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TechCrunch AI News — buy per-query in-session (techcrunchai)

data_preview

Read-onlyIdempotent

✅ No API key needed — call this now. Listing: techcrunchai: TechCrunch AI — industry news, funding & launches. Price 0.01 USDC/query (max 20 queries/session). Sample questions: What are today's biggest AI industry news stories?; Any AI funding rounds or model launches announced this week?. FREE preview — no key, no payment. Try one of the sample questions now.

Input Schema

TableJSON 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. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare read-only and idempotent behavior, and the description adds valuable context beyond that: no API key is required, the preview is free, and the underlying listing costs 0.01 USDC/query with a session cap. The wording could be cleaner about the price applying to the paid listing rather than the preview, but it does not contradict the annotations.

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 description is short but padded with redundant promotional language: 'No API key needed' is echoed by 'no key, no payment', and 'call this now' and 'Try one of the sample questions now' do not earn their place. The message would be tighter as a single factual sentence.

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 description gives enough to attempt a call (free, no key, sample questions, a concrete listing), but it does not state what the response will contain, and the price/session-limit sentence is ambiguous about whether it applies to this preview call. With no output schema, a short note on the return value would complete the picture.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the baseline is 3, and the description exceeds it by providing a concrete slug value ('techcrunchai') and two sample questions that illustrate how to use the question parameter. This gives an agent concrete call examples that the schema alone does not offer.

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 identifies the resource (the techcrunchai listing) and clearly labels the operation as a 'FREE preview' with sample questions, so an agent can infer it is a no-cost way to sample a listing. It does not use a crisp 'preview X' verb form and mixes in pricing details, so it stops short of a 5.

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 'No API key needed — call this now' and 'FREE preview — no key, no payment' lines imply this is the unpaid entry point, which is useful guidance. However, it never names sibling tools like data_session_query or states when to use this instead of a paid query, so the when-to-use guidance remains implicit.

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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