extract

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

No annotations are provided, so the description carries the full burden. It clearly describes the fallback order: JSON-LD → __NEXT_DATA__ → Nuxt → JSON-in-script → OpenGraph/meta → microdata → text_main. It also explains the return format and the behavior when a specific strategy is forced. This provides full transparency about the tool's behavior.

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, but it is well-structured: it opens with the purpose, details the fallback order, then provides usage guidance. It is front-loaded with the core purpose. However, it is somewhat dense and could be broken into more digestible sentences. The information content is efficient, but slight readability improvements would earn a 5.

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 absence of an output schema, the description covers the return format ({strategy, confidence, data, tried}) and explains behavior for both auto-strategy and forced strategy. It does not mention error cases or edge conditions, but for a single-parameter tool with 100% schema coverage, the description provides sufficient context for an AI agent to use it 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% and the only parameter 'strategy' is already described with allowed values in the schema. The description goes beyond by explaining that passing a value forces a specific extractor, and it lists the possible values again. This adds context but does not introduce new semantic meaning beyond what the schema offers. The baseline is 3, and the added usage context justifies a 4.

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 begins with 'Auto-strategy structured-data extraction' which clearly states the tool's purpose. It lists the specific extraction methods and returns the highest-confidence hit as {strategy, confidence, data, tried}. It distinguishes from siblings by positioning it as a one-shot 'give me the data, you figure out how' call, contrasting it with tools like extract_cards or extract_list that target specific data formats.

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 says when to use this tool: 'when you don't want to plan the strategy yourself'. It also provides an alternative: 'Pass strategy='json_ld' (or any of the names above) to force a specific extractor'. It does not explicitly state when not to use it or compare it to sibling tools, but it implies that if a specific strategy is desired, you should force it. The lack of explicit exclusions prevents a 5.

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