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scientific notation

scientific_notation

Convert any number to scientific notation and engineering notation. Returns the coefficient, exponent, a formatted string with Unicode superscripts (e.g. '3.14 × 10²'), and engineering notation where the exponent is a multiple of 3. Useful for expressing very large or very small values compactly, common in physics, electronics (picofarads, gigahertz), and astronomy. Accepts output from sig_figs and log_calc for precision-aware formatting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYesThe number to convert to scientific notation

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
exponentYesThe power-of-10 exponent
coefficientYesThe coefficient (mantissa) between 1 and 10
notation_stringYesFormatted scientific notation with Unicode superscripts (e.g. '3.14 × 10²')
engineering_notationYesEngineering notation with exponent divisible by 3

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description fully explains the tool's behavior: it converts a number and returns specific fields. It is non-destructive and simple. Could mention error handling, but the scope is well-covered.

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?

Three sentences, front-loaded with the main action, no fluff. Every sentence contributes purpose, behavior, or usage context.

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

Completeness5/5

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

Given the tool's simplicity and availability of output schema, the description covers return format, use cases, and interoperability with sibling tools. It is fully informative for an agent.

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

Parameters4/5

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

The single parameter 'value' is described in schema. The description adds value by stating it can accept outputs from sig_figs and log_calc, implying it handles precision-aware numbers, which goes beyond the schema 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?

Clearly states it converts numbers to scientific and engineering notation, lists returned fields (coefficient, exponent, formatted string, engineering notation), and explicitly mentions it accepts output from sig_figs and log_calc, distinguishing it from siblings.

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

Usage Guidelines4/5

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

Provides clear use cases (very large/small values, physics, electronics, astronomy) and mentions compatibility with sig_figs and log_calc for chaining. However, it lacks explicit when-not-to-use instructions or alternatives.

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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TDQS

A3.9/5.0
Disambiguation4/5

Despite 89 tools, each has a clearly distinct purpose with detailed descriptions that often reference related tools. Overlap exists (e.g., multiple LoRa/RF tools), but the descriptions are sufficient to distinguish them. Some confusion possible among similar-sounding tools like attenuator_pi and attenuator_tee, but the descriptions explicitly compare them.

Naming Consistency4/5

Consistent underscore-separated lowercase naming. Most tools follow a verb_noun pattern (e.g., capacitor_charge, wire_gauge) or noun_noun (power_cost). Minor inconsistencies such as 'bmi_calculator' vs 'solar_sizing' but overall predictable.

Tool Count2/5

89 tools is far too many for a single MCP server. This scope is more appropriate for multiple specialized servers. The sheer number will slow agent selection and increase cognitive load, reducing coherence.

Completeness3/5

Covers many domains (RF, solar, PCB, networking, math, etc.) but lacks depth in some areas (e.g., no three-phase power, no airflow calculations). Some domains have comprehensive coverage (LoRa/Meshtastic), but others feel incomplete for the tool count.

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