read_article
Read and extract article content from a URL.
Args:
url: The article URL to read
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Read and extract article content from a URL.
Args:
url: The article URL to read
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavior disclosure. It explicitly states the read/extract action and implies a non-mutating operation, but it does not disclose request-side considerations such as URL format requirements, blocking, paywalls, rate limits, or failure behavior. This is adequate but not rich.
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?
The description is compact and front-loaded: the purpose appears in the first sentence, and the single parameter is documented in a short Args block. There is no filler or redundant detail.
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 an output schema present, the description covers the core mechanics adequately. However, it lacks any guidance about valid URL formats, what type of article content is expected, and how this tool relates to the sibling tools, leaving some selection context incomplete.
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 0%, so the description must compensate. It does restate the parameter and adds that it is 'The article URL to read', which is minimally helpful, but it does not specify expected URL format (e.g., including http/https) or constraints beyond being a string. The single parameter is simple enough that this is acceptable.
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-object pair, 'Read and extract article content from a URL', which clearly identifies the tool as a direct URL content fetcher. It is clear, but it does not explicitly differentiate itself from sibling tools like news_search or daily_briefing, so it misses the top score.
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 gives no guidance on when to use this tool versus the sibling news/search tools, nor does it mention any prerequisites or exclusions. An agent must infer the appropriate context from the tool name and the word 'URL', which is weak selection support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are mostly distinct: daily_briefing is a curated combined digest, korean_news is category-based, tech_news is topic-specific, news_search is keyword search, read_article extracts content, and trending shows top headlines. Minor overlap exists between daily_briefing and the other fetch tools, but each serves a clear purpose.
All tool names use snake_case, but the pattern isn't uniform—some are adjective_noun (korean_news, tech_news, daily_briefing), some noun_verb (news_search), and one gerund (trending). Despite the mixed structure, the naming is readable and predictable enough.
With 6 tools, the server is well-scoped for a news hub. Each tool covers a distinct content need without redundancy, and the count feels neither thin nor bloated.
The surface covers core news workflows: browse by category or topic, search, read full articles, and get trending headlines. Missing features like custom briefings or language-specific search for korean_news are minor and don't break the primary use case.