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find_duplicates

Identify duplicate medical documents by comparing filenames and file sizes to help organize cancer patient records after repeated imports.

Instructions

Detect potential duplicate documents based on original filename and file size.

Returns groups of documents that share the same original_filename + size_bytes. Each group contains 2+ documents. Useful for cleanup after repeated imports.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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 discloses key behavioral traits: it detects duplicates based on specific criteria and returns groups, which is useful. However, it does not mention potential side effects (e.g., whether it modifies data, requires permissions, or has rate limits), leaving gaps for a tool with no annotation coverage.

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 appropriately sized and front-loaded, with two sentences that efficiently convey purpose and usage. Every sentence earns its place: the first explains what the tool does and its criteria, and the second clarifies the output and context, with zero waste or redundancy.

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?

Given the tool's complexity (simple detection with no inputs), no annotations, and an output schema (implied by 'Has output schema: true'), the description is mostly complete. It explains the detection logic and use case, but since no annotations exist, it could benefit from more behavioral details (e.g., safety or performance). The output schema likely covers return values, reducing the burden.

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 input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate since no parameters exist. Baseline for 0 parameters is 4, as the description need not compensate for any gaps.

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 purpose with specific verbs ('detect potential duplicate documents') and resources ('documents'), and distinguishes it from siblings by focusing on duplicate detection based on filename and size. It explicitly mentions the criteria (original_filename + size_bytes) and that it returns groups of 2+ documents, making the purpose highly specific and differentiated.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool ('useful for cleanup after repeated imports'), which implies a specific scenario. However, it does not explicitly state when not to use it or name alternatives among siblings (e.g., 'list_documents' or 'search_documents' for general document queries), so it lacks full exclusion guidance.

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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