Retrieve public Engadget article metadata and full body paragraphs from a canonical article URL for reading, research, or analysis.
Get Engadget article content. Returns public Engadget article metadata and body paragraphs from a canonical article URL. Engadget articles are free to read, so the full body is returned.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Canonical Engadget article URL |
Changes observed during successful MCP inspections.
v1.17.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full behavioral burden. It does disclose useful context: the content is 'public' and 'free to read,' explaining why the 'full body is returned' rather than a paywalled excerpt. This effectively communicates a safe-read operation. However, it doesn't cover edge behaviors like invalid or non-canonical URL handling, or describe the return structure beyond the vague 'metadata and body paragraphs.'
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?
Three short sentences with zero wasted words. The core verb-resource pair is front-loaded in the first sentence, the return content and input requirement follow, and the final sentence earns its place by explaining the free-access behavior. Nothing is redundant or padding.
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 low-complexity tool (1 required param, no output schema, no annotations), the description covers the essential ground: what input is needed, what is returned, and that access is unrestricted. The main gap is that with no output schema, 'metadata and body paragraphs' is underspecified, but an agent still has enough to invoke the tool correctly for this simple fetch operation.
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?
Schema description coverage is 100% — the single `url` parameter is already documented as 'Canonical Engadget article URL.' The description reinforces this by reiterating 'from a canonical article URL' but adds little meaning beyond the schema, so the baseline of 3 applies.
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?
The description states a specific verb ('Get') and resource ('Engadget article content'), and specifies what is returned ('public Engadget article metadata and body paragraphs from a canonical article URL'). It's clear and unambiguous, but it doesn't explicitly differentiate from the many sibling article tools (e.g., cnet_article, nzherald_article) beyond the brand name, which the tool name already carries.
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?
Usage is implied through the input requirement: an agent should call this when it has a 'canonical article URL' and wants full article content. However, the description never explicitly says when to use this versus the four Engadget siblings (engadget_headlines, engadget_news, engadget_author, engadget_sections) or other publications' article tools, and names no alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.