Dream Interpretation MCP Server by RoxyAPI

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful behavioral context beyond that: it is a large read-only dictionary lookup, supports search and letter-based navigation, and covers a wide content domain. It does not mention response shape or pagination behavior, but that is not necessary given the annotations and schema 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 main action and resource are front-loaded in the first sentence. The long list of dream categories is verbose but informative for a dream-dictionary domain. The description is well-organized and readable, though slightly padded with marketing language like 'our complete.'

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 read-only annotations, full schema documentation, and no output schema, the description provides enough domain context and usage direction. It briefly explains the two main access modes (letter and keyword) and the dictionary's scope. A minor gap is that interactions between q, letter, and pagination are not mentioned, but the schema covers those details.

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

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

Schema description coverage is 100% and every parameter already has its own clear description. The description largely restates q and letter filtering without adding new semantic detail, so it meets the baseline but does not elevate 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?

States a specific verb ('Browse and search') and a clear resource ('complete dream interpretation dictionary containing 2,000+ dream symbols'), and lists concrete categories and filter modes. It does not explicitly distinguish itself from siblings like get_dreams_symbols_id or get_dreams_symbols_random, so differentiation is only implied by the title and sibling names.

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?

Gives implied usage context: browse the dictionary, search by keyword, or filter by starting letter for A-Z navigation. However, it never mentions sibling tools or states when to prefer get_dreams_symbols_id, get_dreams_symbols_letters, or get_dreams_symbols_random, so alternative routing is not explicitly addressed.

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 mark this as read-only and non-destructive, and the description aligns with that by describing a lookup operation. It adds useful detail about what the response contains, such as psychological analysis, subconscious symbolism, emotional significance, and waking-life connections, which goes 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 first sentence is strong and front-loaded, but the second sentence becomes a long promotional list of dream themes. This filler could be trimmed without losing functional guidance, making it adequately concise but not tightly 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 explains what the agent will receive: a complete interpretation with several named analysis categories. It does not mention error behavior or authentication, but for a simple read-only single-id lookup, the description is reasonably 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?

The input schema already documents both parameters fully with examples and defaults, so schema coverage is 100%. The description adds little parameter-specific meaning beyond the schema, so the baseline score of 3 is appropriate.

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

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

The description opens with a clear verb and resource: 'Get the complete dream interpretation for a specific symbol.' The phrase 'specific symbol' plus the tool name's 'by id' distinguishes this from siblings like get_dreams_symbols_letters, get_dreams_symbols_random, and get_dreams_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?

Usage is implied: use this when you have a known symbol id and need its full interpretation. However, it does not explicitly state when to prefer this over the sibling tools or when not to use it, leaving some routing decisions to the 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 safe read-only nature is covered. The description adds the A-Z scope and navigational purpose, but does not disclose details like whether letters with zero symbols are included or the exact response structure. No contradiction with annotations.

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

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

The first sentence is direct and front-loaded. The second sentence adds legitimate usage context. The third sentence is somewhat redundant with the first and the illustrative 'abandonment dreams to zodiac dreams' is mild filler, but overall the description remains appropriately 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?

For a zero-required-parameter, read-only endpoint, the description provides enough context to understand the purpose and invoke it successfully. There is no output schema, so the exact response shape is not specified, but 'count for each letter A-Z' implies a letter-to-count mapping.

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

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

Schema description coverage is 100%, and the only parameter, compact, is thoroughly documented in the schema itself. The description does not add parameter-specific meaning, but none is needed since the schema already explains the compact behavior and token savings.

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 a precise verb and resource: 'Get the count of dream symbols available for each letter A-Z.' This clearly differentiates it from sibling tools like get_dreams_symbols, which likely returns the full list, and get_dreams_symbols_id, which targets a specific symbol.

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 concrete use case: 'Build alphabetical dream dictionary navigation to help users browse dream interpretations by letter.' It does not explicitly name alternative tools or state when not to use it, but the intended context is reasonably 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?

Annotations already indicate a safe read-only operation. The description adds behavioral context by explaining that results are randomly sampled from a 2,000+ database and that responses include full psychological interpretations. This goes beyond the annotations and helps set agent expectations for output content.

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 and front-loads the core purpose before listing use cases. It is somewhat promotional but each sentence contributes either purpose or usage context. It earns its length, though it could be trimmed slightly.

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 endpoint with two optional, fully documented parameters and safe read-only annotations, the description is sufficient. It conveys randomness, database scope, and the nature of the returned content. Without an output schema, a bit more shape detail would raise it further, but nothing critical is missing.

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

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

Schema coverage is 100%: both count and compact have clear descriptions including defaults, ranges, and behavior. The description's mention of 'one or multiple random dream interpretations' loosely aligns with the count parameter, but it does not add meaning 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 clearly states the verb ('Discover') and resource ('random dream symbols and their interpretations'), and emphasizes the random nature with 'Each request returns different symbols'. This distinguishes it from siblings like get_dreams_symbols_id and get_dreams_symbols_letters without needing explicit comparison.

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 concrete use cases: dream of the day features, dream journaling prompts, meditation on subconscious themes, and exploring dream meanings. This tells an agent when the random discovery endpoint is appropriate, though it does not explicitly name alternatives or state when not to use it.

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

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

Discloses the seeded randomness behavior, determinism on same seed and date, and that it returns full psychological interpretation. The readOnly and destructiveHint annotations already convey safety, and the description adds meaningful deterministic behavior 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 compact, front-loaded with the core purpose, and every sentence adds useful context. The use-case sentence is slightly promotional but still 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 simple read-only endpoint with three optional parameters and no output schema, the description is nearly complete. It could more precisely describe the response fields beyond 'full psychological interpretation,' but nothing critical is missing for correct 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 schema already covers all three parameters, but the description adds practical meaning: seed can be a userId, email hash, or session token, and omitting seed gives date-based daily symbols. This goes beyond the schema's parameter docs.

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 returns a single dream symbol for daily reflection, with a specific daily/seeded behavior. It does not explicitly name sibling tools or how it differs from them, especially get_dreams_symbols_random, so it falls short of full differentiation.

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 clear context for when this is appropriate: daily dream journal features, wellness apps, and meditation tools. It also explains the seed versus no-seed choice. However, it does not explicitly say when to use this instead of the sibling random symbol endpoint.

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