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validate_track_ids

Validate track IDs and identify which are valid or invalid in rekordbox. Returns validation results with valid and invalid IDs.

Instructions

Validate a list of track IDs and show which are valid/invalid.

Args: track_ids: List of track IDs to validate

Returns: Validation results with valid and invalid IDs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
track_idsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It states the operation (validate) and the output (valid/invalid IDs), but it does not explicitly confirm whether this is read-only, how 'valid' is determined, or whether there are any side effects. This leaves significant ambiguity for an agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured, with a clear first sentence stating the purpose, followed by Args and Returns sections. No redundant information is included, and every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description lacks essential context. It does not define what constitutes 'valid' or 'invalid,' does not mention potential errors or edge cases, and does not clarify whether the operation is purely read-only. With no annotations, the agent may not have enough information to use the tool safely and effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate. The Args section says 'track_ids: List of track IDs to validate,' which merely restates the parameter name and adds no additional constraints, format, or limits. It provides minimal value beyond the schema itself.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Validate a list of track IDs and show which are valid/invalid.' It uses a specific verb ('validate'), a resource ('track IDs'), and an outcome ('show which are valid/invalid'), making it easily distinguishable from sibling tools like find_broken_tracks or get_track_details.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when you need to check if track IDs are valid), but it does not explicitly state when not to use it or mention alternatives. No exclusions or comparisons to sibling tools are provided, leaving the usage context partially implicit.

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

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