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detect_metadata

Locate sidecar metadata files (README, LICENSE, data dictionary, dataset card, manifest) alongside a data path, with long-file excerpting to quickly understand dataset context.

Instructions

Find sidecar metadata in or alongside path: README, LICENSE, data dictionary, dataset card, manifest YAML/JSON.

    Excerpts long files at 1500 chars. Output size: small to medium.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description discloses truncation behavior (1500 chars) and result size, which is useful. However, it does not explain how metadata is detected, potential for recursive scanning, or that it only reads sidecar files.

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?

Two concise sentences front-load the purpose and add a behavioral note. No redundant phrases.

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

Completeness4/5

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

The tool is simple with one parameter and an output schema. The description covers purpose and output size, which is sufficient for an agent to invoke it, though it lacks explicit guidance on result format or edge cases.

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

Parameters4/5

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

The description uses `path` to indicate the target location and specifies that scanning occurs 'in or alongside' it, adding context beyond the bare schema property. It suggests path can be a file or directory, which aids usage.

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 defines the tool's function with a specific verb ('Find') and resource ('sidecar metadata'), listing concrete examples (README, LICENSE, data dictionary, dataset card, manifest YAML/JSON). This differentiates it from sibling tools like list_files or detect_pattern.

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 the tool is used to locate metadata files but does not explicitly state when to use it over alternatives like list_files or describe_source. No exclusions or alternative tool references are provided.

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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