calc.engineer

duty cycle budget

duty_cycle_budget

Calculates LoRa duty cycle budget for EU868, US915, AS923, and AU915 regulatory regions. Computes maximum messages per hour, minimum transmission interval, and effective data rate under regional duty cycle constraints. EU868 and AS923 enforce 1% duty cycle (ETSI); US915 has no duty cycle limit but a 400 ms dwell time per channel (FCC); AU915 has no duty cycle limit. Flags dwell-time-limited regions where packet airtime must not exceed the dwell time. Chain from lora_airtime to get airtime_ms input for end-to-end regulatory compliance analysis.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`region`	No	LoRa regulatory region. EU868: 1% duty cycle (ETSI). US915: no duty cycle but 400 ms dwell time (FCC). AS923: 1% duty cycle (varies by country). AU915: no duty cycle limit.	EU868
`airtime_ms`	Yes	Packet time-on-air in milliseconds. Obtain from the lora_airtime tool.

Output Schema

TableJSON Schema

Name	Required	Description
`duty_cycle_pct`	Yes	Applicable duty cycle limit as a percentage. 100 means no duty cycle restriction.
`min_interval_s`	Yes	Minimum interval between transmissions in seconds to comply with duty cycle regulation.
`dwell_time_limited`	Yes	True if the region enforces a per-transmission dwell time limit (e.g., US915 400 ms).
`max_messages_per_hour`	Yes	Maximum messages per hour allowed under the regional duty cycle constraint.
`effective_data_rate_bps`	Yes	Effective throughput in bits per second considering duty cycle. For duty-cycle-limited regions, this reflects actual achievable throughput.

TDQS

A4.5/5.0

Behavior5/5

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

Despite no annotations, the description thoroughly explains the tool's behavior: it computes max messages per hour, min interval, effective data rate, and flags dwell-time-limited regions. It details region-specific constraints (ETSI 1%, FCC dwell time) without contradictions.

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?

Two well-structured sentences, front-loaded with purpose, no fluff. 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 the output schema exists, the description sufficiently covers inputs, processing logic, and outputs for a moderately complex tool. It provides region-specific rules and chaining guidance.

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 description coverage is 100%, so baseline is 3. The description does not add significant meaning beyond the schema's parameter descriptions; it only reiterates the region's duty cycle details and the airtime_ms source.

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 specifies the verb 'calculates' and the resource 'LoRa duty cycle budget', listing specific regulatory regions and computed outputs. It clearly distinguishes from sibling tools like lora_airtime and lora_param_optimizer.

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?

The description advises chaining from lora_airtime to obtain the required airtime_ms input, providing clear usage context. However, it does not explicitly state when not to use this tool or mention 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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