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 'safely and effectively,' which hints at safety considerations but doesn't specify what makes it safe (e.g., permissions, side effects, rate limits) or describe the agent's behavior (e.g., how it performs actions, what it returns). This is inadequate for a tool that likely involves system-level operations, leaving critical behavioral traits undocumented.

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 is front-loaded with the core purpose. It avoids redundancy and waste, making it appropriately concise. However, it could be more structured by explicitly separating purpose from guidelines or behavioral details, but it earns high marks for brevity and clarity within its limited scope.

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 of a tool that performs computer actions (likely involving system interactions), the description is incomplete. With no annotations, no output schema, and minimal behavioral transparency, it fails to provide enough context for safe and effective use. The agent lacks information on what the tool returns, error handling, or operational limits, making this inadequate for such a potentially impactful tool.

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 'action' parameter documented as 'The action or task you want to perform on the computer.' The description adds no additional meaning beyond this, such as examples, constraints, or format details. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema does the heavy lifting without extra value from the description.

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 the tool uses an AI agent for computer actions, which gives a vague purpose but lacks specificity about what 'computer actions' entails. It mentions 'safely and effectively' but doesn't clarify what types of actions (e.g., file operations, system commands, GUI interactions) or distinguish it from sibling tools like file_search_agent or multi_tool_agent. This is a minimal viable description that doesn't fully differentiate the tool's scope.

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 context, prerequisites, or exclusions for usage, nor does it reference sibling tools like file_search_agent or multi_tool_agent to help the agent choose appropriately. This leaves the agent with no explicit or implied usage rules.

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 the tool uses an 'AI agent specialized in searching' but doesn't describe how it works (e.g., semantic search vs keyword, ranking approach), what types of files it supports, whether it requires specific permissions, or what the output format looks like. The description is too vague about the actual 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 gets straight to the point without any wasted words. It's appropriately sized for a tool with good schema documentation and no complex behavioral nuances to explain.

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 search tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what constitutes a 'relevant' result, how results are ranked, what file formats are supported, or what the return structure looks like. The agent needs more context to understand what this tool actually delivers.

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 thoroughly. The description adds no parameter-specific information beyond what's in the schema. It mentions 'search query or question' and 'vector stores' indirectly but provides no additional context about parameter usage or relationships.

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: 'searching through files and documents to find relevant information' using an 'AI agent specialized' for this task. It specifies the verb (search) and resource (files/documents), but doesn't distinguish it from sibling tools like 'web_search_agent' which might search different content types.

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 'web_search_agent' or 'multi_tool_agent'. It mentions the tool is 'specialized in searching through files and documents' but doesn't clarify when file/document search is appropriate versus web search or other approaches.

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 orchestrates between capabilities but doesn't describe how the orchestration works, what the agent does (e.g., sequential vs. parallel execution), error handling, or output format. This leaves significant gaps in understanding the tool's behavior beyond basic functionality.

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. It avoids unnecessary words and gets straight to the point, though it could be slightly more informative without sacrificing brevity.

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 (orchestrating multiple capabilities) and lack of annotations and output schema, the description is insufficient. It doesn't explain the orchestration logic, result aggregation, or any behavioral nuances, leaving the agent with incomplete context for 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 fully documents all 5 parameters. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain how 'query' interacts with enabled capabilities or provide examples). Baseline score of 3 is appropriate as the schema handles parameter semantics adequately.

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: 'Use an AI agent that can orchestrate between web search, file search, and computer actions based on your query.' It specifies the verb ('orchestrate') and resources (web search, file search, computer actions), but doesn't explicitly differentiate from sibling tools like computer_action_agent, file_search_agent, and web_search_agent, which are mentioned as siblings but not contrasted in the description.

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 sibling tools (computer_action_agent, file_search_agent, web_search_agent). It mentions the tool can orchestrate between capabilities but doesn't specify scenarios, prerequisites, or exclusions for choosing this multi-tool agent over individual specialized agents.

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 agent is 'specialized in web searching' and aims for 'accurate, up-to-date information,' which adds some context about quality and timeliness. However, it doesn't disclose critical behavioral traits such as rate limits, authentication needs, potential costs, or how results are returned (e.g., format, pagination). For a tool with no annotations, this leaves significant gaps in understanding its operation.

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: using an AI agent for web searching. Every word earns its place by specifying specialization ('specialized in web searching'), quality goals ('accurate, up-to-date'), and source ('from the internet'). There's no redundancy or unnecessary elaboration, making it appropriately sized for the tool's complexity.

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 output schema, no annotations), the description is partially complete. It covers the basic purpose and context but lacks details on behavioral aspects (e.g., how searches are performed, result handling) and doesn't compensate for the absence of an output schema. It's adequate as a starting point but leaves the agent with insufficient information for optimal tool invocation without further exploration.

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 both parameters ('query' and 'location') well-documented in the input schema. The description doesn't add any parameter-specific information beyond what the schema provides (e.g., it doesn't explain query formatting or location usage details). According to the rules, with high schema coverage (>80%), the baseline score is 3 even without param info in the description, which applies here.

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: 'Use an AI agent specialized in web searching to find accurate, up-to-date information from the internet.' It specifies the verb ('find') and resource ('information from the internet'), distinguishing it from sibling tools like 'file_search_agent' (local files) and 'computer_action_agent' (system actions). However, it doesn't explicitly differentiate from 'multi_tool_agent' in terms of web search specialization.

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 by mentioning 'accurate, up-to-date information from the internet,' suggesting this tool is for online research. It doesn't provide explicit when-to-use vs. when-not-to-use guidance or name alternatives among siblings (e.g., use this for web searches vs. 'file_search_agent' for local files). The context is clear but lacks specific exclusions or comparative advice.

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