Extract public MacRumors article metadata and body paragraphs from a canonical news, guide, how-to, or review URL to get structured content for research or publishing.
Get MacRumors article content. Returns public MacRumors article metadata and body paragraphs from a canonical news, guide, how-to or review URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Canonical MacRumors 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 burden of behavioral disclosure. It goes beyond a bare 'get article' by specifying that only public content is returned and that the payload consists of metadata and body paragraphs. This gives an agent a realistic expectation of access level and output shape, though it omits error handling, pagination, and URL format details.
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 short sentences with the core purpose front-loaded and return-value detail in the second. There is no filler, tautology, or restatement of the schema; every clause 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 single-parameter fetch tool with no output schema and no annotations, the description adequately covers what it returns and what input it expects. It could add URL format specifics or error behavior, but nothing essential is missing for an agent to decide and invoke it correctly. The completeness is strong given the tool's simplicity.
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 single url parameter at 100% coverage ('Canonical MacRumors article URL'), so the baseline is met. The tool description adds extra meaning by spelling out accepted URL types—news, guide, how-to, or review—which helps the agent rule out non-article pages. This enriches the schema slightly without redundancy.
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 verb ('Get') and resource ('MacRumors article content'), and narrows the input to canonical news, guide, how-to, or review URLs. The mention of 'MacRumors' clearly distinguishes it from the many unrelated article-fetching siblings such as nzherald_article or ninetofivemac_article. The name itself further ties it to the article content tool rather than headlines or author tools.
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 description implies the appropriate use case: use this when you have a canonical MacRumors article URL and want its content. It explicitly sets a precondition ('canonical ... URL') but does not name alternatives or exclusion conditions, such as when to use macrumors_headlines instead. This is clear context without explicit when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.