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

With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it fetches HTML content, processes it for structured extraction, and mentions potential error conditions (HTTPStatusError, parsing errors). It doesn't cover rate limits, caching behavior, or authentication requirements, but provides solid operational context.

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 well-structured with clear sections (purpose, args, returns, raises) and front-loaded key information. Some sentences could be more concise (e.g., 'Fetches the HTML content from the provided URL, processes it to extract structured news information' could be tightened), but overall it's efficient and organized.

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 tool with no annotations and no output schema, the description provides good completeness: clear purpose, parameter explanation, return format description, and error conditions. It could benefit from more explicit sibling tool differentiation and operational constraints, but covers the essential context well.

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?

With 0% schema description coverage and only one parameter, the description fully compensates by clearly explaining the 'url' parameter's purpose ('complete URL of the CoinDesk news article to retrieve') and constraints. It adds essential meaning beyond the bare schema.

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 specific action ('retrieves and extracts full content'), resource ('news article from CoinDesk'), and scope ('structured news information including title, subtitle, author, publication date, and article content'). It distinguishes from the sibling tool 'recent_news' by focusing on individual article extraction rather than recent news listing.

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 usage context through the mention of 'CoinDesk news article' and the required URL parameter, but doesn't explicitly state when to use this tool versus the 'recent_news' sibling. No explicit guidance on prerequisites, alternatives, or exclusion criteria is provided.

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

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 the tool's behavior: fetching and parsing an RSS feed, returning formatted news items, and raising specific errors (HTTPStatusError, Exception). This covers key operational aspects like data source, processing steps, and error handling, though it lacks details on rate limits or caching.

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 well-structured and front-loaded with the core purpose in the first sentence. Subsequent sentences add necessary details about the process, return format, and error handling without redundancy. It could be slightly more concise by combining some sentences, but overall it is efficient and informative.

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 (fetching and parsing external data) and lack of annotations or output schema, the description provides a complete picture: it explains what the tool does, how it works, the return format, and potential errors. This is sufficient for an agent to understand and use the tool effectively, though an output schema would further enhance completeness.

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 tool has 0 parameters with 100% schema description coverage, so no parameter information is needed. The description appropriately does not discuss parameters, focusing instead on the tool's functionality and output. This meets the baseline for tools with no parameters.

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 specific action ('retrieves'), resource ('latest cryptocurrency and blockchain news articles'), and source ('from CoinDesk's RSS feed'). It distinguishes from the sibling tool 'read_news' by specifying the RSS feed source and real-time nature ('latest'), whereas 'read_news' might imply reading stored or different news sources.

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 usage context by specifying 'latest' news and the CoinDesk source, which helps differentiate from 'read_news'. However, it does not explicitly state when to use this tool versus 'read_news' or provide any exclusions or prerequisites for usage.

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