calc.engineer

hex converter

hex_converter

Convert numbers between hexadecimal, binary, decimal, and octal bases. Accepts any base as input (prefix 0x for hex, 0b for binary, 0o for octal, or plain decimal) and returns all four representations simultaneously. Also reports bit width, byte count, ASCII character (if printable), and signed interpretations (8-bit, 16-bit, 32-bit two's complement). Essential for embedded programming, register debugging, network protocol analysis, and color code conversion. Example: 0xFF → decimal 255, binary 0b11111111, octal 0o377, 8 bits, 1 byte.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`value`	Yes	The number to convert. Prefix with 0x for hex (0xFF), 0b for binary (0b1010), 0o for octal (0o17). Plain numbers are treated as decimal. Supports negative values with leading minus.

Output Schema

TableJSON Schema

Name	Required	Description
`hex`	Yes	Hexadecimal string with 0x prefix (e.g. '0xFF').
`bits`	Yes	Minimum number of bits needed to represent this value (unsigned).
`ascii`	Yes	ASCII character if the value is a printable character (32-126), null otherwise.
`bytes`	Yes	Minimum number of bytes needed (ceil(bits/8)).
`octal`	Yes	Octal string with 0o prefix (e.g. '0o377').
`binary`	Yes	Binary string with 0b prefix (e.g. '0b11111111').
`decimal`	Yes	Decimal (base-10) value.
`signed_8`	Yes	Signed 8-bit interpretation (-128 to 127), null if out of range.
`hex_upper`	Yes	Hexadecimal with uppercase letters (e.g. '0xFF').
`signed_16`	Yes	Signed 16-bit interpretation (-32768 to 32767), null if out of range.
`signed_32`	Yes	Signed 32-bit interpretation, null if out of range.

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses input formats, output details (including bit width, ASCII, signed interpretations), and support for negatives. Missing edge case handling but sufficiently transparent.

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?

The description is well-structured, starting with the main action, then details, then example. It is informative but could be slightly more concise.

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?

For a single-parameter tool with no annotations and an output schema (implied), the description fully explains input format and output contents, making it complete.

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?

Schema coverage is 100% with parameter description. The tool description adds value by explaining prefix conventions and negative number support, going beyond the schema.

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?

The description clearly states the tool converts numbers between bases (hex, binary, decimal, octal) and lists additional outputs. It distinguishes itself from sibling calculator tools by specifying its unique function.

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 description implies usage contexts (embedded programming, register debugging, etc.) but does not explicitly state when to use this tool versus alternatives or provide exclusion criteria.

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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