normalise_arabic

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

With no annotations provided, the description fully discloses behavioral traits: it describes Unicode NFC normalization, the effect of each boolean parameter (strip_diacritics, strip_tatweel, normalise_letters), notes that normalise_letters is lossy, and specifies the return type. This compensates for the lack of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with bullet points and clear sections (Args, Returns), but includes some redundancy (e.g., explaining tatweel as both 'elongation character' and 'kashida'). Still efficient and informative.

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

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

Given 4 parameters, no annotations, and an output schema (presumably simple), the description covers all relevant aspects: parameter defaults, optionality, lossiness, normalization steps, and return type. No gaps remain.

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

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

Despite the input schema having no descriptions (0% coverage), the description adds detailed semantics for each parameter in an 'Args' section, explaining what each boolean controls and the default values, far exceeding schema information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Normalise') and resource ('Arabic text'), lists specific operations (removing diacritics, tatweel, unifying letters), and clearly distinguishes from sibling tools like 'detect_dialect' and 'transliterate' which handle different tasks.

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

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

The description states what the tool does and the optionality of certain transformations (e.g., 'optionally'), but does not explicitly specify when to use this tool over siblings like 'strip_tashkeel' or 'transliterate'. However, the context makes it clear for normalization purposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.