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stuff_article

Read-only

Fetch public Stuff article metadata and body paragraphs from a canonical url. Premium stories are marked paywalled when a free teaser exists; stories with no free text return a permission error. Use stuff_headlines for story lists, stuff_sections to browse topics, stuff_news for the general feed, or stuff_author for an author profile.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "stuff_article"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesCanonical Stuff article URL

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / url / description
      Added value: +"Canonical Stuff article URL"
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations cover readOnly and openWorld, so the description's job is to add behavior, which it does: it discloses paywall handling ('paywalled' flag when a free teaser exists) and the failure mode (permission error when no free text). That is real context beyond annotations, though nothing is said about rate limits or truncation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with what it fetches and from what input, then paywall/error behavior, then sibling routing. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-shape explanation is not required, and the description covers scope, paywall edge cases, failure mode, and alternatives. Complete for a single-item fetch tool; the only omission is any hint about how much of a long article body is returned.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already defines the single 'url' parameter as a canonical Stuff article URL. The description reinforces the 'canonical url' requirement, which adds marginal value, but the baseline 3 applies since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb (Fetch) plus resource (Stuff article metadata and body paragraphs) and input (canonical url). It is clearly distinguishable from the sibling list-manipulation tools it names (stuff_headlines, stuff_sections, stuff_news, stuff_author).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes the agent: use this for a single article by URL, and use stuff_headlines for lists, stuff_sections for topics, stuff_news for the general feed, stuff_author for an author profile. When-to-use and alternatives are both spelled out.

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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