Extract article metadata and body paragraphs from a canonical HuffPost URL. Use it to retrieve structured public content for analysis or reading.
Get HuffPost article content. Returns public HuffPost article metadata and body paragraphs from a canonical article URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Canonical HuffPost 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 are provided, so the description bears the full burden. It discloses the key behavioral trait that this is a read-only operation returning 'public' content, which implies no authentication is needed. It does not describe error behavior, response shape details, or any constraints beyond 'canonical,' but for a straightforward read tool the public-read nature is the most important trait and it is conveyed.
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 zero filler. The verb and scope are front-loaded, and the return payload description earns its place by clarifying output. Every word contributes meaning.
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 fetch tool with no output schema and no nested objects, the description is nearly complete: the agent knows what input to supply, what output to expect (metadata and body paragraphs), and the public nature of the data. A slightly richer statement of what 'metadata' includes would fully close the gap, but nothing critical is missing for correct invocation.
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 required 'url' parameter is already documented as 'Canonical HuffPost article URL.' The description reinforces the 'canonical' requirement in prose, which adds marginal value, but it does not explain URL formatting, accepted variants, or what happens with non-canonical URLs. The schema already does the heavy lifting, so baseline 3 is appropriate.
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 uses a specific verb-resource pair ('Get HuffPost article content') and precisely states what is returned: 'metadata and body paragraphs from a canonical article URL.' This cleanly differentiates it from sibling tools like huffpost_headlines, huffpost_author, huffpost_news, and huffpost_sections, and from article tools for other publications.
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 usage context: call this when you already have a canonical HuffPost article URL. However, it gives no explicit when-not-to-use guidance, no mention of alternative discovery tools (e.g., using headlines/search to obtain a URL first), and no stated exclusions. For a simple single-purpose fetch tool, the implied context is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.