Biorhythm MCP Server by RoxyAPI

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

Annotations already mark the tool as read-only and non-destructive, which is consistent with the description. The description adds value by detailing that outputs include scores, rating, strengths/challenges, advice, and a daily sync snapshot, and that compatibility varies by day due to continuous cycles. This provides behavioral context beyond annotation hints.

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 two sentences: the first explains what the tool does and its output, and the second lists use cases. All information is relevant and front-loaded. It could be slightly more concise by avoiding the bullet list in prose, but still efficient and 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?

Given the moderate parameter count (5), nested objects, and no output schema, the description adequately explains inputs and outputs. It mentions all main return values (scores, rating, strengths, etc.) and the date-dependent nature. However, it does not specify whether all parameters are optional (e.g., targetDate defaults to today) or any error conditions, which is a minor gap.

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 60% (parameters like lang, compact, and targetDate are well-described in the schema). The description enhances understanding by explaining the purpose of person1/person2 and targetDate as 'overlaying their cycle profiles on a target date' and that compatibility varies by day. This compensates for the moderate schema coverage.

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 clearly states the tool calculates biorhythm compatibility between two people by overlaying cycle profiles on a target date. It lists specific outputs (scores for physical, emotional, intellectual cycles, overall score, relationship rating, etc.) and gives concrete use cases (dating apps, relationship platforms, team-building), distinguishing it from siblings like post_biorhythm_daily (individual reading) or post_biorhythm_phases (single person 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 implies this tool is for evaluating interpersonal compatibility and mentions use cases, but it does not explicitly state when to use this tool over alternatives (e.g., use this for two-person compatibility; for a single person's cycle, use other tools). No exclusions or prerequisites are given, leaving the agent to infer from sibling names.

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 annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is clearly safe. The description adds valuable behavioral context: the 180-day range limit, the return details (cycle name, period, direction, severity, advisory text), and the highlighting of rare double and triple critical days. This goes beyond the annotations and gives the agent a solid understanding of what to expect.

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 three sentences long, front-loaded with the primary purpose, and every sentence contributes unique information. The first sentence states the core behavior, the second details the output, and the third highlights rare events and use cases. No redundancy or fluff—excellent conciseness.

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?

Despite having no output schema, the description thoroughly explains the return values: each critical day includes cycle name, period, direction, severity, and advisory text. It also mentions the special handling of double and triple critical days. For a read-only tool with five parameters and straightforward behavior, this is complete and sufficient for an agent to understand the tool's capabilities.

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 five parameters have descriptions in the schema itself. The description does not add new semantic details about the parameters beyond what the schema provides (e.g., the 180-day limit is echoed from the endDate description). With full coverage, a baseline of 3 is appropriate; the description does not elevate or undermine parameter understanding.

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 begins with a clear verb+resource combination: 'Find all critical days (zero crossings) within a date range up to 180 days.' It precisely identifies the resource (critical days/zero crossings) and the action (find). The sibling tools cover biorhythm compatibility, daily, forecast, phases, and reading, so this tool's focus on zero-crossing detection is distinct and easily differentiated.

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 suggests ideal use cases such as 'calendar integrations, push notification systems, alert engines, and wellness scheduling tools,' which implies applicability but does not explicitly state when to use this tool versus the sibling tools (e.g., when to choose critical days over daily or forecast). There is no guidance on when not to use it or what alternatives exist. The usage context is implied but not explicit.

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. The description adds valuable behavioral context: deterministic behavior ('Same seed and same date always produce the same reading'), spotlight cycle selection, and the exact output structure. No contradictions 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?

The description is a single well-structured paragraph of about 100 words. It front-loads the main purpose and every sentence adds value, covering output content and use cases 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?

Despite no output schema, the description thoroughly lists all return fields (energy rating, overall phase, spotlight cycle, quick-read values, daily message, actionable advice). Combined with complete parameter documentation, the description provides enough context for an agent to understand the tool's behavior and output.

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 four parameters. The description adds minimal extra meaning beyond the schema (e.g., seed produces spotlight cycle variety). With high coverage, a score of 3 is appropriate as the description does not significantly enhance parameter understanding.

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 clearly states 'Get a daily biorhythm reading' with the key feature of seeded reproducibility. It distinguishes from sibling tools by specifying use cases like 'daily push notifications, morning briefings, and wellness app check-ins', which none of the siblings explicitly target.

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 explains when to use this tool (daily check-ins requiring consistency) but does not provide explicit guidance on when not to use it or how it differs from alternatives like post_biorhythm_reading. The usage context is clear, but exclusions are missing.

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. The description adds value by listing return components (daily cycle values, energy ratings, critical day identification, summary). No contradictions with annotations. Could disclose more about output format but sufficient given read-only nature.

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: first states action and output, second lists ideal use cases. Every sentence earns its place. No filler, front-loaded with purpose.

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, the description details return components (cycle values, energy ratings, critical day identification, summary with best/worst day). However, it does not describe the exact data structure or default shape of the response. The compact parameter is only explained in schema. Still fairly complete for a forecast tool.

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 parameters. The description adds no new information about parameters beyond stating 'date range up to 90 days', which is already in the schema. Baseline score of 3 is appropriate.

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?

Describes specific verb 'generate' and resource 'biorhythm forecast for a date range up to 90 days'. Distinguishes from siblings by mentioning multi-day range and forward-looking aspect, while sibling tools like post_biorhythm_daily or post_biorhythm_phases have different scopes.

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?

Provides clear context: 'Ideal for wellness apps, productivity planners, scheduling tools, and calendar integrations that need forward-looking biorhythm data.' However, it does not explicitly state when to avoid this tool or mention alternatives (e.g., use post_biorhythm_daily for a single day).

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 adds value by revealing the tool is lightweight/compact compared to siblings, explains what is NOT returned (editorial text, full interpretation), and specifies the compact parameter behavior. The only missing context is whether a request can fail for invalid birth dates, but this is a minor gap.

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 two sentences with clear structure: first sentence states purpose and data returned, second sentence specifies usage contexts and what is excluded. It is efficient without waste. One point off because the output data listing ('Returns value, phase name...') could be slightly more concise by mentioning 'compact summary' before listing the individual fields.

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?

The tool has no output schema, so the description must convey return values, which it does comprehensively by listing all 8 data types returned per cycle plus the compact summary string. With full schema coverage and good annotations, the description covers everything needed: what it returns, what it excludes (editorial), and typical use cases. No gaps remain.

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 adds meaning beyond the schema by explaining the tool returns compact data focused on phase details rather than interpretation. It mentions 'compact summary string' which relates to a schema parameter but with actionable context about the output shape. A 5 would require direct parameter usage examples tied to the description.

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 specific verbs ('Get') and a clear resource ('current phase information for all 10 biorhythm cycles') while immediately distinguishing itself from companions by noting 'without the full interpretation payload'. It lists exactly which data fields are returned, which eliminates any ambiguity about what the tool does.

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 explicitly states the tool is designed for dashboards, widgets, status bars, and quick-check interfaces needing lightweight data. It contrasts with sibling tools by saying 'without editorial text', implicitly telling the agent not to use this when human-readable interpretations are needed. A score of 5 would require explicit 'when not to use' or direct naming of alternatives.

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 clear. The description adds meaningful behavioral context: it returns 10 specific cycle names, 8 phase states, a 1-10 energy rating, and critical day alerts. This goes beyond annotation data. However, it doesn't mention performance implications (e.g., this is likely a heavier computation than simpler siblings) or any other caveats, so it's not a full 5.

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 single, dense paragraph of about 80 words. Every sentence adds value: the first sentence states the core action and parameters, the second lists all outputs comprehensively, and the third gives use-case context. No wasted words or repetition of schema information.

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 4 parameters (all described in schema), no output schema, and modest complexity, the description is quite complete. It covers what the tool does, its full output, and typical use cases. However, it doesn't explain the return format or structure (e.g., is it a JSON object with named keys?), which could be helpful for an agent deciding how to parse the response. The presence of the 'compact' parameter hints at shape options but isn't elaborated beyond schema.

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 baseline is 3. The description adds value by explaining that 'targetDate' defaults to today (UTC) if omitted and that 'lang' falls back to English for unsupported languages. The listing of all 10 output cycle values also gives context for how parameters shape results. However, it doesn't explain the 'compact' parameter's output shape in more intuitive terms beyond the schema's description.

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 ('Calculate') and resource ('complete biorhythm reading'), explicitly listing all 10 cycle values, phase detection, energy rating, and other outputs. It clearly distinguishes from siblings like post_biorhythm_daily or post_biorhythm_phases by emphasizing it returns a 'complete' cycle analysis with editorial interpretation, while siblings focus on subsets.

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 states when to use this tool: 'Perfect for wellness apps, dating platforms, productivity tools, and AI chatbot integrations that need structured biorhythm data.' It implies this is the comprehensive option, but it does not explicitly exclude when to use alternatives like post_biorhythm_daily or post_biorhythm_phases, leaving some ambiguity for an agent.

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