Dribba

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds only the vague 'Dribba's take,' which hints at an opinionated output but does not explain behavior, return format, or limitations. It does not contradict 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?

The description is short, but it is under-specified rather than efficiently informative. It is a single vague phrase that does not add meaningful structure or details beyond the tool name.

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 one enum parameter and no output schema, the description should at least explain what a comparison returns and what 'Dribba's take' means. It does neither, leaving the agent to infer output and scope from the enum values alone.

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 0%, and the description never mentions 'topic' or the allowed values. The schema itself is self-explanatory because topic has clear enum values, but the description adds no semantic value 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 'Dribba's take on a technology comparison' essentially restates the tool name without a concrete verb or resource. It does not specify what the tool does with the topic, what output is produced, or how it differs from siblings like get_case_study or search.

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?

There is no guidance on when to use this tool versus the sibling tools. The description provides no context, exclusions, or alternative routing; the only hint is the tool name and the enum values in the schema.

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, covering the safety profile. Description adds the detail that it retrieves a single case study by slug, but does not describe return format or error behavior. The description aligns with annotations, adding minimal context.

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 concise sentence, front-loading the core purpose. It is efficient and avoids unnecessary detail, though it could include more usage guidance without becoming verbose.

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 is simple (one parameter) and annotations cover safety, the description is mostly adequate. However, it lacks information about the return format or error conditions, and with 0% schema coverage, it would benefit from explaining the slash format. Overall, it is minimal but not severely incomplete.

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 0%, meaning the schema has no descriptions for the sluf parameter. The description mentions slug as a URL path segment and what it matches, but does not explain its format, validation, or examples. With 0% coverage, the description should compensate but only provides minimal context.

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 the specific verb 'get' and resource 'case study', and identifies the parameter 'slug'. It distinguishes from siblings by focusing on a single item, unlike 'search' which presumably lists multiple. However, it does not explicitly contrast with siblings, but the purpose is 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?

Implies usage: when you need details of a specific case study and know its slug. Does not explicitly state when not to use or mention alternatives. Sibling 'search' is implied for searching, but no explicit guidance is given.

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, idempotentHint=true, and destructiveHint=false, so safety is clearly communicated. The description adds a behavioral note about the input source (the slug from the /servicios/ URL), which is useful but does not disclose any other behavioral traits such as response shape, pagination, or error cases. With annotations carrying the main safety framework, a mid-range score is appropriate.

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?

A single sentence that is direct, acts as a complete definition, and immediately clarifies the tool's purpose. No filler or 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?

For a simple read operation with one well-described parameter, the description is largely complete. It lacks explicit details about return format or potential exceptions, but given the annotations cover idempotence/read-only nature and the schema covers the parameter, an agent can reasonably invoke the tool without additional information.

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 provides a meaningful description for the only parameter, 'slug', including an example value. Schema coverage is 100%, so the description need not repeat. However, the description adds the source of the slug (from /servicios/<slug>) and the expected output type ('Full summary'), giving the parameter more context than the schema alone.

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 specific verb ('get'), a resource ('one service'), and a clear identifier ('by its slug'), which is entirely distinct from siblings like 'compare_technologies' or 'get_case_study'. It fully explains the tool's purpose in a single phrase.

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 identifies the tool's use case (retrieve a full summary given a slug) and implies it is the single-item counterpart to browsing through the /servicios/ path. It does not explicitly mention when not to use it or direct to an alternative, but the context of the description makes the usage context sufficiently clear given the sibling tools are obviously different in scope.

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, idempotentHint=true, destructiveHint=false, and openWorldHint=false. The description adds that it returns 'matching passages with links' which is useful, but doesn't disclose specifics like result limit, ranking, or whether it searches only llms-full.txt. It's a safe read operation, and the description doesn't add much beyond the annotations, but it does add the return format context. 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?

Single sentence, front-loaded with the core purpose. It's concise and informative. Minor waste: the parenthetical 'the llms-full.txt content' is slightly redundant since 'knowledge base' already suffices, but it clarifies scope. Overall, efficient and 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?

For a simple one-parameter search tool with read-only annotations, the description covers the basics: action, target, return type. It doesn't mention pagination or result count limits, which are common for search tools, but given the tool's simplicity and the annotations' coverage, it's adequate. Could include a note about linking to sources, which it does partially. Overall, moderate completeness for its simplicity.

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 0%, meaning the schema provides no description for the 'query' parameter. The description's term 'Full-text search' implies a free-text query, but it doesn't add specifics like case sensitivity, syntax, or language. Since the schema is bare, the description carries the burden to explain parameter semantics, and it under-delivers. A note like 'natural language or keyword query' would 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?

The description clearly states the action (full-text search) and the resource (Dribba's knowledge base), and specifies the return type (matching passages with links). It's distinguishable from siblings like get_case_study and get_service, though it doesn't explicitly differentiate from compare_technologies. A minor gap is the somewhat informal reference to 'llms-full.txt content', but the purpose is 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?

The description implies usage for finding information across the knowledge base, but it doesn't state when to use this tool over siblings (e.g., when to use get_case_study vs search). Since siblings are specialized retrieval tools, explicit guidance on choosing between search and those tools would be helpful. The context is clear but exclusions are not mentioned.

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