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Metis · Data Analyst — Suggest Cleaning

suggest_cleaning

Analyzes a dataset to detect data quality issues and returns prioritized cleaning operations with explanations.

Instructions

Profile a dataset and return specific recommended cleaning operations.

Analyses the profile and suggests operations with rationale, e.g.:
  - "col 'age' has 12% nulls → consider fill_na or drop_na_rows"
  - "7 duplicate rows detected → apply drop_duplicates"
  - "col 'name ' has leading/trailing whitespace → apply strip_whitespace"

Args:
    path: Absolute local path to the dataset file.

Returns JSON with profile summary and a list of suggested operations,
each with: operation, column (if applicable), rationale, priority (high/medium/low).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Describes the return format and operational logic (analyzes profile, suggests operations with priorities), but omits whether the tool modifies the dataset (assumed read-only but not stated). No annotations to supplement.

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?

Concise, front-loaded purpose, examples illustrate functionality, and structured Args/Returns section clearly explains output format. No redundant information.

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?

Covers purpose, parameters, and return structure adequately. Output schema covers return details, so description doesn't need to exhaustively list fields. Slight gap in describing the profile summary format.

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?

Single 'path' parameter is described as 'Absolute local path to the dataset file,' adding necessary detail beyond the schema's type definition. Compensates for 0% schema coverage.

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?

Clearly states the tool profiles a dataset and returns recommended cleaning operations, with concrete examples distinguishing it from simpler profiling or cleaning execution tools.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like profile_dataset or clean_dataset. Lacks prerequisites (e.g., file must exist) or context about typical workflow placement.

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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