Fetch TechCrunch article content by canonical URL: title, authors, dates, dek, section, lead image, and body paragraphs in structured JSON.
Get TechCrunch article content. Returns public TechCrunch article metadata (title, author(s), published/updated dates, dek, section, lead image) and body paragraphs from a canonical article URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Canonical TechCrunch article URL |
Changes observed during successful MCP inspections.
v1.17.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It usefully states that the content is public and enumerates the returned metadata fields and body paragraphs, but it does not address errors, paywalls, redirect handling, or output formatting.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler; the action is front-loaded and the return contents are compactly but usefully enumerated. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read tool with no output schema, the description provides the input contract and the output payload in sufficient detail. Minor omissions such as invalid-URL or unavailable-article behavior keep it from being fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the only parameter at 100% coverage, so the description adds little beyond restating 'canonical article URL'. No URL format, normalization, or validation details are provided, keeping this at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific operation, 'Get TechCrunch article content', and ties it to a canonical article URL. The mention of metadata plus body paragraphs distinguishes it from sibling list/author/section tools like techcrunch_headlines and techcrunch_author.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use case is implied: use it when you have a canonical TechCrunch article URL and want the full article content. However, it never explicitly names alternatives or exclusion conditions, so an agent must infer when to pick it over techcrunch_news, techcrunch_headlines, or similar article-fetching tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.