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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool provides 'detailed explanation,' which implies a read-only, informational operation, but doesn't specify aspects like response format, potential errors, rate limits, or authentication needs. For a tool with zero annotation coverage, this is a significant gap in behavioral 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 appropriately sized and front-loaded, consisting of two concise sentences that directly state the tool's purpose and usage without any wasted words. Every sentence earns its place by providing essential information efficiently.

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's low complexity (1 parameter, no nested objects) and high schema coverage, the description is adequate but has clear gaps. It lacks output schema, so it doesn't explain return values, and with no annotations, it misses behavioral details. For a simple informational tool, it's minimally viable but could be more 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 has 100% description coverage, with the 'concept' parameter well-documented in the schema. The description adds minimal value beyond the schema by implying the types of concepts (e.g., 'fundamental concepts, terminology, or architectural patterns'), but doesn't provide additional syntax or format details. Baseline 3 is appropriate when the schema does the heavy lifting.

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 with a specific verb ('Get detailed explanation') and resource ('Fabric or Minecraft modding concept'). It distinguishes itself from potential siblings by focusing on concept explanations rather than examples, versions, or documentation searches. However, it doesn't explicitly contrast with the sibling tools listed, which keeps it from a perfect score.

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 implied usage guidance by stating 'Use this to understand fundamental concepts, terminology, or architectural patterns,' which suggests when to use it. However, it doesn't explicitly mention when not to use it or name alternatives among the sibling tools (e.g., use search_fabric_docs for broader searches). This lack of explicit exclusions or named alternatives limits the score.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the output format ('complete, working code snippets with full context including explanations, source documentation, and metadata'), which is helpful. However, it lacks details on error handling, rate limits, or authentication needs, leaving gaps for a tool with 6 parameters.

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 and well-structured with two sentences: the first defines the tool's purpose and output, the second provides usage guidelines. Every sentence adds value without redundancy, making it easy to scan and understand.

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's moderate complexity (6 parameters, no output schema, no annotations), the description is reasonably complete. It covers purpose, output format, and usage context. However, it lacks details on behavioral aspects like error handling or performance, which would be beneficial for a tool returning code examples.

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 all 6 parameters. The description adds no parameter-specific information beyond what's in the schema, such as examples for 'topic' or details on 'limit' behavior. Baseline 3 is appropriate when the schema does all the work.

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 with specific verbs ('Get code examples') and resources ('Minecraft modding topics'), distinguishing it from siblings like 'explain_fabric_concept' (conceptual explanations) and 'search_fabric_docs' (documentation search). It explicitly mentions the output format ('complete, working code snippets with full context').

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 with 'Use this when you need concrete code examples for implementing features,' clearly indicating when to choose this tool over alternatives. It differentiates from siblings by focusing on practical code rather than conceptual explanations or general documentation.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'Returns either the latest version or all available versions,' which implies a read-only operation, but lacks details on data sources, freshness, error handling, or rate limits. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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, efficient sentence that front-loads the core purpose and return options without redundancy. Every word contributes to understanding the tool's function, making it appropriately sized and well-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?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and return types but lacks details on behavioral traits and usage guidelines. Without annotations or output schema, it should provide more context on data handling and sibling differentiation.

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, fully documenting the single parameter 'type' with its enum values and default. The description adds minimal value by mentioning 'latest version or all available versions,' which aligns with the schema but does not provide additional syntax or format details. This meets the baseline for high schema coverage.

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 with specific verbs ('Get Minecraft version information') and resource ('from the indexed documentation'), and distinguishes it from siblings by focusing on version retrieval rather than explanation, examples, or search. It explicitly mentions what is returned ('latest version or all available versions'), making the purpose unambiguous.

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 no guidance on when to use this tool versus its siblings (e.g., explain_fabric_concept, get_example, search_fabric_docs). It mentions the return options ('latest' or 'all') but does not specify contexts or prerequisites for choosing between them, leaving usage decisions unclear.

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?

No annotations are provided, so the description carries the full burden. It mentions the tool searches for 'guides and API information' but lacks details on behavioral traits like response format, pagination, error handling, or performance characteristics. It adds some context about what type of content is searched but doesn't fully compensate for the absence of 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 front-loaded and concise with two sentences that directly state the purpose and usage guidelines, with no redundant or unnecessary information, making it highly efficient and easy to understand.

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's moderate complexity (2 parameters, no annotations, no output schema), the description is adequate but incomplete. It covers purpose and usage well but lacks details on behavioral aspects and output, which could hinder an agent's ability to use it effectively without trial and error.

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 already documents both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as examples or usage tips, but it implies the tool is for searching documentation, which aligns with the parameters.

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 with specific verbs ('search') and resources ('Fabric modding documentation for guides and API information'), and distinguishes it from siblings by focusing on documentation search rather than concept explanation, examples, or version retrieval.

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 provides explicit guidance on when to use this tool ('when you need to find documentation about Fabric modding features, APIs, or tutorials'), though it doesn't explicitly mention when not to use it or name alternatives, the context is clear enough for effective decision-making.

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