readable-content

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

With no annotations, the description should disclose behavioral traits. It mentions redirects are followed and caching behavior via no_cache, but lacks details on rate limits, authentication, error handling for non-article URLs, or cost specifics beyond the alternative comparison. It is moderately transparent.

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: it first states the core purpose, then lists return fields, and ends with cost/alternatives. Every sentence adds value with no waste.

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 simple tool with 2 parameters and no output schema, the description covers purpose, usage, and alternatives adequately. It could clarify behavior for non-article pages, but is largely complete given the tool's complexity.

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% for both parameters. The description adds no new meaning beyond the schema's parameter descriptions (e.g., 'Redirects are followed' is already in url description, no_cache behavior is in schema). Baseline score of 3 applies.

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 'Fetches any public URL and returns the full readable article text as clean Markdown', which is a specific verb+resource combination. It distinguishes itself from siblings like 'web-scrape-links' by emphasizing extraction of readable content.

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 explicitly mentions cost comparison and alternatives ($0.004 vs exa.ai/contents and web-read), implying when to use this tool over others. It also describes the output as ready for LLM tasks, indicating suitable use cases.

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