Numerology MCP Server by RoxyAPI

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

Describes special behavior: 'Numbers 33 to 52 share the meaning of a lower number... returned with a sameAs pointer.' Also specifies return fields: title, nature, interpretation. No annotations, but disclosure is sufficient for a simple read tool.

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?

Four sentences, each essential: purpose, range, output details, special case, and use case. Front-loaded with action. No fluff.

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 no annotations and no output schema, description covers purpose, range, output structure, and special behavior. Lacks mention of error handling or auth, but adequate for a simple read 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 coverage is 100% with descriptions for each parameter, so baseline 3. Description adds value by explaining the tool's purpose and output, though no extra parameter-specific details.

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?

Clear verb 'Get', specific resource 'classical Chaldean interpretation of a compound number', explicit range 10-52, and source 'Cheiro'. Distinguishes from siblings that handle other numerology 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?

States use cases: 'Perfect for Chaldean numerology references, compound number lookups, and AI numerology tools.' Implicitly suggests this is for compound numbers only, though no explicit alternative comparison.

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?

No annotations exist, so the description carries full burden. It explains the output includes comprehensive details (300-500 words) and notes that master numbers get amplified meanings. It also mentions fallback behavior for unsupported languages. This is transparent for a read operation, though it could explicitly state it is read-only.

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 paragraph of 4-5 sentences, efficiently front-loading the core purpose and then detailing what is returned. Every sentence adds value without redundancy.

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

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

Given no output schema, the description richly describes the return content (archetype, keywords, traits, etc.) and addresses edge cases (master numbers, language fallback). It is sufficiently complete for a simple number lookup tool, though an example response snippet would be mildly helpful.

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 extra semantic information about parameters beyond what the schema provides, but the schema already contains all necessary details including enum values, defaults, and patterns.

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 retrieves meanings for specific numerology numbers (1-9, 11, 22, 33) using Pythagorean numerology, listing content types like archetype, keywords, traits, etc. This distinguishes it from sibling tools that cover other numerology aspects like life path or compatibility.

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 mentions ideal use cases: 'reference tools, educational apps, quick lookups, custom calculators.' It implies when to use this tool but does not explicitly state when not to use it or provide direct comparisons to siblings, though the context of many distinct tools makes the purpose clear.

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

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

No annotations are provided, so the description carries full burden. It transparently discloses key behaviors: automatic detection of Master Numbers (11, 22), reduction of double-digit days, and output of a 300-500 word comprehensive interpretation covering innate talents, natural abilities, career advantages, and how to leverage gifts. 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?

The description is a single paragraph that front-loads the core function and key details. It is moderately concise but could be tightened by removing repetitive use case lists. Still, it efficiently communicates purpose, behavior, and output.

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 has 3 parameters and no output schema, the description fairly covers what to expect: comprehensive interpretation with specific topics, master number handling, and use cases. It could benefit from mentioning error conditions or more precise response structure, but overall it is complete for typical usage.

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 the parameter 'day' with explicit range (1-31) but adds no new meaning beyond the schema. For 'lang' and 'compact', the schema already fully describes them. The description does not enhance parameter 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 calculates the Birth Day number from the day of birth using Pythagorean numerology, specifying the verb 'Calculate', resource 'Birth Day number', and context. The title reinforces the purpose and distinguishes it from sibling tools by focusing on special talents from the day of birth.

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 context for usage, listing perfect use cases like talent discovery apps, career counseling, personal development, and skill assessment. However, it does not explicitly state when not to use this tool or name alternative tools for different numerology calculations, leaving some ambiguity.

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?

No annotations provided, so description carries full burden. It explains the calculation method (absolute differences), meaning of results (0=aligned, higher=tension), and internal steps (calculates core numbers first). No mention of auth or rate limits, but behavior is well-covered.

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?

Concise paragraph of 5 sentences, front-loaded with purpose. Each sentence contributes. Could be slightly more structured but not wasteful.

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, and description does not detail return format (e.g., JSON structure of bridges). Mentions compact parameter but not many details. Adequate but could be more 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 has 100% coverage, baseline 3. Description adds context: explains fullName should be legal birth name, birth date used for Life Path, and compact parameter purpose. Adds value beyond 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 it calculates three Bridge Numbers to harmonize personality aspects, specifies the exact pairs (Life Path-Expression, etc.), and distinguishes from sibling tools that calculate individual core numbers.

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 use cases (personal development, coaching) and requirements (full name and birth date), but does not explicitly state when not to use it or list alternative tools for comparable tasks.

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?

With no annotations provided, the description bears full responsibility for transparency. It discloses the tool returns name number (compound and root), planetary ruler, business rating, industry preferences, and Cheiro compound status. It explains the significance of root numbers and notes it is not a guarantee. No mention of auth, rate limits, or side effects, but as a read-only analysis, this is sufficient.

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-organized paragraph of about 170 words. It begins with the action, lists outputs, gives examples, and ends with caveats. It is efficient and front-loaded, though could be slightly tighter.

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 tool's purpose, what it returns, favorable numbers, and limitations. It does not include sample output or exact field names, but since no output schema exists, the description compensates well. It is sufficiently complete for an agent to decide when and how 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 description coverage is 100%, so baseline is 3. The description does not add usage details for the parameters 'name', 'lang', or 'compact' beyond the schema. It focuses on overall functionality instead. Thus it adds no extra value beyond 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 the tool analyzes a business or brand name using Chaldean numerology, listing specific outputs like name number, planetary ruler, rating, industries, and fortunate compounds. This distinguishes it from sibling tools that focus on personal numerology (birth day, life path, 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 explicitly says to use it to vet a company name, compare brand options, or guide naming decisions. It provides context on favorable numbers and cautions against numbers 4 and 8. While it doesn't contrast with specific siblings, the sibling list makes it clear this is for business names, and the description sets expectations that it is positioning guidance, not a guarantee.

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 clearly outlines the output: Destiny number, Soul Urge, Personality, each with compound number, root, Cheiro interpretation, planetary ruler, and karmic flags. It also explains the behavior of the 'lang' and 'compact' parameters. However, it does not state that the tool is read-only or disclose any error handling, though this is implied.

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

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

The description is a single dense paragraph that packs extensive information without redundancy. While concise for the content, it could benefit from structured formatting (e.g., bullet points) to improve scanability, but it remains clear and effective.

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 compensates by fully explaining the return structure, including compound and root numbers, interpretations, and karmic flags. It covers all key aspects of the tool's functionality, making it self-contained for an agent to understand the 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?

With 100% schema coverage, the description adds significant value beyond the schema: for 'name', it notes Chaldean tradition uses the known name rather than full birth name; for 'lang', it details fallback behavior; for 'compact', it explains the token-optimized format and benefits. This greatly aids correct parameter usage.

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 explicitly states the tool calculates a complete Chaldean numerology reading for a name, detailing the returned numbers (Destiny, Soul Urge, Personality) with compound and root layers, which distinguishes it from more specific sibling tools like post_numerology_soul_urge or post_numerology_expression.

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

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

The description implies when to use the tool: for comprehensive Chaldean name analysis needing both compound and root layers. It targets 'Chaldean numerology calculators, name analysis tools, and AI numerology assistants', but does not explicitly exclude narrower use cases or mention alternative sibling tools.

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?

No annotations are provided, so the description carries the full burden. It mentions returns include 'detailed interpretations, karmic analysis, yearly forecast, and holistic summary' but does not disclose any behavioral traits like authentication needs, rate limits, or side effects beyond being a POST request.

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 paragraph with front-loaded purpose. While it contains some marketing fluff, it is concise enough and every sentence adds 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?

With 7 parameters, 100% schema coverage, and no output schema, the description explains the tool's comprehensive nature and return contents. It also details the compact parameter format. A mention of error handling or response structure would improve 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?

Schema coverage is 100%, baseline is 3. The description adds value by explaining the 'compact' parameter's token optimization benefit and that 'fullName' is used for letter-based calculations, which goes 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 it 'Generate a comprehensive numerology chart combining all major calculations' and lists specific components (Life Path, Expression, etc.), distinguishing it from the many sibling tools that provide individual calculations.

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 says 'Save multiple API calls by getting the full chart in one request' and suggests ideal use cases like 'numerology apps, complete reading services', though it does not explicitly state when not to use it or mention 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?

The description fully discloses the calculation methodology (Pythagorean, weights, compatibility matrix) and output content (scores, strengths, challenges, advice), compensating for missing 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 well-structured but somewhat verbose. It front-loads the core purpose and progresses logically, yet every sentence earns its place.

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

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

Despite lacking an output schema, the description adequately covers what the output contains. It provides enough context for a tool with nested objects and multiple inputs.

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 explains the two input modes (pre-calculated numbers vs raw name/birthdate) and the ability to mix modes, which adds meaning beyond the schema's field descriptions (schema coverage 50%).

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 it calculates numerology compatibility between two people using Pythagorean numerology. It distinguishes itself from sibling tools (individual numerology tools) by focusing on two-person compatibility.

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 explicit use cases (dating apps, counseling, matchmaking) and mentions mixing input modes across persons, giving clear context for when to use.

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?

With no annotations provided, the description carries full burden. It transparently explains the deterministic behavior via seeded randomness and lists the full interpretation returned. However, it does not mention any potential side effects, permissions, or rate limits, which limits the score.

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

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

The description is a single dense paragraph that front-loads the primary action and key features. It is information-rich without wasted words, but a slightly more structured layout (e.g., bullet points for use cases or parameter highlights) could improve readability without losing conciseness.

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

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

Given no output schema, the description adequately covers the return value (number with full interpretation including archetype, keywords, etc.) and use cases. No critical information is missing for a user to understand and 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?

Schema coverage is 100%, so baseline is 3. The description adds significant value beyond the schema: for 'date', it clarifies default to today UTC and use case for past/future readings; for 'seed', it explains reproducibility; for 'lang', lists supported languages and fallback; for 'compact', explains token optimization and benchmarks. This greatly aids parameter understanding.

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

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

The description clearly states the tool receives a daily numerology number (1-9, 11, 22, 33) for guidance and reflection. It distinguishes itself from siblings by emphasizing 'Number of the Day' and seeded randomness for consistency, and lists concrete use cases like daily push notifications and morning briefings.

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

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

The description explains when to use the tool (daily guidance, push notifications) but does not explicitly compare it to siblings or state when not to use it. The context from sibling names like 'get_numerology_personal_day' provides implicit differentiation, but a direct alternative mention would strengthen the score.

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?

With no annotations, the description carries full burden. It explains the systems and that it returns both results with interpretations plus an agreement flag, but does not disclose potential errors, rate limits, or authentication requirements. Adequate but not thorough.

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 concise (5 sentences) and front-loaded with the main purpose. Each sentence adds distinct information with no redundancy or filler.

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

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

Given no output schema, the description adequately explains the output (results, interpretations, agreement flag). It is sufficiently complete for an AI agent to understand the tool's functionality, though details on output structure are 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?

Schema description coverage is 100%, so baseline is 3. The description does not add extra meaning beyond the schema for parameters; it focuses on the overall functionality.

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 a name number in both Pythagorean and Chaldean systems and compares them. It distinguishes itself from siblings by being the only API that returns both in one request, with explicit mention of the two systems and their differences.

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 this tool (e.g., for comparison tools and AI numerology assistants) and highlights its uniqueness. However, it does not explicitly state when not to use it or mention alternative tools for single-system calculations.

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?

No annotations are provided, so the description carries the full burden. It discloses that it detects Master Numbers (11,22,33), returns 300-500 word interpretations, and covers various aspects. It does not mention side effects or state changes, but for a computation tool this is acceptable. The description adequately communicates the tool's behavior.

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 but includes some redundant phrasing (e.g., 'Perfect for...'). It is well-structured, front-loaded with purpose, and each sentence adds value. Could be slightly tighter but overall effective.

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 is provided, so the description must explain return values. It does so by describing the interpretation content (personality, career, etc.) and mention of Master Numbers. It also notes the lang and compact parameters. For a 3-param tool with no output schema, this is fairly 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 coverage is 100%, so the baseline is 3. The description adds minimal value beyond the schema, mentioning response language and compact option only briefly. It does not elaborate on parameter meaning beyond what the schema already provides.

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, and explains what it reveals (natural talents, life goals). It distinguishes from siblings by focusing on the Expression number, unlike siblings like 'post_numerology_life_path' which cover different numbers.

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 lists use cases (name numerology apps, career guidance, etc.) but does not explicitly say when not to use this tool or compare with alternatives like other numerology tools. It implies appropriate contexts but lacks 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?

No annotations are provided, so the description must fully disclose behavior. It accurately conveys that the tool performs a read-only calculation to detect karmic debt numbers and returns a comprehensive analysis including descriptions, challenges, and resolution guidance. It mentions the reduction process, adding behavioral context beyond a simple 'check'.

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

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

The description is efficient, starting with the primary purpose and then detailing return content and use cases. Each sentence contributes information, though it could be slightly shorter. It is well-structured and 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?

Given the absence of an output schema and the presence of six parameters, the description provides sufficient context: explains what karmic debt numbers are, how they are derived (during reduction), and what the output contains. It covers the essential aspects for an agent to understand the tool's functionality 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 coverage is 100%, and the description adds value by explaining which parameters correspond to which numerological calculations (e.g., day/month/year for Life Path; fullName for Expression, Soul Urge, Personality). It also references the compact parameter's purpose, though the schema already describes it. Overall, it enriches understanding 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 identifies the tool's function: checking for karmic debt numbers (13, 14, 16, 19) in specific numerological calculations (Life Path, Expression, Soul Urge, Personality) using Pythagorean numerology. It uses specific verbs and resources, and contextually distinguishes from sibling tools like post_numerology_karmic_lessons.

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

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

The description suggests use cases (spiritual growth apps, karmic astrology platforms, etc.) but does not explicitly state when not to use this tool or provide direct comparisons to alternatives. It implies appropriate contexts but lacks 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?

No annotations are provided, so the description carries the full burden. It clearly describes the tool's behavior: it returns a comprehensive analysis including missing numbers, specific lessons, challenges, development strategies, and practical exercises. However, it does not explicitly state that the operation is read-only or disclose any side effects.

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 purpose. It provides necessary details without excessive fluff, though some repetition (e.g., 'Get detailed lesson descriptions, development strategies, and practical exercises') could be trimmed. Overall, it is clear and efficient.

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 no output schema, the description thoroughly explains what the tool returns: missing numbers, lessons, challenges, strategies, and exercises. It also covers language options and compact output. The use cases are clearly stated. The description is complete for a computation tool with these 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 coverage is 100%, but the description adds significant value beyond the schema by explaining the fullName parameter's purpose ('Full birth name to analyze for missing numbers'), the lang parameter with supported languages and fallback behavior, and the compact parameter with a detailed explanation of token optimization. This exceeds the minimal baseline expected from high schema coverage.

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

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

The description clearly identifies the tool's purpose: analyzing Karmic Lessons from the birth name using Pythagorean numerology. It explains what Karmic lessons are (missing numbers 1-9) and details the output components (missing numbers, lessons, challenges, guidance). This distinguishes it from sibling tools focused on other numerology 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 mentions ideal use cases ('Perfect for spiritual growth apps...') but does not explicitly state when not to use the tool or compare it to alternatives. No guidance on selecting this over siblings like post_numerology_karmic_debt or post_numerology_chart is provided.

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?

With no annotations provided, the description effectively discloses key behaviors: automatic detection of Master Numbers and Karmic Debt numbers, comprehensive interpretation details, and support for multiple languages with a compact output option. However, it does not mention error handling or edge cases for invalid dates.

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 informative and front-loaded with the primary action. It includes essential details about outputs and use cases without being overly verbose. Minor redundancy (e.g., 'most important numerology calculation' and later 'most significant number') keeps it at a 4 rather than 5.

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 number of parameters (5), no output schema, and no annotations, the description adequately covers the tool's purpose, output content (traits, strengths, challenges, etc.), and configuration options. However, the lack of output structure details prevents a 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 coverage is 100%; all parameters are described in the schema. The description adds value by explaining the overall result but does not provide additional parameter-specific meaning beyond the schema's 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 it calculates the Life Path number from a birth date using Pythagorean numerology, specifies it is the most important numerology number, and lists the detailed output contents, which distinguishes it from sibling tools that handle other numerology 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 mentions use cases like numerology apps and birth chart calculators, but does not explicitly state when not to use this tool versus alternatives such as post_numerology_expression or post_numerology_soul_urge. It lacks exclusion criteria or explicit guidance on tool selection among siblings.

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?

With no annotations, the description carries full burden and discloses key behaviors: automatic Master Number detection, return of comprehensive interpretation with specific themes (life transformation, mature personality, later-life purpose, wisdom development), and detailed meanings. It lacks mention of potential limitations or error conditions.

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 relatively concise, though it includes some extraneous lists of use cases and word counts. Every sentence contributes useful 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 8 parameters, no required ones, and no output schema, the description adequately explains what the tool returns (detailed interpretations for all numbers) and covers essential behavioral context. It is complete enough for an agent to select and invoke 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?

Schema coverage is 100%, so the description adds minimal value beyond what the schema already provides. The description does not elaborate on parameter specifics, relying on the detailed 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 the tool calculates a Maturity number by adding Life Path and Expression numbers, specifying the resource and action. It differentiates from sibling tools focused on other numerology aspects, though it could explicitly contrast with related tools like post_numerology_expression.

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

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

The description suggests use cases like life coaching and midlife guidance, but does not provide explicit when-to-use or when-not-to-use guidance, nor name alternatives among siblings. Usage context is implied but not definitive.

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?

No annotations are provided, so the description must fully convey behavioral traits. It notes the tool returns daily theme, guidance, and parent context, but omits side effects, mutability, authentication requirements, or idempotency. For a tool with no annotation coverage, this is insufficient transparency.

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 only three sentences, front-loading the core action. Every sentence adds value: purpose, differentiation from generic numbers, and usage examples. 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?

Given the tool has no output schema, the description adequately summarizes return values (daily theme, guidance, parent month/year context). However, it lacks behavioral details (e.g., error handling, rate limits) and does not fully compensate for missing annotations, making it only moderately 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?

Input schema provides 100% coverage with descriptions for all 5 parameters, meeting the baseline. The tool description adds context about how parameters relate to the calculation (birth data + target date) but does not deepen meaning beyond what schema already provides.

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 clearly states the tool calculates a Personal Day number from birth data and target date, specifying it is the most granular cycle in Pythagorean numerology and distinguishing it from generic daily numbers. It explicitly mentions returning daily theme, guidance, and context, making the purpose very clear.

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?

Description lists ideal use cases like daily push notifications, morning briefings, calendar widgets, and life coaching tools, giving clear context for when to use. However, it does not explicitly discuss when not to use this tool versus alternatives like personal_month or personal_year.

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?

With no annotations provided, the description must fully disclose behavior. It does so by revealing that Master Numbers (11, 22, 33) are automatically detected and that the output includes 'detailed 300-500 word meanings' for each number. The tool is a non-destructive calculation, and the description implies no side effects. The transparency is high, though it could explicitly state that it is read-only.

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 but includes a somewhat lengthy list of use cases and output details. Every sentence adds value, but the use case enumeration ('Perfect for...') could be trimmed for conciseness. It is not verbose, but it is longer than strictly necessary.

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 moderate complexity (3 parameters, no output schema), the description covers the main behavioral traits: calculation method, output length, master number detection, and language options. It lacks an explicit description of the return JSON structure, but the mention of 'comprehensive interpretation' and specific aspects (public image, social dynamics, etc.) provides sufficient context for an AI agent to understand the tool's 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?

The input schema already provides descriptions for all three parameters (100% coverage). The description adds minimal additional meaning beyond the schema—it reinforces that fullName is used for consonant extraction and mentions language support. Since schema coverage is high, a baseline of 3 is appropriate; the description does not significantly enhance parameter understanding.

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

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

The description clearly defines the tool's purpose: calculating the Personality number from the consonants of a birth name using Pythagorean numerology. It explains what the number reveals (outer personality, first impressions, social persona) and distinguishes itself from sibling tools by focusing specifically on 'how others perceive you'. The verb 'calculate' is precise and the resource (Personality number) is explicitly stated.

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 listing applications: 'personal branding apps, social skills training, professional development platforms, and communication coaching services'. However, it does not explicitly state when not to use this tool or compare it to alternative numerology tools (e.g., expression, soul urge). The usage guidance is strong but lacks exclusionary criteria.

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?

No annotations are provided, so the description carries full burden for behavioral disclosure. It does not state whether the tool is read-only, whether it stores data, or any side effects. The 'post_' prefix may imply creation, but the description treats it as a pure calculation, creating confusion about its safety profile.

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 no redundancy. The first sentence defines the purpose and inputs, the second summarizes outputs and use cases. Every word contributes meaning.

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

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

The description explains the return values (monthly theme, practical focus, parent Personal Year context) adequately given the lack of an output schema. It could mention default behaviors for year and targetMonth parameters, but overall it provides sufficient context for a calculation tool with well-documented schema.

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

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

All 6 parameters have descriptions in the schema (100% coverage), so the description adds limited value beyond summarizing which parameters are used (birth month, day, target year, target month). It clarifies the role of year and targetMonth, but the schema already explains them well, resulting in a baseline score.

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 a Personal Month number from birth month/day and target year/month, distinguishing it from sibling tools like personal_day or personal_year. It specifies what is returned (monthly theme, practical focus, parent Personal Year context), providing a specific verb and resource.

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 lists concrete use cases such as 'monthly forecast features, push notification content, calendar integrations', giving clear context for when to use. However, it lacks explicit guidance on when not to use or how it differs from closely related tools like personal_day or personal_year, leaving some ambiguity.

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?

No annotations are provided, so the description must fully disclose behavioral traits. It describes the output (theme, opportunities, challenges) but does not mention that it is a read-only, non-destructive operation, nor any authentication or rate limit requirements. This lack of safety information is a significant gap given the absence of 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 concise but includes marketing fluff like 'Perfect for...' which adds length without core utility. It front-loads the key purpose but could be trimmed to emphasize unique behavioral details.

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 explains the return includes 'year theme, opportunities, challenges, and actionable advice' and mentions forecasts for all 9 cycles, which partially covers output. However, it lacks error handling details, edge cases (e.g., invalid dates), and response format structure. Given no output schema, this is sufficient but not thorough.

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 input schema already explains all five parameters. The description adds minimal extra meaning beyond restating 'birth month, day, and current year'. Baseline 3 is appropriate as the schema handles the semantic burden adequately.

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 explicitly states the tool calculates a Personal Year number from birth month, day, and current year using Pythagorean numerology. It clearly distinguishes this annual forecast tool from siblings like personal_day and personal_month by specifying the 9-year cycle theme.

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 mentions use cases like 'yearly planning apps' and 'life coaching platforms' but does not explicitly state when to choose this tool over alternatives such as post_numerology_personal_month or post_numerology_personal_day. No when-not or alternative tool guidance is provided.

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?

Describes output in detail (personality traits, emotional needs, etc.) and mentions automatic detection of Master Numbers. No annotations, so description carries full burden; it covers key behavioral aspects well, though could mention error handling or rate limits.

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?

Well-organized, starting with core function then details and use cases. Each sentence adds value, though could be slightly more concise without losing 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?

Covers input constraints, output characteristics, language options, and compact mode. No output schema, but description compensates with detail. Lacks error behavior but overall sufficient for this 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?

Adds meaning beyond schema: explains vowel extraction for fullName, lists supported languages, and detailly describes compact parameter. Schema coverage is 100%, so baseline is 3, but description adds significant 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?

Clearly states it calculates Soul Urge number from vowels using Pythagorean numerology, and describes what it reveals. Distinct from siblings like life_path or expression due to specific focus on vowels and inner desires.

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?

Lists ideal use cases (self-discovery apps, emotional intelligence tools, etc.), providing context. However, lacks explicit when-not-to-use or alternative tool suggestions, so it's slightly below top score.

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