Extract Article Content

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

Annotations already indicate read-only, idempotent, and open-world. The description adds critical behavior: HTML via Mozilla Readability, academic PDF auto-detection methods, tiered depth, and errorInfo on failures. This goes well beyond annotations, providing rich behavioral 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 a single paragraph of about 5 sentences, efficiently packing purpose, PDF detection, tiered modes, and error handling. No redundant information; every sentence earns its place.

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 (3 params, output schema exists), the description covers all key aspects: URL requirements, PDF detection, mode semantics, truncation, and error behavior. It is fully sufficient for an agent to select and invoke correctly.

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 coverage is 100%, so baseline is 3. The description enhances understanding: explains abstract mode as cheap survey (~1500 chars, page 1 or meta description), full mode uses Playwright, and max_chars truncation. It adds use-case context that the schema alone does not convey.

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 'Fetch one public URL -> clean article text', specifying the verb and resource. It distinguishes itself from siblings like 'search' and 'search_extract' by focusing on extraction from a given URL, not search. The mention of HTML and academic PDFs adds specificity.

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 explains when to use each mode: abstract for cheap survey/triage, full for full article. It also notes best-effort failure handling. However, it does not explicitly contrast with alternatives like 'search_extract' or specify when not to use the tool, missing some guidance.

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