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Biorhythm MCP Server by RoxyAPI

Get biorhythm forecast - Multi-day cycle predictions with best and worst days

post_biorhythm_forecast
Read-only

Generate a biorhythm forecast for a date range up to 90 days. Returns daily cycle values for physical, emotional, intellectual, and intuitive cycles, daily energy ratings, critical day identification, and a summary with best day, worst day, average energy, and period-level guidance. Ideal for wellness apps, productivity planners, scheduling tools, and calendar integrations that need forward-looking biorhythm data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoResponse language (BCP 47). Supported: en, tr, de, es, hi, pt, fr, ru, zh-Hans, zh-Hant. Defaults to en. Coverage varies by domain, and a field with no translation in the requested language returns English.en
compactNoSet true for the same data in a compact shape: arrays of same-shaped objects arrive columnar as {"__cols":[names],"__rows":[[values]]}. Lossless, typically 40 to 52 percent fewer tokens.
endDateNoEnd date of the forecast range in YYYY-MM-DD format. Defaults to startDate + 30 days. Maximum range: 90 days.
birthDateYesBirth date of the person in YYYY-MM-DD format.
startDateNoStart date of the forecast range in YYYY-MM-DD format. Defaults to today (UTC).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysYes
endDateYes
summaryYes
birthDateYes
startDateYes
totalDaysYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "birthDate": {
      +      "type": "string"
      +    },
      +    "days": {
      +      "items": {
      +        "properties": {
      +          "criticalCycles": {
      +            "items": {
      +              "type": "string"
      +            },
      +            "type": "array"
      +          },
      +          "date": {
      +            "type": "string"
      +          },
      +          "daysSinceBirth": {
      +            "type": "number"
      +          },
      +          "emotional": {
      +            "type": "number"
      +          },
      +          "energyRating": {
      +            "type": "number"
      +          },
      +          "intellectual": {
      +            "type": "number"
      +          },
      +          "intuitive": {
      +            "type": "number"
      +          },
      +          "isCritical": {
      +            "type": "boolean"
      +          },
      +          "physical": {
      +            "type": "number"
      +          }
      +        },
      +        "required": [
      +          "date",
      +          "daysSinceBirth",
      +          "physical",
      +          "emotional",
      +          "intellectual",
      +          "intuitive",
      +          "energyRating",
      +          "isCritical",
      +          "criticalCycles"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "endDate": {
      +      "type": "string"
      +    },
      +    "startDate": {
      +      "type": "string"
      +    },
      +    "summary": {
      +      "properties": {
      +        "averageEnergy": {
      +          "type": "number"
      +        },
      +        "bestDay": {
      +          "type": "string"
      +        },
      +        "criticalDayCount": {
      +          "type": "number"
      +        },
      +        "periodAdvice": {
      +          "type": "string"
      +        },
      +        "worstDay": {
      +          "type": "string"
      +        }
      +      },
      +      "required": [
      +        "bestDay",
      +        "worstDay",
      +        "criticalDayCount",
      +        "averageEnergy",
      +        "periodAdvice"
      +      ],
      +      "type": "object"
      +    },
      +    "totalDays": {
      +      "type": "number"
      +    }
      +  },
      +  "required": [
      +    "birthDate",
      +    "startDate",
      +    "endDate",
      +    "totalDays",
      +    "summary",
      +    "days"
      +  ],
      +  "type": "object"
      +}
  2. Changed2 schema fields changed
    • changedInput schema / properties / lang / description
      Previous value: -"Response language (ISO 639-1). Supported: en, tr, de, es, hi, pt, fr, ru. Defaults to en. Languages without translations yet return English."New value: +"Response language (BCP 47). Supported: en, tr, de, es, hi, pt, fr, ru, zh-Hans, zh-Hant. Defaults to en. Coverage varies by domain, and a field with no translation in the requested language returns English."
    • changedInput schema / properties / lang / enum
      Previous value: -[
      -  "en",
      -  "tr",
      -  "de",
      -  "es",
      -  "hi",
      -  "pt",
      -  "fr",
      -  "ru"
      -]New value: +[
      +  "en",
      +  "tr",
      +  "de",
      +  "es",
      +  "hi",
      +  "pt",
      +  "fr",
      +  "ru",
      +  "zh-Hans",
      +  "zh-Hant"
      +]
  3. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "birthDate": "1990-07-15"
      +  }
      +]
    • changedInput schema / properties / compact / description
      Previous value: -"Set true to receive the exact same data in a token-optimized shape that is cheaper for you to read: whitespace is stripped and every array of same-shaped objects is encoded columnar as {\"__cols\":[field names],\"__rows\":[[values]]}, so each field name is sent once instead of once per row. Fully lossless (no field or value is dropped or changed) and typically 40 to 52 percent fewer tokens on large results. Prefer true whenever token or inference cost matters. Default false returns standard indented JSON."New value: +"Set true for the same data in a compact shape: arrays of same-shaped objects arrive columnar as {\"__cols\":[names],\"__rows\":[[values]]}. Lossless, typically 40 to 52 percent fewer tokens."
  4. Changed1 schema field changed
    • changedInput schema / properties / compact / description
      Previous value: -"Return the same data in a token-optimized compact shape (minified, with same-shaped arrays encoded columnar) to reduce LLM token cost. Lossless: no fields are dropped. Default false."New value: +"Set true to receive the exact same data in a token-optimized shape that is cheaper for you to read: whitespace is stripped and every array of same-shaped objects is encoded columnar as {\"__cols\":[field names],\"__rows\":[[values]]}, so each field name is sent once instead of once per row. Fully lossless (no field or value is dropped or changed) and typically 40 to 52 percent fewer tokens on large results. Prefer true whenever token or inference cost matters. Default false returns standard indented JSON."
  5. Changed1 schema field changed
    • addedInput schema / properties / compact
      Added value: +{
      +  "default": false,
      +  "description": "Return the same data in a token-optimized compact shape (minified, with same-shaped arrays encoded columnar) to reduce LLM token cost. Lossless: no fields are dropped. Default false.",
      +  "type": "boolean"
      +}
  6. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the read-only nature is covered. The description adds what data is returned but nothing about rate limits, auth, or other behavioral nuances. It does not contradict annotations and adds moderate context beyond the structured fields.

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 three sentences, front-loaded with the core function and then details. It avoids redundancy and marketing fluff, though the use-case sentence adds some value but is not strictly necessary. It is concise and well-structured.

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

Completeness4/5

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

With an output schema present and annotations covering safety, the description is largely complete. It explains the range, outputs, and use cases. It does not mention defaults like startDate defaults to today, but that is in the schema. Given the tool's complexity and available structured data, this is adequate.

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 the schema already documents all parameters. The description adds little beyond restating the date range limit ('up to 90 days') which is already in the schema. No additional parameter meaning is provided beyond what the schema gives, so baseline 3 is appropriate.

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 states a specific verb (generate) and resource (biorhythm forecast for a date range), and lists the exact outputs (daily cycle values, energy ratings, critical day identification, summary with best/worst day). It clearly distinguishes from siblings like post_biorhythm_daily (single day) and post_biorhythm_compatibility (pairwise) by emphasizing the multi-day range and summary components.

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 provides ideal use cases ('wellness apps, productivity planners...') which implies when to use it, but it does not explicitly state when not to use it or mention alternatives. It lacks explicit exclusions or comparisons to sibling tools, leaving some inference to the agent.

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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