Dream Interpretation MCP Server by RoxyAPI

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

Annotations already provide readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds meaningful context about the content scope (2,000+ symbols, categories like animals, scenarios, people) and the search/filter behaviors, which helps set expectations beyond the annotations. It does not discuss pagination or response format, but for a read-only list tool, that is acceptable given annotation coverage.

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 primary purpose and then provides illustrative examples that add context. It is somewhat lengthy (about 60 words) but well-organized, and each sentence serves a purpose—listing categories and usage modes. It is efficient without being terse or redundant.

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 list/search tool with 5 fully documented parameters and no output schema, the description adequately covers the domain and usage context. It does not detail pagination or response shape, but the schema covers those parameters, and the examples give a good sense of what the tool returns. The description is complete enough for an agent to select 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 description coverage is 100%, with each parameter (q, limit, letter, offset, compact) fully documented in the schema. The description mentions 'q' and 'letter' but adds no new meaning; it simply restates 'search by keyword' and 'Filter by starting letter.' Since the schema carries the parameter documentation, the baseline of 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 the tool's function with specific verbs: 'Browse and search our complete dream interpretation dictionary containing 2,000+ dream symbols.' It explicitly describes filtering by letter and searching by keyword, and the resource (dream symbols) is unambiguous. It naturally distinguishes from siblings like get_dreams_symbols_id (single symbol) and get_dreams_symbols_random (random symbol) by emphasizing the complete dictionary and list/search capabilities.

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 usage: 'Filter by starting letter for A-Z navigation or search by keyword' tells the user when to use this tool for browsing/searching. However, it does not explicitly mention alternatives or exclusions (e.g., 'for a specific symbol, use get_dreams_symbols_id'). There is no direct when/when-not guidance, so the recommendation is only implied.

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 this as read-only and non-destructive, so the safety profile is covered. The description adds contextual value by describing the nature of the output (detailed psychological analysis covering subconscious symbolism, emotional significance, waking-life connections), which goes beyond what annotations provide. 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 description is somewhat verbose, with a long enumerative list of dream themes. It does front-load the core purpose ('Get the complete dream interpretation') but the extended catalog of examples makes it less crisp than it could be. Not wasteful, but could be more compact.

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 conveys what the response will contain (psychological analysis, specific dream themes). It doesn't explicitly describe the compact parameter's effect on the response, but that is already covered by the schema. Overall, it provides a sufficient picture for a simple read-only 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?

The input schema fully documents both parameters (id and compact) with descriptions and examples, so schema coverage is 100%. The description adds no additional parameter semantics, so the 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 states this tool gets the complete dream interpretation for a specific symbol, using a specific verb and resource. It distinguishes from siblings by emphasizing 'specific symbol' rather than random or letters, so the agent knows it's a by-ID lookup.

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 does not explicitly explain when to use this tool versus alternatives like listing all symbols or getting a random symbol. The phrase 'specific symbol' implies you already have an ID, but there is no direct guidance on alternatives or 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 and destructiveHint, so the safety profile is covered. The description adds that it returns per-letter counts and suggests a use context, but doesn't disclose details like response shape or potential empty results. This is adequate but not rich.

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

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

The description is short and front-loaded with the core function. The first sentence is precise; the second gives a practical use case. The third sentence is somewhat redundant with the first, but overall it wastes little space.

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?

This is a simple read-only tool with one optional, well-documented parameter and no output schema. The description fully explains what the tool returns and why it would be used, making it complete for an agent. No significant gaps remain.

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

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

The only parameter, compact, is fully described in the schema with its meaning and token savings. The description doesn't mention it, but schema coverage is 100%, so no additional explanation is needed. 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 the tool gets the count of dream symbols for each letter A-Z. It distinguishes itself from sibling tools by focusing on letter-based counts rather than symbol details, IDs, or random symbols.

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

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

The description gives a clear use case: building alphabetical dream dictionary navigation for browsing interpretations by letter. It doesn't explicitly mention when not to use it or name alternatives, but the context is sufficient for an agent to decide when this fits.

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 declare readOnlyHint=true and destructiveHint=false, so the safety profile is already known. The description adds useful behavioral context: each request returns different symbols from a 2,000+ database and includes full psychological meanings, going beyond what annotations state.

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

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

The description is three sentences long and reasonably front-loaded with purpose. The use-case list in the second sentence is somewhat exhaustive, making it slightly less concise than it could be, but every sentence contributes value and it is not bloated.

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

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

For a simple random-selection tool with no required parameters and no output schema, the description covers what it returns (dream symbols with full meanings), the scope (2,000+ database), and typical uses. It lacks explicit return-shape details, but that is not critical given the simplicity and the presence of an input schema.

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

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

Schema description coverage is 100%, with clear explanations of count and compact. The description adds no new parameter semantics—'one or multiple' merely echoes the count parameter's schema. Since the schema carries the full burden, 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 states the tool provides random dream symbols and interpretations, using strong verbs like 'Discover' and 'Get' tied to a specific resource. It is immediately distinguishable from siblings like get_dreams_symbols (specific listing) and get_dreams_symbols_id (single symbol) by emphasizing randomness.

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 use cases ('dream of the day features, dream journaling prompts, meditation on subconscious themes, or exploring what different dreams mean') but does not explicitly contrast with sibling tools like get_dreams_symbols. It implies when to use this tool but lacks 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 mark the operation as read-only and non-destructive; description adds deterministic seeded randomness ('same seed gets the same symbol on the same day') and notes that it 'Returns the symbol with full psychological interpretation,' giving useful behavioral expectations.

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?

Five sentences, each providing distinct value: purpose, seeded randomness behavior, seed guidance, return contents, and use cases. The most critical information is front-loaded, with no filler or redundant explanations.

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 tool with no output schema, the description sufficiently explains the returned data (symbol plus interpretation), the deterministic behavior, and parameter usage. It is complete for an agent to select the tool and understand its output without needing additional context.

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 covers all 3 parameters with descriptions, but the tool description enriches seed semantics by suggesting concrete identifiers (userId, email hash, session token) and explains the date-based default behavior. The compact parameter is not addressed in the description, but the schema already documents 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?

Description opens with 'Receive a single dream symbol for daily reflection and subconscious exploration,' clearly specifying the output and use case. It distinguishes from sibling tools by focusing on a single daily symbol with seeded randomness, not on listing, ID lookup, letters, or random generation.

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 identifies target use cases ('dream journal apps, wellness platforms, morning ritual apps, meditation tools') and explains when to provide a seed versus omit it, giving concrete context for daily symbol retrieval. However, it does not explicitly name alternative sibling tools for when not to use this one.

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