Biorhythm MCP Server by RoxyAPI

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

The description discloses what the operation does beyond the readOnlyHint: it overlays cycle profiles on a target date and returns computed alignment scores, an overall score, rating, and detailed narrative outputs. It also flags that compatibility is date-dependent. There is no contradiction with annotations, and no hidden mutation is implied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: the first sentence states what the tool does and the target input, the second sentence lists key outputs, and the third sentence gives actionable use cases. Every sentence contributes context without redundancy.

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

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

Even though there is no output schema, the description enumerates the important return fields: per-cycle scores, overall score, relationship rating, strengths/challenges, advice, and daily sync snapshot. Combined with the schema's detailed parameter documentation, an agent has enough guidance to invoke the tool and interpret its result.

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

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

The input schema has descriptions for targetDate, lang, compact, and birthDate nested under person1 and person2, but schema description coverage is only 60%. The description adds little parameter-specific detail beyond mentioning the target date. It does not explain compact mode, language behavior, or person-object shape, so it doesn't significantly compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with a specific verb and resource: 'Calculate biorhythm compatibility between two people by overlaying their cycle profiles.' This clearly distinguishes it from the sibling biorhythm tools, which are single-person daily, forecast, phases, or critical-day calculations. It also specifies the main output categories, so an agent can recognize the intended operation quickly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear use contexts such as dating apps, relationship platforms, team-building tools, and couples coaching. It does not explicitly list alternative sibling tools or exclusion criteria, but the 'between two people' phrase and the compatibility focus make the intended scenario evident. A small gap is that it never says 'use a single-person biorhythm tool if there is only one person.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description goes beyond annotations by explaining the zero-crossing detection behavior, the severity categories, and the special highlighting of double and triple critical days, which is genuinely useful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, stating the core operation in the first sentence. The second and third sentences add valuable output and use-case context without wasted wording, though the final use-case list could be trimmed without losing essential meaning.

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

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

Even without an output schema, the description lists the key return fields: critical day, cycle name, period, direction, severity, and advisory text. Parameters are fully covered by the schema, and the date-range limit is stated. Together this is enough for correct call construction and reasonable response expectations.

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

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 five parameters, including formats, defaults, and language enum. The description adds context about the 180-day range and the nature of critical days, but it does not add significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a precise operation, 'Find all critical days (zero crossings) within a date range up to 180 days,' which names the resource, action, and scope. It also lists the returned information, including severity and direction, making it easy to distinguish from the sibling biorhythm tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when the tool is appropriate: date-range searches for critical days, up to 180 days. It also names ideal use cases like calendar integrations, push notifications, alert engines, and wellness scheduling. It does not explicitly exclude alternatives or name a sibling to use instead, but the context is strong enough for agent selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), and the description adds genuine behavioral value beyond them: seeded determinism ('Same seed and same date always produce the same reading'), deterministic spotlight selection, and the return contents. It does not disclose rate limits or server-side state, but for a non-destructive read with readOnly annotations, the disclosure is more than adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a tight, well-ordered four sentences: first the core purpose, then the determinism premise, then the output contents, then the variation/per-user nuance. There is a mild redundancy ('Same seed and same date always produce the same reading' vs. 'The spotlight cycle is deterministically selected by the seed'), but it earns its place by clarifying variety across users while staying stable for one user. No filler.

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

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

With no output schema present, the description compensates well by enumerating the returned content (energy rating, overall phase, a featured cycle, quick-read values, daily message, actionable advice). All four optional parameters are fully documented in the schema, the language fallback behavior is captured in the lang parameter, and the use case is fully described. Only edge-case or error behavior is not addressed, but that is a minor gap for a read-only tool of this complexity.

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

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

Schema description coverage is 100%, so all four parameters (date, lang, seed, compact) are already documented including defaults, formats, and enum values. The description mostly re-states the seed property that the schema already explains ('Same seed + same date = same reading every time'), adding little alignment beyond it. Baseline 3 applies because the description does not need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource ('Get a daily biorhythm reading') and immediately scopes it to the 'daily check-in' feature niche, distinguishing it from siblings like post_biorhythm_reading, compatibility, forecast, and critical_days. The daily/seed framing makes the differentiation obvious even without reading the sibling schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly names when to use the tool ('perfect for daily push notifications, morning briefings, and wellness app check-ins'), so an agent can route the right feature here. It does not explicitly name alternatives or say 'use post_biorhythm_reading instead when you need X', but the implied usage context is strong enough to leave only a minor gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds useful behavioral detail by describing the exact forecast payload: daily cycle values, energy ratings, critical days, and a summary with best/worst day and average energy, which is valuable because no output schema is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficient and front-loads the 90-day forecast scope before outlining outputs. The first sentence is somewhat packed with output details, but this is generally justified in the absence of an output schema. The 'ideal for' sentence adds practical context without significant bloat.

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

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

Given there is no output schema, the description does a good job describing what the forecast includes: daily cycle values, energy ratings, critical days, and a summary. It could more explicitly differentiate from post_biorhythm_daily or post_biorhythm_critical_days, but the title and content supply enough orientation for most agents to invoke it correctly.

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

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

schemata description coverage is 100%, meaning every parameter already has a description, defaults, formats, and enums in the schema. The tool description does not add meaningful parameter semantics beyond what the schema documents, so the baseline score of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and object: 'Generate a biorhythm forecast for a date range up to 90 days.' It also enumerates the returned content including daily cycle values, critical day identification, best/worst day, and average energy, so an agent can distinguish this from single-day or critical-days siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear intended use context: wellness apps, scheduling, productivity planners, and calendar integrations needing forward-looking biorhythm data. It does not explicitly state when not to use it or name alternatives such as post_biorhythm_daily or post_biorhythm_critical_days, but the multi-day framing provides workable context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

The annotation readOnlyHint=true already signals basic safety, and the description adds far more behavioral context: it lists the returned data (phase name/label, day position, cycle, days until cross, tie) and confirms a compact summary string without editorial text. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded purpose, then the complete returned field list, and then the target use case. No wasted words; every sentence earns its place.

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

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

For a read-only, read-only lightweight endpoint, the description gives enough to select and invoke it correctly: what is returned, what is not covered, and which consumer intents it fits. The schema fills the parameter details and annotations supply the safety profile.

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

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

Because schema description coverage is 100 for all four paramameters — birthDate, targetDate, lang, compact — the schema carries the full parameter semantics. The description adds no parameter-specific guidance, but it isn't needed to be in the schema definition all already covers it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

"Get current phase information for all 10 biorhythm cycles without the full interpretation payload" states the exact action and resource. It clearly differentiates from the reading-type siblings by emphasizing the lightweight, no-editorial-data nature. The title also separates it from dashboards and widgets.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Designed as lightweight endpoint for dashboards, widgets, status bars, and quick-access interfaces" offers clear consumption context, and the mention of the "full interpretation payload" implicitly routes users toward the heavier reading endpoint. It does not explicitly name sibling alternatives, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

There is no contradiction with readOnlyHint/destructiveHint, since the tool only calculates and returns values. The description adds useful behavioral detail beyond annotations: specific cycle outputs, phase states, energy rating, interpretation, advice, and critical-day alerts, which helps the agent know what to expect from the response.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one substantive sentence followed by a short use-case sentence. It front-loads the verb and inputs, and the list of return values is valuable for selecting and invoking the tool correctly. The second sentence is mildly promotional but compact.

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

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

Given there is no output schema, the description compensates by enumerating the result dimensions: all cycles, phase states, energy rating, interpretation, advice, and critical alerts. It is sufficiently rich for an agent to select and invoke this calculation tool. The main minor gaps are exact output field names and JSON shape, which are not critical for invocation because the description already conveys what to expect.

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

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

Schema coverage is 100%, so the baseline is 3. The description correctly mentions birthDate and targetDate, but adds no meaning beyond what the schema and its parameter descriptions already state. lang and compact are thoroughly documented in the schema, so the description is not required to repeat them.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource ('Calculate a complete biorhythm reading') and names the core inputs (birthDate, targetDate). It enumerates the 10 cycle values and assessment components, which makes it distinct in substance from siblings, but it does not explicitly name or contrast with sibling tools like post_biorhythm_daily or post_biorhythm_phases.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear use-context ('wellness apps, dating platforms, productivity tools, AI chatbot integrations') and implies a need for full structured biorhythm data. However, it never says when to prefer this tool over the sibling variants or when not to use it, so the guidance remains implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.