extract_article

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's read-only ('makes no changes to any external system'), handles specific content types ('paywalled and JavaScript-rendered articles'), and includes operational details like rate limits ('Free tier: 100 requests/month') and error conditions ('Returns an error if rate limit or API key is invalid'). However, it lacks details on response format beyond 'structured JSON' and potential latency or retry behavior.

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 appropriately sized and front-loaded, starting with the core purpose and immediately following with usage guidelines and behavioral details. Every sentence adds value, such as distinguishing from siblings, stating read-only nature, and specifying requirements and limits, with no redundant or unnecessary information.

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?

Given the tool's complexity (handles paywalled/JS-rendered content, has API key and rate limit requirements) and lack of annotations and output schema, the description is largely complete. It covers purpose, usage, behavioral traits, and operational constraints. However, it could be more complete by detailing the exact structure of the returned JSON or error formats, slightly reducing the score.

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 input schema has 100% description coverage, with the 'url' parameter fully documented in the schema. The description does not add any additional meaning or context beyond what the schema provides for the parameter. According to the rules, when schema_description_coverage is high (>80%), the baseline score is 3, which applies here as the description compensates adequately but doesn't enhance parameter understanding.

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 clearly states the tool's purpose with a specific verb ('Extract') and resource ('main article content from a news article or blog post'), and distinguishes it from sibling tools by specifying 'use extract_url for product pages, listings, or generic data.' This provides explicit differentiation, making the purpose highly clear.

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 provides explicit usage guidelines, including when to use this tool ('Optimised for editorial content') and when not to ('use extract_url for product pages, listings, or generic data'). It also mentions prerequisites ('Requires HAUNT_API_KEY environment variable'), offering comprehensive guidance for proper tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.