extract_cards

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

No annotations provided, so description carries full burden. It describes that it auto-detects and returns normalized items, and that optional parameters scope detection or bias scoring. It does not explicitly state side effects, but extraction tools are inherently read-only, so this is acceptable.

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?

Two tightly crafted sentences, front-loaded with the main purpose and output format, no unnecessary words. 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 no output schema, the description fully details the output structure (list of objects with specified fields). It also covers usage context and parameter roles, making it complete for an agent to use 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% with descriptions for all three parameters. The description adds value by explaining that selector scopes detection to known card nodes and kind biases scoring, which supplements 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 it auto-detects repeated card/article/product blocks and returns normalized items with specific fields. It also distinguishes itself from the sibling tool 'extract_list' by specifying exactly when to prefer this tool.

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?

Explicitly says 'Prefer this over extract_list when the page has semantically ambiguous... cards and you do not already know field selectors.' Also explains how optional parameters (selector, kind) can be used to bias detection.

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