Numerology MCP Server by RoxyAPI

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

Beyond the readOnlyHint=true and destructiveHint=false annotations, the description discloses return behavior (symbolic title, nature, full interpretation) and the sameAs pointer for numbers 33-52. It also clarifies the fadic number concept and the unreduced two-digit nature, which adds substantial context beyond what annotations provide.

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 well-structured, starting with the primary action and scope, then providing domain context, return details, and use cases. All four sentences add value without redundancy, making it concise yet informative.

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 lookup tool with no output schema, the description covers the return format (title, nature, interpretation), the number range, the special sameAs behavior, and the language support indirectly through schema. It is complete for an agent to understand what the tool returns and when to use it.

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 does not add much parameter-level detail beyond the schema; the only addition is the sameAs behavior for numbers 33-52, which mostly concerns return values rather than parameter semantics. No significant compensation needed.

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 gets the classical Chaldean interpretation of a compound number from 10 to 52, with a specific verb ('Get'), resource ('Chaldean interpretation of a compound number'), and scope. It also distinguishes itself from sibling tools by focusing on compound numbers versus other numerology calculations, and provides concrete examples like 'The Wheel of Fortune'.

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 ('Perfect for Chaldean numerology references, compound number lookups, and AI numerology tools') and explains what compound numbers are, but it does not explicitly contrast with alternative tools or state when not to use this tool. It lacks explicit exclusionary guidance, so it earns a 4 rather than 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 establish read-only non-destructive behavior. The description goes further by detailing the return content (archetype title, keywords, personality traits, strengths, weaknesses, career guidance, relationship dynamics, spiritual insights), master number handling, and word count (300-500 words), adding substantial behavioral context beyond the 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 front-loaded with the core purpose and uses five sentences to cover purpose, return details, master number behavior, and use cases. It is slightly redundant (the final sentence echoes the opening 'Get' and 'meanings'), but overall remains concise and scannable.

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 lookup tool with no output schema, the description explains what the response contains and the special master-number logic. Combined with the comprehensive parameter schema and safety annotations, it gives an agent sufficient information to invoke the tool correctly. Minor gaps like exact response structure or error behavior do not significantly undermine usability.

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% coverage for all three parameters (number, lang, compact) with descriptive text, patterns, and defaults. The description adds little beyond restating the valid number list, so it neither improves nor hurts parameter understanding; 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 clearly defines the tool as retrieving complete numerology meanings for numbers 1-9, 11, 22, 33 using Pythagorean numerology. It explicitly enumerates the exact scope and distinguishes this from sibling tools like compound-number and calculation-specific endpoints by focusing on static single-number interpretations.

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 specific use cases ('numerology reference tools, educational apps, quick lookups, and building custom numerology calculators'), giving clear context for when to invoke this tool. It does not explicitly name alternative tools or exclusion criteria, but the use-case framing is sufficient 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 declare readOnlyHint=true and destructiveHint=false, and the description adds valuable behavioral context: 'Automatically detects Master Numbers (11, 22) and reduces double-digit days' and explains return characteristics (300-500 word meanings). 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 front-loaded with the core purpose and includes useful details like output contents, master number handling, and word count. It is fairly concise, though the 'Perfect for' marketing sentence adds minor non-essential bulk.

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 compensates by detailing what the response includes (innate talents, career advantages, 300-500 word meanings) and special behavior (master numbers). It is sufficiently complete for the tool's complexity and parameters.

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 reiterates the day range (1-31) but adds no new parameter-specific meaning beyond what the schema already provides; it mainly reinforces the existing schema descriptions.

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 'Calculate your Birth Day number from the day you were born (1-31) using Pythagorean numerology' with a specific verb and resource. It distinguishes itself from siblings by focusing on Birth Day number and special talents, making the purpose 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 provides clear usage context: 'Perfect for talent discovery apps, career counseling platforms, personal development services, and skill assessment tools.' However, it does not explicitly mention alternatives or when not to use it, stopping just short of full exclusion 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 valuable behavioral context: the algorithm (absolute differences between specific core number pairs), the meaning of the result scale (0 = aligned, 1-8 = increasing tension), and the fact that four core numbers are computed internally before deriving bridges. It does not mention potential auth or rate limits, but these are not noted as concerns.

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 about 130 words and is efficiently structured: it starts with the core purpose, explains the bridge calculation, lists use cases, and ends with a data requirement. While slightly long, each sentence adds value and there is no redundant repetition of the title or schema.

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 what the tool does, the calculation logic, and the data requirements, but it lacks an explicit description of the return shape or output structure. Since there is no output schema, the description should clarify whether the three bridge numbers and their guidance are returned as a single object, an array, or in some other format. Without this, an agent may not know exactly what to expect from the response.

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 the parameters with detailed descriptions for each (fullName, year, month, day, lang, compact). The description reinforces the need for both name and birth date to compute the core numbers internally, but it does not add meaning to individual parameters beyond what the schema already 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 uses a specific verb-resource pairing ('Calculate three Bridge Numbers') and clearly defines the purpose ('reveal the adjustments needed to create harmony'). It explicitly lists the three pairs of core numbers involved, which distinguishes it from sibling tools that compute a single numerology number.

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 for when to use the tool ('essential for personal development, coaching applications, self-improvement platforms, and AI-powered personality analysis tools') and states the data requirement ('Requires both a full birth name and birth date'). It does not explicitly name alternatives or say when not to use it, but the use cases and prerequisite are sufficient 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 readOnly and non-destructive, and the description adds significant behavioral context: lists specific outputs (compound/root, planetary ruler, rating, industries, Cheiro compounds), cautions about numbers 4 and 8, and explicitly states 'not a guarantee.' No contradictions.

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?

All five sentences earn their place: definition, outputs, favorable/unfavorable roots, use cases, and caveat. Information is front-loaded and structured logically, making it easy to parse.

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 compensates by enumerating return values and providing decision-relevant context (which numbers are favorable vs. caution). Parameter count is small and schema-rich, so no additional context is needed.

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 covers 100% of parameters with clear descriptions for name, lang, and compact. The description adds no additional parameter-level detail, so baseline 3 applies as schema handles the semantics.

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: 'Analyze a business or brand name with Chaldean numerology' and specifies outputs like name number, planetary ruler, and business rating. It distinguishes from siblings by focusing specifically on business names and positioning guidance.

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 usage context: 'Use it to vet a company name, compare brand options, or guide a naming decision.' Does not explicitly name alternative tools or when not to use, but context is sufficient given the niche focus.

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 description goes well beyond the readOnlyHint annotation by explaining the computational approach (letters mapped to 1-8, 9 is sacred) and detailing the exact outputs (Destiny, Soul Urge, Personality, compound numbers, planetary ruler, caution flags). This provides rich behavioral context that annotations alone do not offer.

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 dense paragraph that front-loads the main purpose and then elaborates with useful system details. It's longer than the ideal two-sentence version but every sentence earns its place, with no filler 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?

With no output schema, the description compensates by enumerating the returned components (Destiny, Soul Urge, Personality, compound numbers, etc.) and explaining the Chaldean method. It's adequate for an agent to determine fit, though it doesn't discuss edge cases like invalid names or language fallback behavior.

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 already fully documents all three parameters (name, lang, compact) with 100% coverage. The description adds no new parameter-level detail beyond naming 'name' as the subject, so it adds no value beyond the schema. 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 'Calculate a complete Chaldean numerology reading for a name,' clearly identifying the action and resource. It differentiates from sibling tools by detailing unique Chaldean features like the unreduced compound number, planetary ruler, and karmic flags, making it distinct from other numerology 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?

Provides an explicit use case: 'Perfect for Chaldean numerology calculators, name analysis tools, and AI numerology assistants that need both the compound and root layers in one call.' It gives clear context but does not explicitly mention alternatives or when not to use it, so it falls 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, and the description adds valuable behavioral context by describing the return content: 'Returns detailed interpretations for all numbers, karmic analysis, yearly forecast, and holistic summary.' This goes beyond the annotations to inform the agent about what the response contains, 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?

The description is 5 sentences and includes some redundancy, such as 'This single endpoint provides everything needed' and 'Save multiple API calls' both conveying comprehensiveness. The core action is front-loaded, but the marketing-style phrases ('Perfect for numerology apps...') add length without substantive new 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 the tool's complexity (7 parameters, no output schema), the description compensates by listing all calculation components, the nature of the returns, and practical use cases. Combined with the schema and annotations, it provides sufficient context for an agent to decide when and how to invoke the 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%, with all 7 parameters having descriptions in the input schema. The description itself does not add parameter-specific details beyond what the schema already provides, so the baseline 3 is appropriate per the rubric.

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 'Generate a comprehensive numerology chart' and enumerates all included components (Life Path, Expression, Soul Urge, Personality, etc.), which unambiguously conveys its scope. It is distinguished from sibling tools that focus on individual numerology calculations, making the purpose specific and well-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 provides clear usage context by stating this 'single endpoint provides everything needed for a full numerology reading' and advising to 'Save multiple API calls by getting the full chart in one request.' It also lists ideal use cases like apps and PDF reports. However, it does not explicitly name alternative tools or describe when not to use it, so it falls short of the 'explicit when-not' bar.

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?

Beyond the readOnlyHint and destructiveHint annotations, the description discloses the exact weighting scheme (Life Path 50%, Expression 30%, Soul Urge 20%), output components (score 0-100, strengths, challenges, advice), and the ability to mix input modes across persons. It also mentions language fallback behavior ('Languages without translations yet return English'), providing rich 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 front-loaded with purpose and functionality, and despite being longer than ideal, it packs useful details. The final sentences about use cases and 'Get actionable insights' are somewhat redundant marketing language, but they don't significantly detract from clarity.

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 complex nested schema (person1/person2 with multiple optional fields), no output schema, and minimal annotations, the description is remarkably complete. It covers input mode options, flexible mixing, output structure, weightings, and application contexts, giving an agent sufficient information to invoke the tool 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?

The description adds meaningful high-level semantics not fully expressed in the schema: two input modes (pre-calculated numbers vs raw name/birthdate) and the ability to mix modes across persons. The schema already provides detailed per-field descriptions, but the description clarifies the overall usage pattern, which is valuable.

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 it 'Calculate numerology compatibility between two people using Pythagorean numerology' with a specific verb and resource. This distinguishes it from sibling tools that handle single-number or single-person numerology, making the tool's purpose 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 explicitly outlines use cases ('Perfect for dating apps, relationship counseling platforms, matchmaking services, and compatibility tools') and clarifies the tool's two-person scope. However, it does not explicitly mention alternatives or exclusions (e.g., 'for single-person numbers, use get_numerology_meanings_number'), so it misses the full 'when-not/alternatives' criterion.

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, but the description adds valuable behavioral detail: 'Uses seeded randomness so the same seed gets the same number on the same date' and describes the output content ('full interpretation including archetype, keywords, strengths, challenges, career, relationships, and spiritual insights'). This goes beyond the annotations and helps the agent understand determinism and output richness.

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 long, each adding value: purpose, determinism, output content, and use cases. It is front-loaded with the main function. It could be condensed slightly (e.g., the 'perfect for' and 'Ideal for' phrases overlap), but overall it is concise and 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?

With no output schema, the description does explain the return value ('number with full interpretation including...'). It also covers the key behavioral nuance (seeded determinism) and gives clear use cases. It does not mention error conditions or response shape beyond what the schema implies, but for a non-destructive read tool with a simple interface, this is sufficient.

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 fully documented in the input schema. The description does not add new parameter-level meaning beyond noting seeded randomness, which is also in the schema. Per the rubric, baseline 3 is appropriate when schema covers the parameters.

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: 'Receive a daily numerology number (1-9, 11, 22, 33) for guidance and reflection.' It also distinguishes itself from sibling tools by emphasizing 'daily' and 'Number of the Day', which is unique among the numerology siblings. The verb 'Returns' and the specific resource (daily number with interpretation) make the purpose 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 provides clear usage context: 'perfect for "Number of the Day" features in numerology apps, wellness platforms, and daily guidance tools' and 'Ideal for daily push notifications, morning briefings, and personalized numerology experiences.' It implies this is for generic daily guidance rather than specialized readings (e.g., life path, personal day), but it does not explicitly name alternatives or say 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, and the description adds rich behavioral context: letter mapping rules ('maps letters 1 to 9 in alphabetical order'), master number preservation ('preserves master numbers 11, 22, 33'), Chaldean specifics ('reads the compound number 10 to 52'), and return details ('returns both results with their interpretations, plus an agreement flag'). This goes well beyond the 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 longer than average but every sentence adds value: it explains both systems, the mapping rules, the return payload, and uniqueness. It is front-loaded with the core purpose. Slightly verbose, but appropriate for a dual-system tool with no output schema.

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 compensates by explaining return contents ('Returns both results with their interpretations, plus an agreement flag') and the core numerology logic. Combined with the detailed schema for parameters, this gives the agent enough to understand what the tool does and what it returns without gaps.

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 descriptions for name, lang, and compact. The description adds general context about the numerology systems, but it does not add new parameter-level semantics beyond what the schema already provides. Baseline 3 is appropriate because schema 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 states exactly what the tool does: 'Calculate a name number in both major numerology systems at once and compare them.' It specifies the resources (Pythagorean and Chaldean systems), the output (interpretations and agreement flag), and clearly differentiates from siblings by noting it is 'the only numerology API that returns Pythagorean and Chaldean for a name in a single request.'

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 usage context: 'ideal for comparison tools and AI numerology assistants' and highlights the unique value of a single request. However, it does not explicitly mention when not to use this tool versus using individual system tools (e.g., post_numerology_chaldean or post_numerology_expression), so the guidance is strong but not fully exhaustive.

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 indicate read-only and non-destructive behavior. The description adds valuable behavioral traits: automatic detection of Master Numbers (11, 22, 33) and the detailed nature of the output (300-500 word meanings, covering personality, career, relationships, spiritual insights). This goes beyond what annotations provide.

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 detailed but well-structured and front-loaded with the core purpose. It uses multiple sentences to convey use cases, output details, and Master Number handling, with no redundant filler. It is slightly longer than necessary but every sentence adds value.

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 the absence of an output schema, the description thoroughly explains what the response contains (comprehensive interpretation, personality traits, career paths, relationship dynamics, spiritual insights, and word counts). It is complete enough for an agent to understand the tool's capabilities, though it does not mention error conditions or language fallback behavior.

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 only mentions the full birth name parameter, which is already documented in the schema. It does not add additional meaning for 'lang' or 'compact' parameters, but the schema descriptions are sufficiently clear on their own.

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 the Expression (Destiny) number from the full birth name using Pythagorean numerology, with a specific verb and resource. It distinguishes itself from sibling tools like life_path and soul_urge by naming the specific calculation and its purpose (natural talents, life goals).

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 usage context (name numerology apps, career guidance, personal development, talent assessment) and implies when to use it, but does not explicitly mention when not to use it or differentiate from alternatives. This gives a strong sense of appropriate use cases without exclusions.

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 the safety profile. The description adds valuable context: the numbers 'appear during reduction', and it returns 'comprehensive analysis including debt descriptions, challenges to overcome, and resolution guidance.' This goes beyond what annotations provide and does not contradict 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?

The core purpose is front-loaded in the first sentence, but the description includes redundant marketing-like sentences ('Perfect for spiritual growth apps...', 'Get detailed meanings...') that restate earlier content. These do not help an agent select or invoke the tool, so the description is not as concise as it could be.

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?

Without an output schema, the description appropriately explains the return value ('Returns comprehensive analysis...'). It also explains the underlying concept (karmic debt, past life challenges, reduction). It does not fully address behavior with partial inputs (all parameters optional), but the schema covers that, and the description is sufficient for an AI agent to understand the tool's function 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 baseline is 3. The description's mention of Life Path, Expression, Soul Urge, and Personality maps to the date and fullName parameters, but the schema already explains these in each parameter's description. No additional parameter-level meaning is provided.

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 a specific action ('Check for Karmic Debt numbers (13, 14, 16, 19)') on a specific resource ('Life Path, Expression, Soul Urge, or Personality calculations using Pythagorean numerology'). This differentiates it from sibling tools like post_numerology_karmic_lessons by naming the exact numbers and calculation types.

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 the tool ('Check for Karmic Debt numbers', 'Past life challenges') and even lists applicable domains ('spiritual growth apps, karmic astrology platforms...'). However, it does not explicitly mention when not to use it or point to alternative tools, so it falls 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 cover read-only and non-destructive hints. The description adds behavioral value by detailing what the response contains: missing numbers, specific lessons, challenges, and practical guidance. It does not describe exact response structure or error behavior, but no output schema exists and the description carries the burden well.

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 front-loaded and readable, but the final sentence largely repeats the output details from the 'Returns comprehensive analysis...' sentence, and the 'Perfect for...' list is somewhat promotional. Minor trimming would tighten it.

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 3-parameter read-only tool with no output schema, the description is complete enough: it explains the data source, calculation basis, return contents, and typical use cases. It doesn't explicitly differentiate from karmic_debt, but sibling names and the detailed mechanism make the boundary clear.

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 parameter meaning is fully documented. Description adds no new parameter syntax beyond reinforcing that fullName is the birth name; 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?

Description opens with a specific verb and resource: 'Analyze your Karmic Lessons from your birth name using Pythagorean numerology.' It then defines the core mechanism (numbers 1-9 missing from the name), which clearly distinguishes it from sibling tools like karmic_debt or chaldean.

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 provides explicit context (Pythagorean numerology, birth name analysis) and target use cases ('Perfect for spiritual growth apps, personal development platforms...'). It does not name alternatives or exclusions, but the domain and input requirements imply when 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?

The description adds substantial behavioral detail beyond the readOnlyHint annotation, including automatic detection of Master Numbers (11, 22, 33) and Karmic Debt numbers (13, 14, 16, 19), the comprehensive interpretation categories (personality traits, strengths, challenges, etc.), and the 300-500 word length of meanings. This goes well beyond the safety hints provided by 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 that leads with the primary purpose, then explains significance, features, and use cases. Every sentence adds useful information without redundancy or filler. It is appropriately sized for the tool's richness.

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 thoroughly covers what the tool returns (comprehensive interpretation, personality traits, strengths, challenges, career guidance, relationship compatibility, spiritual insights) and its special behavior (Master/Karmic detection). This is complete enough for an AI agent to understand the tool's function and 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?

The input schema already provides 100% coverage and detailed descriptions for all parameters (day, month, year, lang, compact). The tool description adds no extra parameter-specific meaning, only mentioning 'birth date' in passing. Since schema coverage is high, 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 clearly states the tool calculates the Life Path number from birth date using Pythagorean numerology, with a specific verb ('Calculate') and resource scope. It distinguishes itself from sibling tools by calling it 'the most significant number' and detailing unique outputs like Master Numbers and Karmic Debt detection.

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 on when to use the tool, listing use cases like 'numerology apps, birth chart calculators, life purpose discovery tools, personal development platforms, and astrology services.' However, it does not explicitly mention when not to use it or name alternative tools, so it falls 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: it calculates by combining Life Path and Expression, automatically detects Master Numbers, and returns a 300-500 word interpretation covering specific themes. This goes beyond 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?

The description is well-structured and front-loaded with the core function, but it includes marketing language like 'Perfect for life coaching apps, midlife guidance platforms, personal development services, and aging wisdom tools' that doesn't help an AI agent invoke the tool. This adds unnecessary length for the agent's 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 appropriately explains the return value ('Returns comprehensive interpretation including life transformation, mature personality, later-life purpose, and wisdom development') and mentions the word count. It also explains the numerology concept and input alternatives. Logical constraints are covered by the schema, making this sufficiently complete for a read-only calculator.

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 all 8 parameters described in detail. The description adds little beyond noting that lifePath/expression can be computed from birth data or fullName, which is already in the schema. Since the schema does the heavy lifting, 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 your Maturity (Realization) number by adding Life Path and Expression numbers using Pythagorean numerology.' This clearly distinguishes it from sibling tools like post_numerology_life_path and post_numerology_expression, and the title adds the 'later life' context.

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 for when to use the tool: 'reveals who you become in the second half of life, typically manifesting after age 35-40' and mentions suitability for life coaching and midlife guidance. It doesn't explicitly name alternatives or when not to use, but the context is strong enough to guide an agent.

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 tool is known safe. The description adds valuable context about return content ('Returns the daily theme, actionable guidance, and parent month and year context') and explains the personalized nature. 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 five sentences, well-organized into what, concept, differentiation, returns, and use cases. It is not overly verbose, but the 'Perfect for' list is somewhat listy and could be trimmed. Still, each sentence earns its place and the structure is logical.

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 5 parameters, no output schema, and a moderately complex domain, the description covers the core purpose, the return value, and practical use cases. It doesn't explain all parameters, but the schema handles those. The description is complete enough for a read-only calculation tool, though a bit more detail on the output structure would push it to 5.

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 mentions birth month, day, and target date, which maps to three of the five parameters, but adds no semantic detail beyond what the schema already provides for lang or compact. It does not elevate the understanding of parameters 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 and resource: 'Calculate your Personal Day number from birth month, day, and a target date.' It clearly distinguishes this from sibling tools by noting it is 'the most granular cycle' and 'based on YOUR birth data combined with the calendar date', and contrasts with 'generic daily numbers' (post_numerology_daily). It also mentions 'parent month and year context', which separates it from personal month/year 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 provides clear context for use with the 'Perfect for' list (daily push notifications, morning briefings, etc.) and explicitly differentiates from generic daily numbers. However, it doesn't name alternative sibling tools or provide 'when not to use' guidance, so it stops short of a full 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?

Given readOnlyHint=true annotations, the description adds substantial behavioral detail: output includes comprehensive interpretation of public image, social dynamics, professional presence, relationship first impressions, and detects Master Numbers (11, 22, 33) with 300-500 word meanings. 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?

Description is well-structured and front-loaded with the core purpose, followed by useful output details and use cases. Slightly verbose due to the marketing-like 'Perfect for...' list, but every sentence contributes value.

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 sufficiently explains the return value's content and length. It mentions Master Numbers and interpretation categories, but does not describe the exact response structure (e.g., JSON fields). Adequate for an agent to set 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?

All parameters are fully described in the schema (100% coverage), providing clear semantics. The description adds no parameter-specific details beyond restating that consonants will be extracted, so it meets the baseline without enhancing 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?

The description clearly states it calculates the Personality number from consonants in the birth name using Pythagorean numerology, distinguishing it from sibling numerology tools. It specifies what the number reveals (outer personality, first impressions) and includes return characteristics.

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 context for use cases like personal branding and communication coaching, but does not explicitly compare with sibling tools or state when not to use. Lacks direct exclusions but gives clear application 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, so the safety profile is covered. The description adds useful context about the return values ('Returns the monthly theme, practical focus guidance, and the parent Personal Year context') but does not discuss error handling, limitations, or other behavioral details. This is decent but not extensive.

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 with no fluff. Each sentence contributes: what it does, what it reveals, what it returns, and when to use it. It is not as tight as a two-sentence description but is appropriately sized for the tool's complexity.

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 adequately explains the return values (monthly theme, guidance, parent Personal Year context). It also gives use cases. It does not describe the exact JSON structure, but for a simple numerology calculation with two required params and sensible defaults, this is complete enough.

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 summarizes the key parameters ('birth month, day, and a target year and month') but does not add new syntactical or semantic details beyond the schema. It does not explain 'lang' or 'compact', but those are already well documented in 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 starts with a specific verb and resource: 'Calculate your Personal Month number from birth month, day, and a target year and month.' It specifies the inputs and outputs, and the phrase 'within your Personal Year cycle' distinguishes it from sibling tools like post_numerology_personal_day and post_numerology_personal_year.

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 by listing concrete use cases: 'Perfect for monthly forecast features, push notification content, calendar integrations, editorial monthly columns, and life coaching tools.' It implies monthly-level forecasting, which contrasts with daily or yearly tools, but it does not explicitly state when not to use this tool or name 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. The description adds context about return contents (theme, opportunities, challenges, advice) and the 9-year cycle logic, which is useful but does not go deeper into potential edge cases or limitations. No contradiction.

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 core functional part is concise, but the concluding sentences 'Perfect for yearly planning apps...' and 'Get detailed forecasts for all 9 Personal Year cycles' are promotional and not essential for tool invocation. The description could be trimmed without losing key 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 the absence of an output schema, the description adequately explains what the function returns and the context of the 9-year Personal Year cycles. It is sufficient for an AI to understand the tool's role within the numerology family, though it doesn't address potential ambiguities like the 'all 9 cycles' phrase.

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%, with all parameters fully described in the schema. The description only repeats month/day/year without adding extra meaning beyond what the schema already provides, so baseline 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 clearly states 'Calculate your Personal Year number' with a specific verb and resource, and distinguishes from sibling tools like post_numerology_personal_day/month by emphasizing the annual cycle and forecast.

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 mentions target use cases like 'yearly planning apps' but provides no explicit guidance on when to use this tool versus alternatives such as post_numerology_personal_day or post_numerology_chart. The usage context is implied but not directly compared.

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 indicate read-only and non-destructive, so the description adds value by detailing what the tool returns: a comprehensive interpretation including traits, needs, desires, and spiritual longings, plus automatic Master Number detection and word counts. This goes beyond the structured fields and sets expectations for output richness.

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 front-loaded with the core calculation and then details the output, but repetition exists (e.g., 'reveals your innermost desires' and 'shows what drives you from within', 'Returns comprehensive interpretation' and 'Get detailed 300-500 word meanings'). The marketing sentence about use cases adds length but could be trimmed. It's not egregiously verbose but not maximally concise.

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 explaining the nature and length of the returned content (personality traits, emotional needs, etc., 300-500 words, all numbers 1-9, 11, 22, 33). It also sets user expectations for language fallback implicitly via the schema, and the tool is simple enough. Some minor gaps remain (e.g., what happens with invalid names), but overall it is complete for a read-only numerology calculation.

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 reinforces that the fullName parameter is used for vowel extraction, but the schema already states this. It adds no new parameter-specific detail 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 clearly states the tool calculates the Soul Urge number from vowels in the birth name using Pythagorean numerology. This specific verb+resource+method distinguishes it from sibling tools that calculate other numerology values (life path, personality, etc.).

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 use-case context ('Perfect for self-discovery apps, emotional intelligence tools, relationship counseling platforms, and personal development services') but does not explicitly name alternatives or when not to use it. It implies suitability based on the type of interpretation offered, which is enough for differentiation.

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