calc.engineer

log calc

log_calc

Compute logarithms of a positive number in any base. Returns the custom-base logarithm, natural logarithm (ln), common logarithm (log10), and binary logarithm (log2). Useful for signal processing (decibel calculations), information theory (entropy in bits), pH chemistry, and general scientific computation. Uses the change-of-base formula log_b(x) = ln(x) / ln(b). Feeds into exponent_calc for inverse operations and scientific_notation for order-of-magnitude analysis.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`base`	No	The logarithm base (default 10). Must be positive and not equal to 1
`value`	Yes	The positive number to compute the logarithm of

Output Schema

TableJSON Schema

Name	Required	Description
`log2`	Yes	Binary logarithm (base 2) of the value
`log10`	Yes	Common logarithm (base 10) of the value
`result`	Yes	Logarithm of the value in the specified base: log_base(value)
`natural_log`	Yes	Natural logarithm (ln) of the value

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations, description fully discloses behavior: computes four logarithms via change-of-base formula, requires positive input. No contradictions or hidden side effects.

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 tightly written sentences: function, use cases, tool connections. Front-loaded with purpose, every sentence adds value.

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 low complexity and presence of output schema, description fully covers purpose, usage, behavior, and relations to siblings. No missing information for effective use.

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

Parameters3/5

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

Schema already describes both parameters (100% coverage). Description adds context about outputs but no new parameter-specific details beyond 'positive number' which matches 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?

Description uses clear verb 'Compute logarithms' and specifies resource 'positive number in any base'. Distinguishes from siblings by mentioning inverse operation (exponent_calc) and order-of-magnitude (scientific_notation).

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 concrete use cases (decibel calculations, entropy, pH) and explicitly links to sibling tools for related operations. Lacks explicit 'when not to use' guidance, preventing a perfect score.

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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