Angel Numbers MCP Server by RoxyAPI

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

Annotations already mark it read-only/non-destructive, and the description adds meaningful behavioral scope: a complete 75+ entry catalog across root, master, mirror, palindrome, compound, and sequential families, with optional filtering. No hidden mutation or side effects are 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 core action is front-loaded and the category enumeration is dense but useful. The use-case sentence earns its place; only the category list could be slightly trimmed, so it is efficient rather than perfectly spare.

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 catalog endpoint, it covers scope, categories, filtering, and intended applications while the schema covers pagination, language, and compact output. It lacks a concrete statement of the response item shape beyond 'summary information', which is the main remaining gap.

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

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

Schema coverage is 100% and each parameter (lang, type, limit, offset, compact) already has a clear description. The tool description only repeats 'optional type filtering', adding no semantic meaning beyond the schema.

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

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

Description begins with a specific verb-resource pair ('Retrieve the complete database of angel numbers') and the title reinforces 'List all angel numbers'. The 'complete database' scope clearly distinguishes it from singular lookup/number/documentation siblings.

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

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

It establishes clear context: this is the catalog-wide listing endpoint for building explorers/reference guides, with optional type filtering for browsing. It does not explicitly say 'use lookup for a single number', so it stops short of full when-not/alternative 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 safety is covered. The description adds valuable behavior: it automatically classifies pattern types, calculates digit root, checks the database, and provides a fallback interpretation with life areas. This goes beyond the annotations and helps the agent understand what the tool does internally, though it doesn't mention error handling or edge cases.

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 with the key differentiator ('works for ANY number sequence') front-loaded. It's concise enough to be parsed quickly, though it lists many details in one long sentence. It's not bloated but could be broken into a clearer structure.

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

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

For a tool with no output schema, the description thoroughly explains what the response contains: pattern type, digit root, known meaning, and fallback interpretation across spiritual, love, career, money, and twin flame domains. It also covers the context parameter's effect. Together with the schema, an agent has everything needed to call 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% with descriptions for all 4 parameters. The description adds extra meaning by explaining that the number can be from clock times, addresses, receipts, etc., and details how context tailors the reading. This goes beyond the schema's basic field descriptions, providing richer semantics for parameter selection.

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 any number sequence beyond known angel numbers, and lists the specific actions (classify pattern, calculate digit root, check DB, provide fallback). It differentiates from siblings by emphasizing 'ANY number sequence, not just known angel numbers', making it distinct from get_angel_numbers which presumably only handles predefined ones.

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 gives a clear use case: 'Perfect for syncing tracking apps where users enter arbitrary number sequences'. This implies it's the tool to use when the number is not necessarily a known angel number. However, it doesn't explicitly name alternatives or state when not to use this tool, 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 safety disclosure is covered. The description adds meaningful behavioral context by listing exactly what the response contains: spiritual, love, career, money, twin flame, biblical, shadow, keywords, affirmation, and actionable steps.

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 first two sentences are useful and front-loaded with purpose and output contents. However, the final sentence largely repeats the 'authoritative' and coverage claims, and the 'complete, authoritative' wording appears twice, making the description slightly padded.

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?

Since there is no output schema, the description properly enumerates the return shape and support scope (75+ numbers with examples), which is enough for an agent to know what it will get. Missing error behavior is minor because the schema already states the number must match an entry in the database.

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

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

Schema description coverage is 100%, so the schema fully documents number, lang, and compact. The description adds a couple of example numbers and confirms the lookup targets a specific sequence, but it does not add meaningful semantics 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 a specific-number lookup: 'complete, authoritative meaning and interpretation for a specific angel number' and enumerates the return domains. However, it does not explicitly distinguish itself from the sibling get_angel_numbers_lookup, whose name implies the same operation.

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?

Usage is implied: use this tool when you need an interpretation for one specific angel number such as 444. There are no explicit when-to-use, when-not-to-use, or alternative routing statements, leaving selection among the similarly named siblings somewhat ambiguous.

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 mark the tool readOnlyHint=true and destructiveHint=false, and the description does not contradict them. It adds valuable behavioral context: the result is deterministic per date, all users see the same number for the same day, and seeds enable reproducible readings. It also enumerates the interpretation domains included in the response, which matters more because there is no output schema.

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

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

Three sentences with a front-loaded purpose statement followed by deterministic behavior, response contents, and explicit use cases. Every sentence adds distinct value, and the length is appropriate 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?

The tool has no output schema, so the description compensates by listing the major interpretation categories (spiritual, love, career, money, twin flame, biblical, shadow). Combined with fully documented optional parameters and read-only annotations, the agent has enough to call it correctly. A small gap is the lack of any mention of rate limits or response size, but these are not critical for invocation.

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

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

The input schema has 100% description coverage with clear explanations for date, lang, seed, and compact. Per the baseline, the schema already carries the semantic weight. The description adds only indirect references to date/seed determinism, which do not materially exceed the schema's own parameter documentation.

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 verb and resource: 'Get the angel number of the day with full meaning and interpretation.' This differentiates it from the sibling get_angel_numbers* tools through the 'of the day' focus. However, it does not explicitly name or contrast sibling tools, so it stops one step short of a 5.

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 contexts: 'Perfect for daily guidance features, push notifications, content generation, and angel number widget integrations.' This gives an agent solid signals for when to choose this tool. It lacks explicit when-not-to-use guidance or named alternatives compared to siblings.

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