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 describes what the tool does (fetch documentation) but lacks details on behavioral traits such as error handling (e.g., what happens if the component slug is invalid), performance characteristics (e.g., response time), or output format (e.g., structured data vs. raw text). This is a significant gap for a tool with no 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 appropriately sized and front-loaded, with two sentences that efficiently convey the tool's purpose and usage. Every sentence earns its place: the first defines the action and scope, and the second provides parameter guidance with examples. There is no wasted verbiage.

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 (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and parameter usage but lacks behavioral context (e.g., error handling) and output details. Without annotations or an output schema, the description should do more to compensate, but it only meets minimum viability.

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 description coverage is 100%, with the single parameter 'component' fully documented in the schema. The description adds minimal value beyond the schema by providing examples ('accordion', 'elastic-slider', 'aurora'), but does not explain semantics like format constraints or validation rules. This meets the baseline of 3 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 specific action ('Fetch'), resource ('full documentation for a specific Reacticx component'), and scope ('including props, code examples, usage, and installation instructions'). It distinguishes from sibling tools like 'list_components' (which likely lists components) and 'search_components' (which likely searches for components) by specifying retrieval of detailed documentation for a single component.

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 clear context for when to use this tool: to get comprehensive documentation for a specific component. It implicitly distinguishes from siblings by focusing on detailed docs rather than listing or searching. However, it does not explicitly state when NOT to use it or name alternatives (e.g., 'list_components' for overviews), which prevents a score of 5.

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 of behavioral disclosure. It mentions the tool 'gets' dependencies, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns structured data, or handles errors. For a tool with no annotation coverage, this is a significant gap in transparency about its behavior and constraints.

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: the first states the core purpose, and the second provides usage context. Every sentence earns its place without redundancy or fluff, making it efficient and easy for an agent to parse.

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 (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and basic usage but lacks details on behavioral traits (e.g., authentication needs) and output format, which are important for a dependency-checking tool. This results in a minimal viable description with clear gaps.

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 'components' parameter fully documented in the schema as 'Array of component slugs to check dependencies for.' The description adds no additional parameter semantics beyond this, such as examples of slugs or format details. Given the high schema coverage, a baseline score of 3 is appropriate, as 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: 'Get the required npm dependencies for one or more Reacticx components.' It specifies the verb ('Get'), resource ('npm dependencies'), and scope ('Reacticx components'), distinguishing it from sibling tools like 'list_components' or 'get_component_docs'. However, it doesn't explicitly differentiate from all siblings (e.g., 'search_components' might also involve dependencies), so it falls short of a perfect 5.

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 with 'Useful for planning installations,' suggesting it should be used when preparing to install dependencies. However, it lacks explicit when-to-use vs. when-not-to-use instructions or named alternatives among sibling tools (e.g., no mention of when to use 'list_components' instead). This leaves gaps in guiding the agent on optimal tool selection.

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 of behavioral disclosure. It describes a read operation ('Get'), implying it's likely safe and non-destructive, but doesn't specify aspects like authentication requirements, rate limits, or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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: 'Get the Reacticx getting started guide with installation and setup instructions.' It's front-loaded with the core action and resource, with no wasted words, making it highly concise and well-structured for quick comprehension.

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 simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It explains what the tool does but lacks details on behavioral traits or usage context. For a straightforward read tool, it meets basic needs but could be more informative to compensate for the absence of annotations.

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 tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The description appropriately focuses on the tool's purpose without redundant parameter information, earning a baseline score of 4 for zero-parameter tools.

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: 'Get the Reacticx getting started guide with installation and setup instructions.' It specifies the verb ('Get') and resource ('Reacticx getting started guide'), making the action and target explicit. However, it doesn't distinguish this from sibling tools like 'get_component_docs' or 'get_dependencies', which limits 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or contexts where this is preferred, such as for initial setup versus detailed documentation. Without such guidance, users must infer usage from the tool name and description alone.

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 listing and filtering but doesn't disclose behavioral traits such as pagination, rate limits, authentication needs, or what 'list all' entails (e.g., completeness, ordering). This leaves significant gaps for an agent.

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 one efficient sentence that states the core purpose and optional filtering. There is zero waste, making it highly concise 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 lack of annotations and output schema, the description is incomplete. It doesn't explain return values, error handling, or other contextual details needed for a list operation. This is inadequate for a tool with no structured support.

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 the 'category' parameter with its description. The description adds no additional meaning beyond what the schema provides, such as syntax details or examples, resulting in the baseline score of 3.

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 'List' and the resource 'Reacticx components', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_components' or 'get_component_docs', which prevents 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 implies usage by mentioning optional filtering by category, but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'search_components'. No exclusions or clear context for tool selection are stated.

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 full burden. It describes the search scope (names, descriptions, categories) but lacks critical behavioral details: it doesn't mention if the search is case-sensitive, how results are sorted/limited, whether it supports partial matches, or what the output format looks like. For a search tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 extremely concise (two sentences) and front-loaded with the core purpose. Every word earns its place: the first sentence states the action and resource, the second clarifies the search scope. No redundant or vague language is present.

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 (search operation with one parameter), no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose and search fields but lacks details on behavioral traits, output format, and usage distinctions from siblings. For a search tool, this leaves the agent with incomplete guidance on how to interpret results or choose between similar tools.

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 the single parameter 'query' well-documented in the schema (including examples). The description adds minimal value beyond the schema, only reinforcing that it's a keyword search. Since the schema already provides comprehensive parameter documentation, 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 clearly states the verb ('Search') and resource ('Reacticx components'), specifying what fields are searched (names, descriptions, categories). It distinguishes from 'list_components' by indicating a keyword-based search rather than listing all components. However, it doesn't explicitly differentiate from other siblings like 'get_component_docs' or 'get_dependencies'.

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 context (searching by keyword across multiple fields) but doesn't explicitly state when to use this tool versus alternatives. For example, it doesn't clarify when to use 'search_components' versus 'list_components' (which might return all components without filtering) or 'get_component_docs' (which might retrieve documentation for a specific component). No exclusions or prerequisites are mentioned.

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