reefapi-mcp

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

Annotations already indicate readOnlyHint=false and openWorldHint=true. The description adds valuable behavioral details: the return envelope structure ({ ok, data, meta, error }), authentication requirements (ReefAPI key, local vs hosted), and credit policy. It does not contradict annotations and provides transparency beyond structured data.

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 with four sentences, each adding critical information: the core action, return format, prerequisite, authentication, and cost. It is front-loaded with the main purpose. No redundant or extraneous content.

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 and open-world behavior, the description covers essential contextual aspects: the return envelope shape, authentication setup, credit usage, and the need to consult schema tools. It is sufficiently complete for an agent to use 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 three parameters. The description adds context by directing users to get_engine_schema for parameter names and get_action_schema for valid values, which complements the schema. This extra guidance improves semantics beyond the schema alone, justifying a 4.

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

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

The description clearly states the tool's purpose: 'Call a ReefAPI engine action — POST /<engine>/v1/<action> with params.' It specifies the HTTP method, resource (engine action), and parameters. It distinguishes itself from sibling tools like get_engine_schema (which provides schemas) and search_engines (which lists engines). The verb 'call' is specific and actionable.

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 instructs to 'Get param names from get_engine_schema first,' indicating a prerequisite step. It also notes that 'Failed calls cost no credits,' which is a usage hint. However, it does not explicitly state when not to use this tool or provide alternatives to other sibling tools. The context is clear but lacks exclusionary 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 provide readOnlyHint, idempotentHint, openWorldHint. The description adds that it returns parameter details, pricing, and example_params, enriching the behavioral understanding beyond annotations. 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?

Single paragraph, front-loaded with key information, no redundant sentences. Every sentence adds value.

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

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

Given no output schema, the description thoroughly explains what is returned (param detail, return, pricing, example_params). Combined with high schema coverage and annotations, the tool is fully contextualized for an AI agent.

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 context: action comes from get_engine_schema, engine from search_engines or get_catalog. This provides useful semantic linkage 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 returns 'FULL detail for ONE engine action' and enumerates included items (parameters, return, pricing, example_params). It distinguishes itself from siblings like get_engine_schema (which lists all actions) and call_engine (which executes).

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?

Explicitly instructs 'Call this right before call_engine so you send valid params' and warns about invalid enum rejection, providing clear context for when to use the tool.

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 annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, indicating no destructive side effects. The description adds value by revealing the approximate token size (a few thousand tokens) and the internal structure (grouped by category, one-line titles). It does not contradict annotations, so no flag. Slight deduction because the description could mention that no parameters are needed, but it's already 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 slightly verbose but every sentence adds value: it states the content, token budget, comparison to search_engines, and post-call workflow. The information is front-loaded. It could be slightly more concise, but the detail is justified.

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 zero parameters, full schema coverage, and rich annotations (readOnly, openWorld, idempotent), the description provides all necessary context: what the catalog contains, how large it is, when to use it, and how to chain it with sibling tools. No output schema exists, but the description explains what it returns.

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?

There are zero parameters, and the schema coverage is 100% (empty object). The description does not need to elaborate on parameters, and it correctly focuses on the output and usage. This is a perfect handling of a parameterless tool.

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 returns the FULL ReefAPI catalog with every engine's one-line title grouped by category. It explicitly distinguishes from the sibling search_engines by emphasizing comprehensiveness: 'SCAN IT AND PICK THE BEST ENGINE YOURSELF.' The verb 'get' is straightforward, and the resource 'catalog' is well-defined.

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 usage guidance: 'Use this whenever search_engines didn't surface the right engine (or to be sure you didn't miss a better one).' It also specifies the ideal workflow after using this tool: 'get_engine_schema(engine) -> get_action_schema -> call_engine.' This effectively tells the agent when to use this tool vs alternatives and what to do next.

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

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

Annotations already indicate read-only, idempotent, and open world; the description adds that the tool returns a lean overview to save tokens, setting accurate expectations beyond the annotations.

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

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

Two sentences: first defines the tool's purpose, second provides workflow context. No waste, front-loaded with key information.

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

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

With one parameter fully described, annotations covering safety, and output behavior explained, the description is complete for the tool's simplicity and fits its role in the workflow.

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 schema description already states what the parameter is and what the tool returns; the tool description doesn't add new parameter-level 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?

Explicitly states it provides a compact overview of one engine's actions, descriptions, required params, and returns, and distinguishes from similar tools by naming the workflow sequence.

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?

Clearly states it should be called after search_engines and before get_action_schema, establishing a clear usage order and specifying when to use alternatives.

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

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

Annotations provide readOnlyHint, openWorldHint, idempotentHint. Description adds rich behavioral details: stem matching, ranking by match, empty query returns all, and return fields.

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-structured with front-loaded purpose, but slightly verbose. Each sentence adds value, but could be tightened.

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?

Comprehensive description covering behavior, return values, and relationships with sibling tools. No output schema, but return info is sufficient.

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

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

Schema description coverage is 100%, already explaining the query parameter. Description adds value with translation guidance and ranking details, enhancing 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?

Description clearly states the tool finds the right ReefAPI engine for a task using English keywords or natural language, distinguishing it from siblings like get_catalog and get_engine_schema.

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?

Explicitly states 'Call this FIRST' and advises to use get_catalog if the right engine isn't found. Also provides translation guidance for non-English queries.

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