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clean_drop_duplicates

Remove duplicate rows from a data source by exact full-row matching or by specified key columns, keeping the first occurrence per key.

Instructions

New source with duplicates removed.

    Without `keys`: exact full-row deduplication (`SELECT DISTINCT *`).
    With `keys`: keeps the first row per key combination via ROW_NUMBER.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keysNo
aliasNo
source_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the burden of disclosing behavior, and it does so well by specifying the exact SQL semantics (`SELECT DISTINCT *` and `ROW_NUMBER`). It also implies non-destructive behavior by saying 'New source'. However, it does not clarify what determines the 'first row' when using keys (no ordering specified), which is a notable gap.

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 extremely concise and well-structured. The first sentence states the outcome, and the two bullet-like lines cover the distinct modes. Every sentence provides necessary information with no wasted words.

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

Completeness3/5

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

The description covers the core behavior and the output schema is present, so return values don't need explanation. However, it omits the purpose of the `alias` parameter and fails to warn that 'first row' is undefined without an explicit ordering, which is important for a deduplication tool. These gaps prevent it from being fully complete.

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?

Schema description coverage is 0%, so the description must compensate. It explains the `keys` parameter in detail, but it does not describe `source_id` or `alias`. Since only one of three parameters is addressed, the compensation is incomplete.

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: it creates a new source with duplicates removed. It further distinguishes between two modes (full-row deduplication and key-based deduplication), making the tool's behavior specific and differentiated from sibling cleaning tools.

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 provides mode-specific guidance by explaining when to use `keys` versus not, but it does not explicitly discuss when to choose this tool over alternative cleaning tools or mention exclusions. Usage context is implied rather than stated.

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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