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netintel_money

Normalize messy monetary strings into a typed decimal amount and ISO 4217 currency, handling symbols, locale separators, magnitude suffixes, accounting notation, and natural-language amounts.

Instructions

Normalize any messy money string into a typed decimal amount plus ISO 4217 currency — handles symbols, locale separators ($1,234.56 vs €1.234,56), magnitude suffixes (1.2M), accounting notation, and natural-language amounts — so agents can…

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
allow_llmNo
locale_hintNo
default_currencyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.61

TDQS

B3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose meaningful behavioral scope: locale separator disambiguation, magnitude suffixes (1.2M), accounting notation, and natural-language amounts. However, it says nothing about ambiguity handling, failure modes, or what the allow_llm fallback does when parsing is uncertain.

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

Conciseness3/5

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

The core purpose is front-loaded, but it is a single dense run-on sentence that reads as an incomplete fragment. The partial second clause ('so agents can…') is cut off, so the structure cannot be judged as fully earned.

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

Completeness2/5

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

No output schema and no annotations mean the description must cover both behavior and parameters. It does gesture at return values ('typed decimal amount plus ISO 4217 currency'), but three of four parameters and any ambiguity/failure behavior remain undocumented for a tool whose whole job is resolving messy input.

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 4 parameters, so the description must compensate. It only addresses the semantics of the required 'text' input; allow_llm, locale_hint, and default_currency are left completely unexplained in both the schema and the description.

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?

States a specific verb and resource ('Normalize any messy money string into a typed decimal amount plus ISO 4217 currency') and enumerates the input shapes it handles. It is clearly distinguished from unrelated siblings, though it never explicitly contrasts itself with the closest neighbors, netintel_currency_exchange (which converts between currencies) or netintel_convert.

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?

The enumerated messy formats imply when the tool applies, and the truncated trailing clause ('so agents can…') suggests usage framing was intended but is cut off. No explicit when-to-use vs alternatives such as netintel_currency_exchange is present.

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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