Schema

NameRequiredDescriptionDefault
appidYesSteam app ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses a significant behavioral trait: 'Paid: $0.005 per call via x402,' informing the agent of cost implications. It also sets expectations for response content by listing the data returned. It does not mention failure behaviors or auth requirements, but for a simple read tool, the cost disclosure adds meaningful transparency.

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 short clauses, front-loading the tool's purpose and then listing concrete data types. The pricing information is concise and valuable. No filler or redundant phrasing. Every word contributes to understanding scope and cost.

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?

With only one parameter and no output schema, the description does enough by naming the response categories: 'details, live player count, review summary, owner estimate.' It also notes the pricing model. It lacks examples or edge-case handling, but for a low-complexity informational tool with a simple input, this suffices.

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 schema fully documents the one parameter (appid) with a description 'Steam app ID,' so baseline is 3. The tool description adds no additional parameter context, but given 100% schema coverage, the schema is sufficient. The description does not clarify the format or range of appid, but that is not required for a simple integer field.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly enumerates what the tool provides—'details, live player count, review summary, owner estimate'—making its purpose concrete with specific data elements. It lacks an explicit verb like 'retrieve' or 'get,' but 'Full Steam app intelligence' combined with the list conveys the function. It does not explicitly distinguish from sibling tools, but the listed data types set it apart from general game metadata or deals.

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 use when the user needs comprehensive Steam app data, as indicated by 'Full Steam app intelligence' and the enumerated fields. It does not mention when not to use it or provide alternatives, and the paid per-call note is a cost consideration rather than a usage exclusion. This makes the guidance implicit rather than explicit.

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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