Lynceus page extraction

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

No annotations are present, so the description carries the full burden. It discloses the 4-tier anti-bot ladder, cost model (1 credit per success, 25 for captcha, free cache hits, no charge for failures), and response statuses (needs_browser/skipped_browser/error). It also explains that per-URL errors don't fail the batch, providing complete behavioral clarity.

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?

While long, the description is highly structured with clear section headers (WHEN TO USE, ARGUMENTS, COST, RETURNS, FAILURES) and every sentence carries useful information. It's front-loaded with purpose and usage, then details arguments, cost, and failure modes in a logical order without redundancy.

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?

This is a complex tool with 4 parameters, cost implications, and a multi-tier process. The description covers everything needed for correct invocation: parameter semantics, cost rules, return format, retry logic (needs_browser), and error handling. Without an output schema, it fully explains the response structure. Nothing essential is missing.

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%, but the description adds significant extra semantics: batching URLs is cheaper/faster, allow_browser is only for JS-rendered pages and costs time, allow_captcha requires explicit user consent and premium cost, and format differences (markdown keeps links vs plain text). This goes well beyond the schema descriptions.

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 fetches web pages and returns clean Markdown, with a specific verb+resource. It also distinguishes from naive fetchers and siblings (lyn_search is search, lyn_usage is usage) by focusing on content extraction. The mention of handling 403/paywall-shell pages adds specificity that sets it apart.

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 'WHEN TO USE' section explicitly says to use this when you have URLs and need actual text, and directly says 'Prefer this over your built-in fetch' with reasons. It provides clear conditions for toggling allow_browser (only when needs_browser/skipped_browser) and allow_captcha (with user consent), leaving no ambiguity about when to select this tool.

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