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Glama

format_short_number

Convert large numbers into compact Persian or Latin forms, such as ۲٫۵ میلیون or 2.5M, with optional units like تومان.

Instructions

Short Persian number form: 2500000 -> '۲٫۵ میلیون', 1200 -> '۱٫۲ هزار' (style 'latin' gives 2.5M). Optional unit like تومان.

Input Schema

NameRequiredDescriptionDefault
unitNo
styleNo
valueYes
maxFractionNo
persianDigitsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden, and it does disclose useful behavior via worked examples: the localized scale suffix (میلیون/هزار), the Persian decimal separator, the 'latin' style alternative, and unit appending. However, it says nothing about defaults, rounding/truncation behavior, invalid or negative input, or whether the result is a plain string.

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

Conciseness4/5

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

A single dense sentence with front-loaded purpose and inline examples; almost no waste. The parenthetical style aside is slightly compressed but still readable and earns its place.

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?

For a compact 5-parameter tool with no output schema and no annotations, the description gives enough to form a correct call (value + optional style/unit) and shows sample outputs. It remains incomplete on three parameters and on edge-case behavior, so it is adequate rather than thorough.

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% across 5 parameters, so the description must compensate. It covers 'style' (with the 'latin' enum value) and 'unit' (with a تومان example), but leaves 'value', 'maxFraction', and 'persianDigits' completely unexplained—a notable gap given the low schema coverage.

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

Purpose4/5

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

Names a specific operation (short/compact number formatting) and immediately grounds it with two concrete input→output examples, so the resource and the transformation are unambiguous. It does not explicitly contrast itself with the likely sibling format_number_grouped, so it falls short of 5.

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?

Usage is only implied by the word 'short' and the compact examples (e.g., UI labels, prices). There is no explicit when-to-use guidance and no mention of when to prefer format_number_grouped or number_to_persian_words instead, which are the obvious alternatives in the sibling list.

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