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normalize_arabic

Normalize Arabic text for consistent matching by removing diacritics, tatweel, and unifying alef variants. Use for search keys, deduplication, and comparison, not for display.

Instructions

Normalise Arabic text so that forms users type interchangeably compare equal — strips diacritics and tatweel and folds the alef variants. Use it for search keys, deduplication and matching, never for text you are about to display.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe Arabic text to normalise.
convertDigitsNoConvert Arabic-Indic digits into 0-9. Default false.
unifyTaaMarbutaNoFold ة into ه. Helps fuzzy matching, changes meaning. Default false.
unifyAlefMaqsuraNoFold ى into ي. Helps fuzzy matching, changes meaning. Default false.
collapseWhitespaceNoCollapse whitespace runs. Default false.
Behavior4/5

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

No annotations are provided, so the description carries full responsibility for disclosing behavior. It warns that the output is not suitable for display, which conveys the lossy/destructive nature of normalization. It does not mention the optional transformation flags or their implications, but the schema covers those; the description adds the key caveat.

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 two sentences, immediately states the core function, and provides a clear use-case disclaimer. No redundancy or wasted words.

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 has five parameters, all documented in the schema, and the description gives the essential context and usage caveat. It does not explicitly state the return value, but that is inferable from the normalization concept and the schema. The sibling tools are different enough that no confusion arises.

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

Parameters3/5

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

Schema covers 100% of parameters with descriptions, so baseline is 3. The description reinforces the overall purpose but does not add parameter-specific details beyond what the schema already states. The mention of stripping diacritics and tatweel corresponds to the default behavior, aligning with the text parameter description.

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 normalizes Arabic text, specifically stripping diacritics and tatweel and folding alef variants. It distinguishes itself from sibling lint/detection tools by focusing on normalization for matching and deduplication.

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

Usage Guidelines5/5

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

It explicitly provides usage guidance: use for search keys, deduplication, and matching, and explicitly warns never for display. This is a clear when-to-use and when-not-to-use directive, though it does not reference sibling tools, they are unrelated enough that no alternative is implied.

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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