Human Design MCP Server by RoxyAPI

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

Annotations already mark it as read-only and non-destructive. The description adds behavioral context by calling it 'static reference data' and clarifying that no birth data is required, reinforcing the read-only nature and differentiating it from computation endpoints. 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?

The description is two sentences long, front-loaded with the verb and resource, and contains zero fluff. Every clause adds value by specifying the data fields and the endpoint's reference nature.

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 simple read-only lookup with rich schema and annotations, the description adequately covers purpose, data returned, and the distinction from chart computation. The language fallback and compact shape are documented in the schema, so no critical detail is missing.

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 covers 100% of parameters with detailed descriptions, enums, defaults, and examples. The description adds minimal parameter-specific meaning beyond referring to 'id' as one of nine centers; the schema already handles the heavy lifting.

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 looks up static reference data for one of the nine Human Design centers, specifies the exact data fields returned (display name, motor/awareness, defined/undefined meanings), and distinguishes it from the POST-based sibling tools that compute charts by noting 'no birth data required.'

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 phrase 'pure reference endpoint with no birth data required' implies it is for static lookups rather than chart calculations, but it does not explicitly name alternative tools or list exclusion criteria. The context is clear enough for an agent to select it for reference lookups.

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, and the description adds meaningful behavioral context by emphasizing 'static reference data' and 'no birth data required.' It also clarifies the data scope. While it doesn't discuss error cases or response format, the description goes beyond the annotations appropriately for a simple read-only endpoint.

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, front-loaded with the action and resource, and contains no unnecessary filler. Every clause earns its place, and the structure is easy to scan.

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 simple read-only lookup, the description completely conveys the purpose, the exact returned data (keynote, center, hexagram, channel gates), and the stateless nature. The schema handles all parameter details, and annotations cover the safety profile, so no critical information is missing.

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 provides detailed descriptions for all three parameters (number range, language enum with fallback, compact mode), yielding 100% coverage. The description adds minimal extra meaning beyond restating the gate number range (1-64), so the 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?

The description specifies a concrete action ('look up the static reference data') on a clear resource (Human Design gate by number from 1 to 64) and enumerates the exact returned fields (keynote name, center, I-Ching hexagram, channel gates). This makes it immediately distinguishable from sibling tools that compute bodygraphs or target centers.

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 this is a 'pure reference endpoint with no birth data required,' which implies it should be used for static lookups rather than the personalized post_* tools. It doesn't explicitly name alternative tools, but the context is clear enough for an agent to select it appropriately.

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, covering safety. The description adds value by specifying exactly what the tool returns (type, authority, profile, centers, channels, planetary activations) and by highlighting the 'single endpoint' behavior, which distinguishes it from multiple-call workflows. It does not contradict 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 three sentences, each with a distinct role: purpose, output contents, and positioning as the single full-chart endpoint. There is no redundancy or filler, and the most important information is front-loaded.

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 8 parameters, no output schema, and no nested objects, the description compensates for the missing output schema by enumerating the major return categories (centers, channels, gates, activations, etc.). It provides a solid overview for a complex tool, though it omits details on response structure or error handling. Given the schema already describes parameters well, this is a strong level of completeness.

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 100% parameter description coverage, including detailed explanations of date, time, timezone, nodeType, and compact. The description only restates that it takes birth date, time, and timezone, adding no new meaning beyond the schema. Baseline 3 is appropriate because the schema carries the semantic load.

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 'Generate a complete Human Design bodygraph from a birth date, time, and timezone,' which names the specific verb and resource. It further distinguishes itself from siblings with 'The single endpoint for a full chart in one call,' making clear it is the comprehensive chart endpoint among the more specialized post_human_design_* 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 states it is 'The single endpoint for a full chart in one call, built for Human Design apps, readings, and coaching tools.' This signals that it is intended for full-chart retrieval and implies that sibling tools are for narrower queries. It does not explicitly name alternatives or when-not-to-use, but the context is sufficient for an agent to choose it when a complete bodygraph is needed.

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 meaningful behavioral context by specifying what is calculated for each center and that this is the raw data layer, which goes beyond the annotations without contradicting them.

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, no wasted words. The first packs the core function and outputs, the second provides valuable context about the tool's role relative to a rendered bodygraph.

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 clearly and sufficiently enumerates the return contents: defined/open state, motor/awareness, theme, and active gates for each center. Combined with the rich parameter schema, the tool is fully understandable for invocation.

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% with detailed descriptions for all 8 parameters, so the description does not need to add parameter-level meaning. The description mentions 'birth moment' as context, but does not elaborate on parameters themselves—acceptable given the schema carries the burden.

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') with a precise resource ('the state of all nine Human Design centers') and enumerates the computed attributes (defined/open, motor/awareness, theme, active gates). It also differentiates from sibling tools by framing itself as 'the data layer behind a rendered bodygraph' rather than the rendering itself.

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 provides clear context: this is the underlying data for a bodygraph view where centers are colored or white. However, it does not explicitly name alternatives or state when not to use this tool, relying instead on the implied use case.

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 the channel definition rule and return shape, but no further behavioral traits like error handling, timezone sensitivity, or response format nuances. This is acceptable given the annotations, but not rich.

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?

Three sentences, with the core purpose front-loaded in the first sentence. Each sentence earns its place: definition, return contents, and intended use case. No fluff or repetition.

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 description covers the essential logic and return shape, and the rich schema handles all parameter details. It is complete enough for an agent to understand what the tool does and what it returns, though a touch more explicit usage context (e.g., how it complements other HD tools) would make it fully complete.

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%, and the tool description does not mention parameters at all. Per the rubric, baseline 3 applies because the schema already documents all 8 parameters thoroughly; the description adds no extra semantic value.

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 the specific verb+resource 'Calculate the defined channels for a birth moment' and explains the definition rule (both gates activated), making the tool's purpose unmistakable. It also lists what the tool returns (gates, name, circuit family, centers), distinguishing it from sibling tools for centers, gates, or the full bodygraph.

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?

'Built for bodygraph rendering and definition analysis' gives clear intended-use context, indicating when an agent would need this tool. However, it does not explicitly name alternative tools or state when not to use it, stopping short of full usage guidance.

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 meaningful behavioral detail beyond that: it reveals the classification mechanics (four dynamics), the combined definition output, and the center-level breakdown. It does not mention rate limits or auth, but since annotations cover the safety profile, this additional output-focused transparency is a solid contribution.

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 relatively concise (three sentences) and front-loaded with the core action. It packs in essential details about outputs and use cases without fluff. It is slightly longer than strictly necessary but every sentence serves a purpose: action/method, core output mechanics, and intended context.

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 of outlining the main return content (channel dynamics, center definition, combined definition, counts). It does not describe the exact response shape or error handling, but for a read-only composite tool with detailed input schema, this is reasonably complete. The use-case guidance and output enumeration help an agent know 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?

The input schema has 100% coverage of all parameters with rich descriptions, so the baseline is 3. The description does not add parameter-specific semantics beyond what the schema already provides — it does not explain lang, compact, or the person subfields in a way that would change an agent's behavior. It simply restates the purpose at a high level.

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 ('Human Design connection chart by overlaying two bodygraphs'), clearly distinguishing this from sibling tools like post_human_design_bodygraph (single-person chart) and post_human_design_penta (group composite). It also enumerates the exact outputs (36 channel dynamics, nine centers, combined definition, counts), leaving no 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 it is 'Built for relationship, dating, and coaching tools,' giving clear use-case context. It does not explicitly name alternatives or exclusions (e.g., 'use penta for more than two people'), but the title and mention of 'two-person composite' make the intended scope clear. This is strong contextual guidance without explicit when-not-to-use instructions.

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 establish read-only, non-destructive behavior. The description adds non-obvious behavioral detail: the 88-degree solar arc offset for Design activations and the specific contents of each activation report (planet, gate, line, keynote, I-Ching hexagram). It doesn't cover edge cases, but meaningfully supplements the annotation baseline.

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?

Three sentences, each carrying distinct information: first explains the split and solar arc, second enumerates output fields, third states intended use. Starts with the core action and contains no redundant or filler text.

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 an 8-parameter tool with no output schema, the description covers the essential calculation logic and return payload, plus a usage context. It doesn't discuss error handling, response shape beyond the activation fields, or how the optional location params are ignored, but the schema covers the parameter behaviors. Slight gaps remain around return format, so 4.

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%, and each parameter already has a detailed description (formats, defaults, effects, edge cases). The tool description only restates 'birth moment' and does not add new meaning beyond what the schema already provides, so the baseline 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?

The description uses a specific verb ('Calculate') and clearly identifies the resource ('the 26 gate activations'), the input ('a birth moment'), and the internal split (13 conscious + 13 unconscious). It also lists the exact output fields per activation. This strongly distinguishes it from sibling tools like get_human_design_gates_number and post_human_design_bodygraph.

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 final sentence, 'Built for activation columns and detailed chart views,' gives a clear context for when this tool is appropriate. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of a 5.

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 valuable behavioral context by enumerating exactly what the Penta calculation reports (filled gates, defined channels, leadership vs. generative channels, material core, functional gaps), which goes beyond the structured 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 four sentences and front-loads the main purpose. Each sentence adds meaningful detail about scope, outputs, and constraints. It is compact without being overly terse, covering the essential information in a readable structure.

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?

No output schema exists, so the description must convey what the tool returns. It does so comprehensively by listing the report dimensions: filled gates, defined strengths, upper vs. lower channels, 2/14 material core, and functional gaps. It also includes the critical size limitation. This is complete for the tool's 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 parameters (lang, compact, members) are already documented in detail. The description adds the conceptual rationale for the members constraint (min 3, max 5) but does not introduce new parameter syntax or meanings beyond what the schema provides. Baseline 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?

The description opens with a specific verb and resource: 'Calculate the Human Design Penta (BG5, Base Group 5) for a small group of three to five people.' It clearly identifies the tool's purpose and scope, and the details about gates, channels, and group size distinguish it from sibling tools that handle individual charts or other aspects.

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 'Built for team, family, and group analysis tools' and provides clear size constraints: 'Below three people no Penta forms and above five a second Penta emerges.' This gives strong contextual guidance, though it does not explicitly name alternative tools for individual analysis.

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 context about the calculation method (the two Sun lines) and a quality claim ('Verified against NASA JPL Horizons positions'), but it does not disclose any additional behavioral traits such as return format, error handling, or rate limits. It adds some value beyond annotations but not rich behavioral detail.

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 the primary action front-loaded in the first sentence. It provides essential information (what is calculated, an example, and a verification claim) without any redundancy or filler. Every word contributes to understanding the tool.

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 complexity of the tool (8 parameters, 3 required) and the fact that all parameters are well-documented in the schema, the description is sufficient for an agent to understand what the tool does and when to use it. It includes an example output format ('5/1 the Heretic Investigator') which hints at the return value. However, it does not cover all edge cases like how the profile is affected by nodeType, but that detail is available in the schema. Overall, it is complete enough for effective tool selection and invocation.

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 100% parameter coverage with detailed descriptions for each parameter. The tool description itself does not add any parameter-specific information; it focuses solely on the tool's purpose and output concept. With such high schema coverage, the baseline of 3 applies – the schema does the heavy lifting and the description adds no extra semantic value.

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's purpose: 'Calculate the Human Design profile for a birth moment' and provides specific details about what the profile is (conscious Personality Sun line over unconscious Design Sun line). It distinguishes from sibling tools by focusing on the profile and gives a concrete example ('5/1 the Heretic Investigator'), making it unambiguous.

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 on what the tool calculates and even mentions verification against NASA JPL Horizons, which sets expectations for accuracy. However, it does not explicitly name alternatives or state when not to use this tool versus siblings like post_human_design_bodygraph or post_human_design_type. The purpose is clear enough that usage is implied, but no exclusions are given.

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 context about the transit's instantaneous nature ('A transit is a single moment, so there is no Design side'), the channel categorization (personal vs educational), and the output components. It does not contradict 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 moderately long but front-loaded with the core action. Each sentence adds either purpose, output detail, or usage context, with no filler. It is slightly verbose but well-structured.

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?

There is no output schema, so the description responsibly enumerates what is returned (13 activations, personal/educational channels, open centers, summary). It also covers the temporal default and the absence of a Design side. The nested birthData parameters are fully documented in the schema, so the description does not need to repeat them.

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 only a note about date/time defaults, which is helpful but not essential 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 specific verb ('Overlay') and resource ('natal Human Design bodygraph'), and explains the goal ('see which channels the transit temporarily completes'). It also enumerates the exact outputs, distinguishing it from sibling tools like post_human_design_bodygraph and post_human_design_channels.

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 states intended use cases ('Built for daily Human Design apps, transit widgets, and notification tools') and clarifies the default behavior ('When date and time are omitted the overlay is computed for now in UTC'). However, it does not explicitly contrast with alternatives or state when not to use it.

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 context by stating the tool is verified against NASA JPL Horizons positions and is a fast lookup, which informs the agent about accuracy and performance. 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 three sentences, each with a distinct purpose: listing outputs, stating the tool's scope/positioning, and establishing verification. It is front-loaded and free of filler words.

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 enumerates the returned fields, which is helpful for the agent. It also clarifies the scope relative to the bodygraph. It does not describe the return format in detail, but for a calculation tool with explicit outputs, it is adequate.

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 provides 100% parameter description coverage, so the description does not need to repeat parameter meanings. The description's mention of 'birth moment' and 'type-and-authority features' aligns with the main parameters but adds little 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 uses a specific verb ('Calculate') and clearly identifies the resource and outputs: energy type, aura strategy, inner authority, signature and not-self themes, and profile. It also distinguishes this tool from siblings by highlighting that it is 'the fast lookup for type-and-authority features without the full bodygraph payload'.

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 a clear use case: use this when you need type-and-authority features without the full bodygraph. It does not explicitly mention when not to use alternatives like post_human_design_profile, but the 'fast lookup' positioning implies the appropriate 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?

Annotations already state readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds crucial behavioral context beyond annotations: 'Color, Tone, and Base shift with tiny differences in birth time, so each arrow carries a confidence flag that turns false near a Color or Tone boundary, and a precise birth time is essential.' It also details return structure (Color, Tone, Base numbers, direction), which is valuable given no output schema.

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 five sentences, each with a distinct purpose: purpose, return structure, context, confidence flag caveat, and use case. Every sentence earns its place, and there is no redundant fluff. Dense but well-organized and front-loaded with the core 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?

Given 8 parameters, no output schema, and no nested objects, the description is comprehensive. It explains what the tool returns (arrows with Color, Tone, Base, direction), the sensitivity to birth time, the confidence flag behavior, and the intended application. It leverages the schema's detailed parameter descriptions for the rest, making the combination complete.

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 baseline is 3. The description does not add parameter-specific semantic details beyond what the schema provides. It mentions birth time sensitivity ('precise birth time is essential') but does not elaborate on format or timezone handling, which the schema already covers thoroughly. Thus no additional value beyond baseline.

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's function: 'Calculate the four Human Design Variable arrows for a birth moment' and enumerates the exact arrows (Determination, Environment, Perspective, Motivation). It distinguishes this tool from siblings by positioning it as 'the advanced Rave Variables and Primary Health System layer beneath Type, Strategy, Authority, and Profile', making it unmistakably different from bodygraph, centers, or type 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 to use this tool: 'Built for Human Design apps offering PHS, diet, environment, and Rave Psychology readings.' It implies this is for advanced variable calculations, but it does not explicitly name alternatives or say when NOT to use it. Since it provides clear use cases without exclusions, it earns a 4.

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