validate_guided_recipe_structure

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains the underlying Cookidoo request schema, positional indexing semantics (zero-based JavaScript UTF-16 ranges), and the distinction between VOLUME and other annotation positions. This is a validation tool, so read-only behavior is implied, but the detailed schema conventions usefully disclose the validation contract.

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 well-organized with clear line breaks and bullet-like enumeration of annotation types. Each section adds value: purpose, annotation types, placement rules, and positional semantics. It's somewhat long but dense with necessary technical detail; no filler.

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 validation tool with an output schema and one parameter, the description covers the key context: what gets validated, annotation type semantics, placement rules, and positional encoding. It could possibly clarify the expected return/error format, but the output schema presumably handles that. Given the moderate complexity of guided-cooking validation, this is reasonably complete.

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?

With 0% schema description coverage and only one parameter (recipe_json, a string), the description compensates by explaining what the JSON contains: TTS, MODE, INGREDIENT annotations with specific semantic meaning. While it doesn't describe the exact JSON structure format, it clarifies the annotation types and their placement rules, which is meaningfully beyond the bare schema.

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 validates a complete custom recipe including guided-cooking annotations, which is a specific verb+resource purpose. It distinguishes reasonably from siblings like generate_recipe_structure and update_custom_recipe_steps by focusing on validation of annotation structure, though it doesn't explicitly name alternative tools.

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 provides substantial context on when this tool applies: validating complete recipes with guided-cooking annotations and includes important placement rules (INGREDIENT annotations in ingredient-only steps, TTS/MODE in separate machine-action steps). It also tells the user about the companion tool calculate_annotation_position for position handling, giving clear operational guidance.

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