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 'with curl', hinting at underlying implementation, but fails to disclose critical traits: whether it handles authentication, rate limits, error responses, timeouts, or what the return format looks like. For a tool making HTTP requests, 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 with a single sentence, 'Make an HTTP request with curl', which is front-loaded and wastes no words. Every part of the sentence contributes to understanding the tool's basic function, making it efficient 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 of making HTTP requests, no annotations, no output schema, and 4 parameters, the description is incomplete. It doesn't explain what the tool returns, how errors are handled, or any behavioral nuances. For a tool with this functionality, more context is needed to be fully helpful to an AI 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?

The input schema has 100% description coverage, clearly documenting all 4 parameters (body, headers, type, url). The description adds no additional meaning beyond what the schema provides, such as examples or constraints. With high schema coverage, the 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 states the tool's purpose as 'Make an HTTP request with curl', which is clear but vague. It specifies the verb ('Make') and resource ('HTTP request'), but lacks specificity about what curl entails or how it differs from sibling tools like puppeteer_navigate or semantic_search_requests. It doesn't distinguish itself from alternatives, leaving ambiguity about its 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. With siblings like puppeteer_navigate (for browser navigation) and semantic_search_requests (for search-related requests), there's no indication of appropriate contexts, exclusions, or prerequisites. Usage is implied only by the tool name, not explained.

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, and the description does not disclose behavioral traits such as whether the tool waits for page load, handles errors, or returns navigation status. For a navigation action, these details are important.

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, concise sentence that communicates the core functionality without redundancy. It is appropriately sized and front-loaded.

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 and the absence of an output schema, the description is minimally adequate but lacks completeness. It does not mention return values, timeout behavior, or prerequisites (e.g., an active page).

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 description implies that the 'url' parameter is the target URL for navigation, adding basic meaning beyond the schema. However, with 0% schema description coverage, more detail (e.g., format, allowed protocols) would be beneficial.

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 'Navigate to a URL' clearly states the action (navigate) and the resource (URL). It distinguishes from sibling tools like puppeteer_screenshot or puppeteer_click, which perform different actions.

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?

No guidance is provided on when to use this tool versus alternatives such as puppeteer_connect_active_tab. The description lacks context for appropriate usage scenarios.

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 what the tool does but lacks critical details: whether it requires an active Puppeteer session, if it returns a list or object, potential errors (e.g., no page open), or performance implications. This is inadequate 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 with zero waste. It front-loads the core action ('Get the history') and adds a useful ordering detail ('most recent urls first'). Every word earns its place, 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 no annotations, no output schema, and the tool's potential complexity (interacting with browser history), the description is incomplete. It doesn't cover return format, error conditions, or dependencies (e.g., needing a page object). For a tool with rich behavioral context needs, this is insufficient.

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% (empty schema). The description doesn't need to explain parameters, so it meets the baseline of 4 for parameter-less tools. No additional parameter context is required or provided.

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') and resource ('history of visited URLs'), and specifies ordering ('most recent urls first'). It doesn't explicitly differentiate from sibling tools like 'puppeteer_navigate' or 'make_http_request', but the focus on history retrieval is distinct enough for a 4.

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 prerequisites (e.g., needing an active page), exclusions, or compare it to siblings like 'semantic_search_requests'. This leaves the agent without context for 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 mentions the tool returns 'top 10 results,' which is useful, but lacks critical details: it doesn't specify what 'requests' refer to (e.g., HTTP requests, user requests), how semantic search works, whether it's read-only or has side effects, or any rate limits or permissions required. This is inadequate 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 extremely concise and front-loaded: two sentences that directly state the tool's function and output. Every word earns its place, with no redundant or vague phrasing, making it efficient 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 complexity of a semantic search tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'requests' are, how results are ranked or formatted, or any error conditions. Without this context, an agent might struggle to use the tool correctly or interpret outputs.

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 ('page_url' and 'query') with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate when the schema handles parameter documentation effectively.

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: 'Semantically search for requests that occurred within a page URL.' It specifies the verb (search), resource (requests), and scope (within a page URL). However, it doesn't explicitly differentiate from sibling tools like 'make_http_request' or 'puppeteer_page_history', 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'make_http_request' (for making requests) or 'puppeteer_navigate' (for page navigation), nor does it specify prerequisites or exclusions. This leaves the agent without context for tool selection.

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