calc.engineer

timestamp converter

timestamp_converter

Convert between Unix timestamps and human-readable date/time formats. Accepts Unix epoch (in seconds or milliseconds), ISO 8601 strings, or 'now' for the current time. Returns both Unix seconds and milliseconds, ISO 8601 UTC string, date and time components, day of the week, relative time description ('2 hours ago'), and past/future indicator. Auto-detects whether a numeric input is seconds or milliseconds based on magnitude. Essential for debugging logs, API timestamps, cron scheduling, and time zone conversions.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`value`	Yes	A timestamp to convert. Accepts Unix epoch (seconds or milliseconds), ISO 8601 string (e.g. '2024-01-15T10:30:00Z'), or 'now' for the current time.

Output Schema

TableJSON Schema

Name	Required	Description
`is_past`	Yes	True if the timestamp is in the past.
`iso_8601`	Yes	ISO 8601 formatted string in UTC (e.g. '2024-01-15T10:30:00.000Z').
`iso_date`	Yes	Date portion only (YYYY-MM-DD).
`iso_time`	Yes	Time portion only (HH:MM:SS).
`relative`	Yes	Human-readable relative time (e.g. '2 hours ago', 'in 3 days').
`day_of_week`	Yes	Day of the week (e.g. 'Monday').
`unix_seconds`	Yes	Unix timestamp in seconds since epoch (Jan 1 1970 00:00:00 UTC).
`unix_milliseconds`	Yes	Unix timestamp in milliseconds since epoch.

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 discloses key behaviors: auto-detection of seconds vs milliseconds, acceptance of various formats including 'now', and return of multiple time representations. No contradictory or missing critical behavior.

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?

The description is two sentences, front-loaded with the main purpose, followed by details on inputs, outputs, and use cases. No unnecessary words or repetition.

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 presence of an output schema (indicated by context), the description does not need to explain return values. It covers input types, behavior, and usage context, making it complete for an AI agent to select and invoke the tool.

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' has full schema coverage (100%). The description adds context beyond the schema by explaining auto-detection, format support, and the meaning of 'now', thus adding value.

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 between Unix timestamps and human-readable formats, lists input types and output components, and mentions auto-detection of seconds/milliseconds. This distinguishes it from sibling tools which are other calculators.

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 provides use cases like debugging logs, API timestamps, cron scheduling, and time zone conversions. It does not explicitly exclude scenarios or name alternatives, but the sibling list shows no overlapping tools.

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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