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 that selecting a technology 'scope[s] all subsequent searches and documentation lookups,' which implies a stateful or persistent effect, but doesn't detail how this scoping works (e.g., is it session-wide, does it affect all sibling tools, are there limitations or side effects). For a tool with potential global impact and no annotation coverage, this is a significant gap in transparency.

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 clearly states the tool's purpose and effect. It is front-loaded with the core action ('Select the framework/technology') and avoids unnecessary details, making it easy to understand quickly. Every word earns its place by contributing to clarity.

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 complexity (stateful scoping with potential global effects), no annotations, no output schema, and high schema coverage, the description is minimally adequate. It explains the purpose but lacks details on behavior, return values, or integration with sibling tools. For a tool that sets context for subsequent operations, more completeness would be beneficial to guide the agent effectively.

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 both parameters ('identifier' and 'name') documented in the schema. The description doesn't add any meaning beyond what the schema provides, such as explaining the relationship between 'identifier' and 'name' or providing examples of valid inputs. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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: 'Select the framework/technology to scope all subsequent searches and documentation lookups.' It specifies a verb ('Select') and resource ('framework/technology'), and explains the downstream effect ('scope all subsequent searches and documentation lookups'). However, it doesn't explicitly differentiate from siblings like 'current_technology' or 'discover_technologies', which could clarify its unique role.

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 when to use this tool by stating it 'scope[s] all subsequent searches and documentation lookups,' suggesting it should be used to set a context for future operations. However, it doesn't provide explicit guidance on when to use it versus alternatives like 'current_technology' (which might retrieve the current setting) or 'discover_technologies' (which might list options), nor does it mention any exclusions or prerequisites.

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 reports information and provides guidance on changing technology, implying a read-only operation, but lacks details on permissions, response format, or potential side effects. This is a significant gap for a tool with zero 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 a single, efficient sentence that front-loads the core purpose ('report the currently selected technology') and adds a useful extension ('and how to change it'). There is zero waste, 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 simplicity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It covers the basic purpose but lacks behavioral details and usage guidelines, making it minimally viable for a read-only reporting tool in a context with sibling alternatives.

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 with 100% schema description coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, earning a baseline score of 4 for not adding unnecessary information 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 the tool's purpose: to report the currently selected technology and provide information on how to change it. This specifies both the action ('report') and the resource ('currently selected technology'), though it doesn't explicitly differentiate from sibling tools like 'choose_technology' or 'get_version'.

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 mentions 'how to change it,' which might imply usage before or after 'choose_technology,' but there are no explicit instructions on context, prerequisites, or exclusions relative to siblings like 'discover_technologies' or 'get_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?

No annotations are provided, so the description carries the full burden. It mentions 'Explore and filter' but doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, pagination behavior beyond schema hints, or what the output format looks like. The description adds minimal context beyond the basic action.

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 ('Explore and filter available Apple technologies/frameworks') and adds context ('before choosing one') without any wasted words. Every part earns its place.

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 annotations, no output schema, and a tool with three parameters for filtering and pagination, the description is incomplete. It doesn't explain what 'technologies/frameworks' entails, how results are structured, or any behavioral constraints. For a discovery tool with filtering capabilities, more context is needed to guide effective use.

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 all three parameters (page, pageSize, query) with their types and defaults. The description adds no additional parameter semantics beyond implying filtering via 'query', which is already covered in the schema. 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 action ('Explore and filter') and resource ('available Apple technologies/frameworks'), and distinguishes it from sibling tools by mentioning 'before choosing one' (implying choose_technology is for selection). However, it doesn't explicitly differentiate from other siblings like search_symbols or get_documentation, which might also involve exploration.

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 ('before choosing one') by referencing choose_technology, suggesting this tool is for preliminary exploration. However, it lacks explicit guidance on when to use this versus alternatives like search_symbols or get_documentation, and doesn't specify any exclusions or prerequisites.

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 'detailed documentation' but doesn't specify what that includes (e.g., format, length, examples) or any constraints like rate limits, authentication needs, or error handling. The phrase 'within the selected technology' hints at a prerequisite but doesn't clarify how technology selection works (e.g., via 'choose_technology' sibling). This leaves significant gaps 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 concise with two sentences that efficiently cover purpose and usage. It's front-loaded with the core function and includes helpful examples. There's no wasted text, though it could be slightly more structured by separating prerequisites or constraints into distinct points.

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 basic purpose and parameter usage but lacks details on behavioral aspects like output format, error cases, or dependencies on other tools (e.g., technology selection). Without annotations or output schema, more context would be beneficial for effective agent use.

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 parameter 'path' fully documented in the schema as 'Symbol path or relative name'. The description adds minimal value beyond this, only repeating 'Accepts relative symbol names' and providing examples like '"View"'. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

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 detailed documentation for specific symbols within the selected technology.' It specifies the verb ('Get'), resource ('documentation'), and scope ('specific symbols within the selected technology'). However, it doesn't explicitly differentiate from sibling tools like 'search_symbols' or 'discover_technologies' beyond mentioning 'known symbol 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?

The description provides some guidance with 'Use this for known symbol names (e.g., "View", "Button", "GridItem")', which implies this tool is for lookup rather than discovery. However, it doesn't explicitly state when not to use it or name alternatives like 'search_symbols' for unknown symbols, leaving usage context somewhat implied rather than fully explicit.

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. While 'Get' implies a read operation, the description doesn't specify whether this requires authentication, what the response format looks like, or any rate limits. It lacks details on what 'version information' includes (e.g., server version, API version) or potential side effects.

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, clear sentence that directly states the tool's purpose without any fluff or redundant information. It is front-loaded and appropriately sized for a simple tool with no parameters, making it easy for an agent to parse quickly.

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 has gaps. It explains what the tool does but doesn't provide context on when to use it, what the output entails, or how it fits with sibling tools. For a basic read operation, it meets minimum viability but could be more informative about behavioral aspects.

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 no parameter documentation is needed. The description appropriately doesn't discuss parameters, which is efficient and avoids redundancy. A baseline of 4 is applied as it correctly handles the absence of parameters without adding unnecessary information.

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 current version information of the Apple Doc MCP server.' It uses a specific verb ('Get') and identifies the resource ('version information'), though it doesn't explicitly differentiate from sibling tools like 'current_technology' or 'discover_technologies' which might also provide version-related information.

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 any prerequisites, context for usage, or how it differs from sibling tools such as 'current_technology' or 'discover_technologies', leaving the agent to infer usage based on the tool name 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'supports wildcards (* and ?)' which adds useful context about search capabilities, but doesn't cover important behavioral aspects like pagination behavior (only mentions maxResults default), error handling, or what happens when no results are found. The description is adequate but has clear gaps in behavioral transparency.

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 perfectly concise and well-structured in just two sentences. The first sentence states the purpose and primary use case, the second provides important behavioral detail (wildcard support) and sibling differentiation. Every sentence earns its place with no wasted words.

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 (4 parameters, no output schema, no annotations), the description is reasonably complete but has gaps. It covers purpose, usage guidelines, and some behavioral aspects, but doesn't address what the tool returns (no output schema means the description should ideally mention return format) or important constraints like rate limits or authentication requirements.

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 has 100% description coverage, so the baseline is 3. The description adds some value by mentioning wildcard support in the context of the query parameter ('Search keywords with wildcard support'), but doesn't provide additional semantic context beyond what's already documented in the schema descriptions for each parameter.

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 discover symbols') and resource ('within the currently selected technology'), distinguishing it from sibling tools like get_documentation (for specific known symbols) and choose_technology/current_technology/discover_technologies (which handle technology selection rather than symbol 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?

The description provides explicit usage guidance: 'Use this for exploration and finding symbols by keywords' and 'For specific known symbols, use get_documentation instead.' This clearly defines when to use this tool versus alternatives, including both positive guidance (when to use) and negative guidance (when not to use).

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