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 generating install buttons but lacks details on what these buttons do (e.g., install Copilot extensions, trigger actions), the output format (e.g., HTML, markdown), any rate limits, authentication needs, or side effects. This leaves significant gaps for an agent to understand the tool's 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 that front-loads the core purpose ('Generate VS Code install buttons') and includes essential parameter information without unnecessary details. Every word contributes directly to the tool's functionality, 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 complexity (5 parameters, 40% schema coverage, no output schema, and no annotations), the description is incomplete. It doesn't explain the output (what the generated buttons look like or how to use them), lacks behavioral context, and leaves key parameters underspecified, making it inadequate for an agent to fully understand the tool's operation.

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 40% (only 'kind' and 'path' have descriptions), and the description adds minimal semantic value by listing parameters ('owner/repo/path and optional branch') without explaining their roles or relationships. It doesn't clarify what 'kind' enums represent or how 'branch' defaults to 'main', leaving parameters partially undocumented.

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 ('Generate VS Code install buttons') and target resource ('for a GitHub file'), with specific identifiers ('using owner/repo/path and optional branch'). However, it doesn't explicitly differentiate from sibling tools like 'copilot_buttons_from_raw' or 'make_install_buttons', which likely serve similar purposes but with different input sources.

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., 'copilot_buttons_from_raw' or 'make_install_buttons'), nor does it mention any prerequisites, exclusions, or alternative scenarios. It only states what the tool does without contextual usage advice.

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 states the tool 'generates' something, implying a read-only or creation operation, but does not clarify if this involves side effects, authentication needs, rate limits, or output format. For a tool with no annotations, this leaves significant behavioral gaps, as it doesn't describe what the generated buttons look like or how they are returned.

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 directly states the tool's purpose without unnecessary details. It is front-loaded with the core action and resource, making it easy to parse. There is no wasted language, and every word contributes to understanding the tool's function, exemplifying optimal conciseness.

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 no annotations and no output schema, the description is incomplete. It explains what the tool does but lacks details on behavioral aspects like side effects, authentication, or what the generated buttons entail. For a tool that likely produces visual or interactive elements, the absence of output information and behavioral context makes it insufficient for full agent understanding, especially compared to richer tool definitions.

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 both parameters ('kind' and 'url') well-documented in the schema. The description adds minimal value beyond the schema, as it only reiterates that the URL is for 'chat instructions, prompts, or chat modes', which aligns with the enum values in the schema. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description does not 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: 'Generate VS Code install buttons for a raw URL to chat instructions, prompts, or chat modes.' It specifies the verb ('generate'), resource ('VS Code install buttons'), and target ('raw URL to chat instructions, prompts, or chat modes'), making the action clear. However, it does not explicitly differentiate from sibling tools like 'copilot_buttons_from_github', which likely serves a similar purpose but with different input sources, leaving room for improvement in sibling distinction.

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 the input is a 'raw URL' but does not specify scenarios where this is preferred over sibling tools like 'copilot_buttons_from_github' or 'from_mcp_config'. Without explicit when-to-use or when-not-to-use instructions, the agent lacks context for tool selection, resulting in minimal 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates something ('install buttons'), implying a creation or transformation operation, but doesn't specify what the output looks like, whether it's idempotent, if there are side effects, or any performance considerations. The description is too vague to provide meaningful behavioral insights 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 directly states the tool's function and inputs without unnecessary words. It's front-loaded with the core action and avoids redundancy, making it easy to parse quickly. Every part of the sentence contributes essential information, earning 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 the tool has 2 parameters with only 50% schema coverage, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain the output format (what 'install buttons' are), lacks behavioral details, and provides minimal parameter guidance. For a tool that generates something from config data, more context is needed to ensure correct usage by an 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 description coverage is 50% (only 'name' has a description), and the description adds minimal value beyond the schema. It mentions 'raw MCP JSON-like config object' for the 'mcp' parameter, which hints at its type but doesn't clarify format, structure, or constraints. Since schema coverage is moderate, the description partially compensates but leaves key details undocumented, aligning with the baseline for this coverage level.

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 ('Generate install buttons') and the inputs ('from a raw MCP JSON-like config object and a server name'), making the purpose understandable. It distinguishes itself by specifying the source as 'MCP config', which differentiates it from sibling tools like 'copilot_buttons_from_github' or 'copilot_buttons_from_raw'. However, it doesn't fully specify what 'install buttons' are or their format, leaving some ambiguity.

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 the inputs but doesn't explain scenarios where this is preferred over sibling tools like 'make_install_buttons' or 'copilot_buttons_from_raw'. There's no mention of prerequisites, constraints, or typical use cases, leaving the agent without contextual usage cues.

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 generates markdown, implying a read-only output, but doesn't cover aspects like required permissions, rate limits, or what the generated markdown looks like (e.g., format, links). For a tool with no 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 without unnecessary words. Every part ('Generate', 'VS Code Stable and Insiders MCP install button markdown', 'for an NPX-based server') contributes directly to understanding the tool's function.

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 (3 parameters with nested objects, low schema coverage, no annotations, and no output schema), the description is insufficient. It doesn't explain the output format, parameter interactions, or behavioral constraints, leaving the agent with incomplete context for proper tool invocation.

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 low at 33%, with only the 'name' parameter documented. The description adds no parameter-specific information beyond implying NPX-based server configuration, which loosely relates to the 'config' parameter but doesn't detail the 'inputs' array or other fields. This provides marginal value, aligning with the baseline for partial 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 action ('Generate') and the output ('VS Code Stable and Insiders MCP install button markdown') with specific context ('for an NPX-based server'), which distinguishes it from sibling tools like 'copilot_buttons_from_github' that likely generate different types of buttons. However, it doesn't explicitly differentiate from all siblings (e.g., 'from_mcp_config'), keeping 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 no guidance on when to use this tool versus alternatives like the sibling tools listed. It mentions the context ('NPX-based server') but doesn't specify prerequisites, exclusions, or comparisons to other button-generation tools, leaving the agent with minimal usage direction.

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