sanitize_persian_text

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

With no annotations, the description carries the full behavioral burden; it does disclose the specific normalizations performed, which is genuine behavioral content. It says nothing, however, about return semantics, idempotency, or whether unspecified content is preserved. Adequate but incomplete for an annotation-free tool.

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?

A single compact sentence that front-loads the primary case (ZWNJ/half-space) before secondary fixes. No filler. The dense domain jargon is appropriate for the audience and costs little.

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?

For a text-transformation tool with no annotations and no output schema, the description should clarify the return value and the relationship to the near-identical normalize_persian_text sibling. Neither is present, so an agent lacks enough to choose confidently.

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?

Schema description coverage is 0%, so the description must compensate, and it does not explicitly describe the input. Still, the single parameter "text" is self-evident given the tool's purpose, so meaning is not lost. Baseline-adequate rather than additive.

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?

States a specific verb ("Fix") and the exact resource it operates on: ZWNJ/half-space, می/نمی prefixes, plural suffixes, Persian punctuation and spacing, and Arabic letter variants. This is concrete and actionable. However, it never distinguishes itself from the sibling normalize_persian_text, which shares a nearly identical purpose, leaving ambiguity about which tool to pick.

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?

There is no indication of when to use this tool versus normalize_persian_text or slugify_persian, both of which operate on Persian text as well. No prerequisites, ordering, or exclusions are given. The agent must infer selection purely from the name and the transformation list.

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