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New Hugging Face Spaces — AI App Demo Discovery (hfspaces)

data_preview

Read-onlyIdempotent

✅ No API key needed. Listing: hfspaces: New Hugging Face Spaces — AI app demos & live web UIs. Price 0.01 USDC/query (max 20 queries/session). Sample questions: What AI app demos were just created on Hugging Face Spaces?; Show the newest gradio or streamlit Spaces shipped this hour. FREE preview — no key, no payment. Try one of the sample questions now.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "data_preview"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugNoPublic listing slug. Defaults to the routed session's listing when connected via /mcp/data/{slug}/http.
questionNoOptional free-text question you'd ask this data (echoed back).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

With annotations already covering read-only, non-destructive, idempotent behavior, the description adds useful auth/rate-limit context (no key, max 20 queries/session). However, the line 'Price 0.01 USDC/query' conflicts with the repeated 'FREE preview—no payment' messaging and is not clarified, which could confuse an agent about whether a call is billed.

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

Conciseness2/5

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

The text is a promotional blurb: it repeats the no-key/free message, includes a price that muddies the offer, and puts sample questions before a clear purpose statement. Emojis and a call to action add noise rather than front-loaded clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is low-complexity with two optional params and rich annotations, and the schema description says it returns public metadata only. Still, the main description never states the preview's return shape or how slug routing works, so it is adequate but not complete for a no-output-schema 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 coverage is 100%, and both slug and question are documented in the input schema, so the description need not explain them. The main description gives sample questions but does not add slug/question semantics beyond the schema.

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

Purpose3/5

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

The description names the hfspaces listing and calls itself a free preview, but it never states a clear verb like 'preview a listing' or explains what the preview returns. The sample questions help illustrate use, yet the purpose remains somewhat indirect because the text is dominated by pricing and promotional language.

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?

It provides some usage context—free, no API key, up to 20 queries/session, sample questions—but does not say when to choose this over paid siblings such as data_session_query. There are no explicit exclusions or conditions beyond 'try the sample questions.'

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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