Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but provides minimal behavioral context. It states the action but doesn't disclose effects (e.g., page navigation, form submission), error handling, or performance implications. It lacks details like whether it waits for element visibility or handles dynamic content.

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's front-loaded with the core action and method, making it easy 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?

For a tool with no annotations, no output schema, and a single parameter, the description is incomplete. It doesn't cover behavioral traits, error cases, or return values, leaving gaps in understanding how the tool behaves in practice.

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 parameter 'selector' fully documented in the schema. The description adds no additional meaning beyond implying CSS selector usage, matching the schema. Baseline 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 action ('click') and target ('element on the page'), specifying the method ('by CSS selector'). It distinguishes itself from siblings like 'type' or 'navigate' by focusing on clicking, but doesn't explicitly differentiate from other browser interaction tools beyond the verb.

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. It doesn't mention prerequisites (e.g., needing an open browser page), error conditions (e.g., if selector doesn't exist), or sibling tools like 'execute_js' for more complex interactions.

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 behavioral details: it doesn't mention that this executes in the browser context (implying potential side effects like DOM manipulation), whether it returns a value from the script, error handling, security implications, or performance considerations. The description is minimal and doesn't compensate for the absence of annotations.

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, direct sentence with zero wasted words. It front-loads the core action ('Execute JavaScript') and specifies the context ('in the current page context') efficiently. Every word earns its place, making it easy 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 complexity of executing JavaScript in a browser (a potentially powerful and risky operation), the description is incomplete. With no annotations and no output schema, it fails to address key aspects: what the tool returns (e.g., the result of the script, errors), behavioral traits (e.g., side effects, execution context), or error conditions. For a tool with one parameter but significant implicit complexity, this minimal description leaves too many gaps for safe and 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?

The input schema has 100% description coverage, with the single parameter 'script' clearly documented as 'JavaScript code to execute'. The description adds no additional semantic context beyond what the schema provides (e.g., no examples of valid scripts, no mention of async support, or return value handling). Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't enhance parameter understanding but doesn't need to.

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 ('Execute') and resource ('JavaScript in the current page context'), making the purpose immediately understandable. It distinguishes itself from sibling browser tools like click, navigate, or read_page by focusing on script execution rather than navigation or content extraction. However, it doesn't explicitly differentiate from potential JavaScript-related tools that might exist elsewhere in the server.

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 a page loaded first), limitations (e.g., cross-origin restrictions), or when other tools like boj_browser_read_page might be more appropriate for extracting information. The agent must infer usage from the tool name and context 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 full burden for behavioral disclosure. 'Navigate Firefox to a URL' implies a state-changing operation (browser navigation), but doesn't disclose important behavioral traits: whether this opens a new tab or uses current tab, what happens if navigation fails, whether it waits for page load, authentication requirements, or rate limits. The description is minimal and lacks operational context.

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 maximally concise - a single sentence with zero wasted words. It's front-loaded with the core action and resource. Every word earns its place: 'Navigate' (action), 'Firefox' (target), 'to a URL' (resource/destination).

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 browser navigation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after navigation (does it return success/failure? page title? status?), doesn't mention potential side effects (tab creation, history updates), and provides no context about the Firefox instance being controlled. Given the operational nature of browser automation, more behavioral context is needed.

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 'url' clearly documented in the schema. The description doesn't add any parameter semantics beyond what the schema provides (it doesn't specify URL format requirements, validation rules, or examples). With high schema coverage, baseline 3 is appropriate as the schema does the parameter documentation work.

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 ('Navigate Firefox') and resource ('to a URL'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling browser tools like 'boj_browser_read_page' or 'boj_browser_tabs', but the verb 'navigate' is specific enough to distinguish it from other browser interactions.

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 multiple sibling browser tools available (like 'boj_browser_read_page' for reading content or 'boj_browser_tabs' for tab management), there's no indication of when navigation is appropriate versus other browser operations.

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 reads text content but lacks details on what 'text content' includes (e.g., visible text, hidden elements, formatting), whether it handles errors (e.g., if no page is loaded), or any performance considerations (e.g., speed, size limits). This leaves significant gaps in understanding how the tool behaves in practice.

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 function without any unnecessary words or fluff. It's front-loaded with the core action ('Read'), making it easy to understand at a glance, and every part of the sentence contributes to defining the purpose efficiently.

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 browser tool (which can involve dynamic content and errors), no annotations, and no output schema, the description is insufficient. It doesn't explain what 'text content' entails, how it's returned (e.g., as plain text, structured data), or potential limitations (e.g., for JavaScript-heavy pages). This leaves the agent with incomplete information to use the tool effectively in varied contexts.

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 the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline score of 4 is applied as it meets the requirement for a parameterless tool without introducing confusion.

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 ('Read') and resource ('text content of the current page'), making the tool's purpose evident. However, it doesn't explicitly differentiate from sibling browser tools like 'boj_browser_screenshot' (which captures visual content) or 'boj_browser_execute_js' (which runs scripts), leaving some ambiguity about its specific scope within the browser context.

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, such as whether it's for extracting visible text versus full HTML, or how it relates to other browser tools like 'boj_browser_navigate' (for page loading) or 'boj_browser_click' (for interaction). There's no mention of prerequisites, like needing a page to be loaded first, which could lead to misuse.

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 full burden but only states the basic action. It doesn't disclose behavioral traits such as whether this is a read-only operation, what format the screenshot returns (e.g., image data, file path), potential side effects, or any rate limits. 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 that directly states the tool's purpose with no unnecessary words. It's front-loaded and appropriately sized for a simple tool, earning its place without waste.

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 minimal but incomplete. It lacks details on output format (e.g., image data type), behavioral context, and usage guidelines, making it insufficient for an agent to fully understand how to invoke and interpret results.

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 the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here, but doesn't compensate for any gaps since there are none. Baseline is 4 for zero parameters.

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 ('Take a screenshot') and the target ('of the current page'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'boj_browser_read_page' which might also involve page content retrieval, missing full sibling 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 prerequisites (e.g., needing an active browser page), exclusions, or compare it to similar tools like 'boj_browser_read_page', leaving the agent to infer usage context.

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 three operations but doesn't describe their effects (e.g., whether 'create' opens in background/foreground, if 'close' requires confirmation, or if 'list' returns tab metadata). For a tool with potential side effects (create/close), this lack of detail is a significant gap, though it doesn't contradict any annotations.

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 (four words) and front-loaded with all key information. Every word earns its place by specifying the core operations. There's no redundancy or unnecessary elaboration, making it highly efficient for quick understanding.

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 (three distinct operations with side effects), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral traits, error conditions, or return values (e.g., what 'list' outputs). For a multi-operation tool, this minimal description leaves too much undefined 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 description adds no parameter semantics beyond what the schema provides. Since schema description coverage is 100% (each parameter has a description), the baseline score is 3. The description doesn't explain parameter interactions (e.g., 'url' is only for 'create', 'tab_id' for 'close') or provide examples, so it doesn't compensate for potential schema gaps.

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 (list, create, close) and resource (browser tabs). It distinguishes itself from sibling browser tools like 'boj_browser_navigate' or 'boj_browser_read_page' by focusing on tab management rather than page interactions. However, it doesn't explicitly differentiate from non-browser siblings, which keeps 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. It doesn't mention prerequisites (e.g., browser context), exclusions (e.g., when other browser tools might be more appropriate), or comparisons with siblings like 'boj_browser_navigate' for URL handling. Usage is implied through the operation list but not explicitly 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action but doesn't mention important behavioral traits: whether this requires the element to be visible/interactable, if it simulates keystrokes or sets value directly, potential side effects (like triggering events), error conditions, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.

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 states the core functionality without any wasted words. It's appropriately sized for a simple tool and front-loads the essential information. Every word 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?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after typing (success indicators, return values, or error behavior), nor does it provide context about browser state requirements or interaction constraints. The agent lacks sufficient information to use this tool reliably in complex scenarios.

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 (selector and text) clearly documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema descriptions. According to guidelines, when schema coverage is high (>80%), the baseline is 3 even with no param info in 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 clearly states the action ('type text') and target ('into an element on the page'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling browser tools like boj_browser_click or boj_browser_read_page, which would require mentioning this is specifically for input elements rather than general interaction.

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 (like needing a page to be loaded), when not to use it (e.g., for non-input elements), or direct alternatives among the sibling browser tools. The agent 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a read operation ('Get'), but doesn't mention authentication needs, rate limits, error conditions, or what 'detailed information' includes (e.g., format, fields). For a tool with zero annotation coverage, this is insufficient.

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 with zero wasted words. It's appropriately sized for a simple lookup tool and front-loads the core purpose.

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 simple single-parameter lookup tool with good schema coverage but no annotations and no output schema, the description is minimally adequate. It states what the tool does but lacks behavioral context and usage guidance. The absence of output schema means the description should ideally hint at return format, which it doesn't.

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 single parameter 'name' with examples. The description doesn't add any parameter semantics beyond what's in the schema (e.g., doesn't clarify what constitutes a valid cartridge name beyond the examples). Baseline 3 is appropriate when schema does the work.

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 ('Get') and resource ('detailed information about a specific BoJ cartridge'), making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'boj_cartridges' (which likely lists cartridges rather than providing detailed info about a specific one), preventing 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 'boj_cartridges' or 'boj_cartridge_invoke'. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from 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, the description carries full burden but provides minimal behavioral insight. It mentions 'invoke' and 'send a command,' implying a write/mutation operation, but does not disclose permissions, side effects, error handling, or response format. This is inadequate for a tool that likely performs actions with potential consequences.

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 brief (two sentences) and front-loaded with the core action. It avoids redundancy, though it could be more informative without sacrificing 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 no annotations, no output schema, and a tool that likely performs operations (implied by 'invoke'), the description is incomplete. It lacks details on behavior, return values, error cases, or how it fits with siblings, leaving significant gaps for an agent to use it correctly.

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 parameters 'name' and 'params' are documented in the schema. The description adds no extra meaning (e.g., examples of cartridge names or param structures), but the baseline is 3 since the schema handles parameter documentation 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 states the tool 'invoke[s] a BoJ cartridge operation' and 'send[s] a command to a specific cartridge for execution,' which clarifies the verb (invoke/send) and resource (cartridge). However, it lacks specificity about what 'invoke' entails (e.g., running a script, querying data) and does not differentiate from siblings like 'boj_cartridge_info' or 'boj_cartridges,' making it vague in context.

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. The description mentions sending a command to a cartridge but does not specify scenarios, prerequisites, or exclusions compared to sibling tools (e.g., 'boj_cartridge_info' for metadata). This leaves usage unclear.

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 shows a matrix but doesn't describe how it behaves—e.g., whether it's a read-only operation, requires authentication, has rate limits, or returns structured data. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational traits.

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 ('Show the BoJ cartridge matrix') and adds clarifying detail ('protocol x domain grid showing which cartridges serve which protocol/domain combinations'). Every word earns its place with no redundancy or waste.

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 0 parameters, 100% schema coverage, and no output schema, the description is adequate for a simple read operation. However, it lacks details on behavioral aspects like safety or output format, which are important since no annotations or output schema exist. It meets minimum viability but has clear gaps in completeness.

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 baseline for 0 parameters is 4, as the description appropriately doesn't discuss parameters, and the schema fully covers the input structure.

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: 'Show the BoJ cartridge matrix — protocol x domain grid showing which cartridges serve which protocol/domain combinations.' It specifies the verb ('Show'), resource ('BoJ cartridge matrix'), and output format ('protocol x domain grid'), distinguishing it from siblings like 'boj_cartridge_info' or 'boj_cartridge_invoke'. However, it doesn't explicitly differentiate from all siblings, so it's not 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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, nor does it reference sibling tools like 'boj_cartridge_info' for detailed cartridge data. Usage is implied by the purpose but lacks explicit instructions.

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 full burden but offers minimal behavioral insight. It mentions 'manage' which implies both read and write operations, but doesn't disclose authentication requirements, rate limits, error handling, or what 'manage' entails beyond listing resource types. The description is too vague about 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 front-loads the core purpose. It wastes no words, though it could be more structured by separating resource types or adding brief context. For a multi-operation tool, this conciseness is reasonable but not optimal.

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 complex tool with 12 operations, 3 parameters (including a nested object), no annotations, and no output schema, the description is inadequate. It doesn't explain the tool's scope, authentication flow, error conditions, or return formats. The agent must rely entirely on the input schema without contextual guidance.

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 documents all parameters thoroughly. The description adds no parameter-specific information beyond implying the tool handles Cloudflare resources. It doesn't explain the relationship between 'operation' choices and required parameters, or provide context for the 'params' object. Baseline 3 is appropriate when schema does the work.

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 as managing Cloudflare resources with specific examples (Workers, D1 databases, KV namespaces, R2 buckets, DNS zones/records). It uses the verb 'manage' which is appropriate, though it doesn't explicitly differentiate from sibling tools like boj_cloud_vercel or boj_cloud_verpex beyond the Cloudflare focus.

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 like authentication, compare it to sibling cloud tools, or indicate which operations are appropriate for different scenarios. The agent must infer usage from the operation enum 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 full burden but offers minimal behavioral disclosure. It mentions resource types but doesn't describe authentication requirements (though 'api_token' parameter hints at it), rate limits, error handling, or what 'manage' entails (read vs write operations). The description doesn't contradict annotations since none exist, but it fails to provide adequate behavioral context for a multi-operation cloud management tool.

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 lists key resource areas. It's appropriately sized and front-loaded with the main purpose ('Manage Vercel projects'). However, it could be slightly more structured by separating operation categories or adding minimal context about the tool's 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?

For a tool with 3 parameters, no annotations, no output schema, and a complex operation enum (9 options), the description is inadequate. It doesn't explain the tool's multi-operation nature, how operations relate to parameters, what results to expect, or any prerequisites. The description leaves too much undefined 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?

Schema description coverage is 100%, providing good documentation for all 3 parameters. The description adds minimal value beyond the schema—it mentions 'Vercel projects' which aligns with the operation enum, but doesn't explain parameter relationships (e.g., that 'api_token' is specifically for 'authenticate' operation) or provide context for the generic 'params' object. Baseline 3 is appropriate given the schema does most of the work.

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: 'Manage Vercel projects' with specific resource areas listed (deployments, domains, environment variables, logs, serverless functions). It distinguishes from sibling tools by focusing on Vercel cloud operations rather than browser, GitHub, GitLab, or other domains. However, it doesn't specify the exact verb for each operation beyond 'manage'.

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 when to choose specific operations (like 'authenticate' vs 'list-projects'), nor does it differentiate from sibling cloud tools like 'boj_cloud_cloudflare' or 'boj_cloud_verpex'. Usage context is implied but not 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?

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It mentions 'manage' which implies both read and write operations, but doesn't specify authentication requirements, rate limits, error behavior, or what 'manage' entails for each operation type. The description is too vague about the tool's 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 efficiently structured as a single sentence listing the platform, interface, and resource areas. It's appropriately sized for a multi-operation tool, though it could be more front-loaded with clearer purpose. Every element earns its place by conveying 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?

For a complex tool with 6 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the multi-operation nature, authentication flow, error handling, or return formats. The agent must rely entirely on the input schema to understand how to use this tool 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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. It mentions general resource areas but doesn't explain how parameters like 'operation', 'domain', or 'params' relate to those areas. 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 tool's purpose as managing Verpex hosting via cPanel UAPI and lists key resource areas (domains, DNS, email, databases, SSL, cron, metrics). It distinguishes from sibling tools by specifying the Verpex platform, but doesn't explicitly differentiate from other cloud tools like boj_cloud_cloudflare or boj_cloud_vercel beyond the platform name.

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 when to choose Verpex management over other cloud tools, what prerequisites exist (like authentication), or any limitations. The agent must infer usage from the operation list 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 full burden. It mentions operations but doesn't disclose behavioral traits like authentication requirements (implied by 'authenticate' operation but not explained), rate limits, error handling, or what 'check availability' entails. The description is too vague to inform the agent about how the tool behaves beyond basic operation names.

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 and front-loaded with a clear purpose in a single sentence. It efficiently lists key operations without unnecessary elaboration. However, it could be slightly more structured by grouping or explaining operations, but it's appropriately sized with zero waste.

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 (multiple operations, authentication, no output schema, and no annotations), the description is incomplete. It lacks details on authentication flow, operation-specific behaviors, return values, and error cases. For a multi-operation tool with significant behavioral implications, this description is insufficient to guide an 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?

Schema description coverage is 100%, so the schema already documents parameters well. The description adds minimal value beyond the schema—it hints at operations but doesn't provide additional semantics like parameter usage details or constraints. With high schema coverage, the baseline is 3, and 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 as 'Google Calendar operations' with specific verbs (list, create, check) and resources (events, availability). It distinguishes this as a calendar tool among siblings that are mostly browser, GitHub, GitLab, and other operations, though it doesn't explicitly differentiate from boj_comms_gmail which is another communications tool.

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 lists operations but doesn't indicate prerequisites (like authentication), when to choose specific operations, or how this tool relates to sibling tools like boj_comms_gmail. There's no explicit when/when-not or alternative tool recommendations.

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 operations like 'send' and 'manage labels' which imply mutations, but doesn't disclose permissions needed, rate limits, error handling, or what 'authenticate' entails. The description is too vague to inform the agent about key behavioral traits 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 phrase that front-loads the core purpose. It lists key operations without unnecessary elaboration, though it could be slightly more structured (e.g., separating authentication from other operations). Every word earns its place, making it appropriately concise for a multi-operation tool.

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 (multiple operations including mutations like 'send'), lack of annotations, and no output schema, the description is incomplete. It doesn't cover authentication requirements, error cases, or response formats, leaving significant gaps for an AI agent to understand how to invoke it correctly in context.

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 parameters. The description adds minimal value by listing operation types (send, read, search, manage labels) which aligns with the 'operation' enum, but doesn't provide additional semantics like format details or constraints beyond what's in the schema. Baseline 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 as 'Gmail operations — send, read, search emails, manage labels', which specifies the verb 'operations' and resource 'Gmail' with concrete examples. It distinguishes from sibling tools like calendar or GitHub tools by focusing on email functionality, though it doesn't explicitly differentiate from potential overlapping email tools.

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 lists operations but doesn't indicate prerequisites (like authentication), when to choose specific operations, or how it compares to other communication tools like 'boj_comms_calendar'. Usage is implied through the operation list, but no explicit context or exclusions are given.

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 only states the action 'comment' without any information on permissions needed, rate limits, whether the comment is editable, if it triggers notifications, or what the response looks like. This is inadequate for a mutation 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 extremely concise with a single three-word phrase, 'Comment on an issue', which is front-loaded and wastes no words. However, this conciseness comes at the cost of under-specification, but based on the scoring criteria, it earns full points for brevity and structure.

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 GitHub API tool with 4 parameters, no annotations, no output schema, and 0% schema coverage, the description is completely inadequate. It lacks essential details like authentication needs, error handling, return values, and usage context, making it insufficient for effective 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 0%, meaning none of the 4 parameters (owner, repo, issue_number, body) are documented in the schema. The description adds no semantic information about these parameters, such as what 'owner' refers to (e.g., GitHub username/organization) or format requirements for 'issue_number' and 'body'. It fails to compensate for the schema gap.

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 'Comment on an issue' is a tautology that essentially restates the tool name 'boj_github_comment_issue'. It specifies the verb 'comment' and resource 'issue' but lacks any distinguishing details about scope or GitHub context, making it vague compared to more specific descriptions like 'Add a comment to a GitHub issue with markdown support'.

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. It does not mention sibling tools like 'boj_github_create_issue' for creating issues or 'boj_github_get_issue' for retrieving issue details, nor does it specify prerequisites such as authentication or issue state requirements.

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 for behavioral disclosure. It only states the basic action without mentioning permissions required, rate limits, whether it's idempotent, what happens on failure, or the format of the response. This is inadequate for a mutation 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 wasted words. It's front-loaded with the core action and resource, making it easy to scan and understand 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 complexity (a mutation tool with 5 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, parameter details, or expected outcomes, leaving significant gaps for an AI agent to use the tool correctly.

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 0%, so parameters are undocumented in the schema. The description adds no information about parameters beyond implying 'owner', 'repo', 'title', 'body', and 'labels' from the tool name and context. It doesn't explain what these parameters mean, their formats, or constraints, failing to compensate for the schema gap.

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 ('Create an issue') and target resource ('on a GitHub repo'), providing a specific verb+resource combination. It distinguishes from siblings like 'boj_github_comment_issue' or 'boj_github_get_issue' by focusing on creation. However, it doesn't specify scope or constraints beyond the basic action.

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. It doesn't mention prerequisites (e.g., authentication, repository access), compare to similar tools like 'boj_gitlab_create_issue', or indicate when other tools might be more appropriate (e.g., 'boj_github_create_pr' for pull requests).

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 only states the action ('Create a pull request') without disclosing behavioral traits like required authentication, rate limits, whether it's idempotent, what happens on failure, or the expected response format. This is inadequate for a mutation 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's appropriately sized and front-loaded, though it lacks detail, which is a completeness issue rather than 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 complexity of creating a pull request (a mutation with 6 parameters), no annotations, no output schema, and 0% schema coverage, the description is completely inadequate. It doesn't explain parameters, behavior, or return values, leaving the agent with insufficient information to use the tool correctly.

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 0%, meaning none of the 6 parameters (owner, repo, title, body, head, base) are documented in the schema. The description adds no information about what these parameters mean, their formats, or examples, failing to compensate for the coverage gap.

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 'Create a pull request' clearly states the action (create) and resource (pull request), but it's generic and doesn't differentiate from sibling tools like boj_github_merge_pr or boj_gitlab_create_mr. It specifies the GitHub context in the tool name but not 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?

No guidance is provided on when to use this tool versus alternatives like boj_github_create_issue or boj_github_merge_pr. The description lacks context about prerequisites, such as needing an existing repository or branch, or when this is appropriate in a workflow.

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 'gets' file contents, implying a read-only operation, but doesn't specify authentication requirements, rate limits, error handling, or what happens with missing files. This leaves significant gaps for a tool interacting with external APIs.

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 words. It's appropriately sized and front-loaded, making it easy 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 complexity of interacting with GitHub's API (4 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain return values, error conditions, or behavioral nuances, leaving the agent with insufficient information to use the tool effectively beyond basic inference.

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 0%, meaning none of the 4 parameters (owner, repo, path, ref) are documented in the schema. The description adds no information about what these parameters mean, their formats, or examples, failing to compensate for the schema's lack of documentation.

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 ('Get file contents') and target resource ('from a repo'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'boj_github_search_code' or 'boj_github_get_repo' which might have overlapping functionality, preventing 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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions, 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?

No annotations are provided, so the description carries full burden but offers no behavioral details. It doesn't disclose if this is a read-only operation, requires GitHub authentication, has rate limits, returns structured data or raw content, or handles errors. For a tool with 3 parameters and no output schema, this lack of transparency is critical.

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, 'Get a specific issue,' which is front-loaded and wastes no words. While under-specified, it meets the criteria for brevity and structure without redundancy.

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, no annotations, no output schema), the description is severely incomplete. It doesn't cover purpose differentiation, usage context, behavioral traits, parameter meanings, or return values. For a GitHub API tool interacting with issues, this leaves the agent ill-equipped to use it correctly.

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 0%, meaning parameters (owner, repo, issue_number) are undocumented in the schema. The description adds no meaning beyond the tool name—it doesn't explain what these parameters represent (e.g., GitHub username, repository name, issue ID), their formats, or constraints. This leaves the agent guessing about input semantics.

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 'Get a specific issue' restates the tool name (boj_github_get_issue) without adding specificity. It mentions the resource ('issue') but lacks details about what 'get' entails (e.g., retrieving metadata, comments, or full content) and doesn't differentiate from sibling tools like boj_github_list_issues or boj_github_search_issues, making it tautological rather than informative.

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. It doesn't mention prerequisites (e.g., authentication), compare it to siblings like boj_github_list_issues for multiple issues or boj_github_search_issues for filtered searches, or specify use cases (e.g., retrieving a single issue by number). This leaves the agent without context for 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 states 'Get a specific pull request', implying a read-only operation, but does not specify authentication requirements, rate limits, error handling, or what data is returned. This leaves significant gaps in understanding 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 with no wasted words, making it easy to parse. It is appropriately sized for a simple tool, though this conciseness comes at the cost of detail in other dimensions.

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 (3 parameters, no output schema, no annotations), the description is incomplete. It lacks details on parameter usage, behavioral traits, and output format, making it insufficient for an AI agent to fully understand how to invoke the tool correctly without additional context.

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 0%, meaning parameters 'owner', 'repo', and 'pull_number' are undocumented in the schema. The description does not add any meaning or context for these parameters, such as explaining what 'owner' refers to (e.g., GitHub username or organization) or the format of 'pull_number'. It fails to compensate for the low 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 'Get a specific pull request' clearly states the verb 'Get' and resource 'pull request', making the purpose understandable. However, it does not differentiate from sibling tools like 'boj_github_get_issue' or 'boj_github_get_repo', which follow a similar pattern, so it lacks explicit 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, such as 'boj_github_list_prs' for listing multiple pull requests or other GitHub tools for different operations. There is no mention of prerequisites, context, or exclusions, leaving usage unclear.

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. The description 'Get a GitHub repository' gives no information about behavioral traits such as whether this is a read-only operation, what data is returned, error handling, rate limits, authentication requirements, or side effects. This is inadequate for a tool that interacts with an external API like GitHub.

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 with zero wasted words. It's front-loaded with the core action ('Get a GitHub repository'), making it immediately understandable. Every word earns its place, and there's no unnecessary elaboration or redundancy.

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 interacting with GitHub's API, the lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't address what the tool returns (e.g., repository metadata, status codes), error conditions, authentication needs, or how it differs from similar tools. This leaves significant gaps for an AI agent to use the tool 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 2 parameters (owner, repo) with 0% description coverage, meaning the schema provides no semantic information. The description 'Get a GitHub repository' adds minimal context by implying these parameters identify a repository, but it doesn't explain what 'owner' and 'repo' represent (e.g., GitHub username/organization and repository name), their format, or examples. This is insufficient compensation for the schema gap.

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 'Get a GitHub repository' clearly states the verb ('Get') and resource ('GitHub repository'), making the purpose immediately understandable. It distinguishes this tool from other GitHub tools like 'list_repos' or 'get_file' by focusing on retrieving a specific repository. However, it doesn't specify what 'Get' entails (e.g., retrieving metadata vs. full content), 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 when this tool is appropriate (e.g., for retrieving repository details) versus when to use sibling tools like 'boj_github_list_repos' (for listing repositories) or 'boj_github_get_file' (for retrieving specific files). There's no context about prerequisites, authentication needs, or common use cases.

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 states 'Execute a GitHub GraphQL query,' which implies a write operation could be possible (e.g., mutations), but doesn't clarify authentication needs, rate limits, error handling, or what 'execute' entails (e.g., returns raw GraphQL response). This leaves significant behavioral 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 a single, efficient sentence with no wasted words. It's front-loaded and gets straight to the point, making it easy 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 no annotations, 0% schema coverage, no output schema, and 2 parameters (one nested), the description is incomplete. It doesn't cover authentication, error cases, return format, or how to structure queries/variables, leaving the agent with insufficient context for reliable 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 0%, so the description must compensate. It mentions 'GitHub GraphQL query,' which hints at the 'query' parameter's purpose, but doesn't explain the 'variables' parameter or provide any syntax examples, required scopes, or format details. This adds minimal value beyond the bare 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 'Execute a GitHub GraphQL query' clearly states the action (execute) and target (GitHub GraphQL query), which is better than a tautology. However, it's somewhat vague about what specifically is executed (e.g., raw queries vs. predefined operations) and doesn't distinguish it from sibling tools like boj_github_get_repo or boj_github_list_issues, which might also use GraphQL internally.

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 many sibling GitHub tools (e.g., boj_github_get_file, boj_github_list_issues), it's unclear whether this is for custom queries when those specific tools are insufficient, or if it's the primary interface. 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states the basic action without disclosing behavioral traits. It doesn't mention authentication requirements, rate limits, pagination behavior (implied by 'per_page' parameter but not explained), or what the output looks like, leaving significant gaps for a tool that likely interacts with an external API.

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 without unnecessary words. It's front-loaded with the core purpose, making it easy to parse, though this brevity contributes to gaps in other dimensions.

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, 0% schema description coverage, and no output schema, the description is incomplete for a tool with 4 parameters that likely involves API calls. It fails to address authentication, error handling, response format, or usage nuances, leaving the agent with insufficient context to use it 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?

Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'owner' and 'repo' refer to, the meaning of 'state' enum values, or how 'per_page' affects results. This leaves all 4 parameters semantically unclear beyond their schema definitions.

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 ('List') and resource ('issues on a GitHub repo'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'boj_github_search_issues' by focusing on listing rather than searching, though it doesn't explicitly contrast them.

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 like 'boj_github_search_issues' or 'boj_github_get_issue'. The description lacks context about prerequisites (e.g., authentication needs) or typical use cases, offering minimal direction for 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?

With no annotations provided, the description carries full burden but only states the action without disclosing behavioral traits like authentication needs, rate limits, pagination, or response format. It lacks details on what 'list' entails, such as whether it returns all PRs or requires parameters for filtering.

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 just three words, making it front-loaded and efficient. However, it's under-specified rather than optimally concise, as it lacks necessary details for effective tool use.

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 3 parameters with 0% schema coverage, the description is incomplete. It doesn't provide enough context for a tool that likely interacts with GitHub API, missing details on behavior, parameters, and output.

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 0%, so the description must compensate but adds no parameter information. It doesn't explain the meaning of 'owner', 'repo', or 'state' parameters, leaving them undocumented. With 3 parameters and low coverage, this is inadequate.

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 'List pull requests' states the verb and resource clearly, but it's vague about scope and doesn't differentiate from sibling tools like 'boj_github_list_issues' or 'boj_github_get_pr'. It specifies what it does at a basic level but lacks detail about what kind of listing it performs.

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 'boj_github_get_pr' for a single PR or 'boj_github_list_issues' for issues. The description implies usage for listing PRs but offers no context about prerequisites, filtering, or comparison with siblings.

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 'List your GitHub repositories' but doesn't clarify what 'your' means (e.g., authenticated user's repos, includes forks, visibility settings), whether it's paginated, rate-limited, or requires specific permissions. 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, straightforward sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's purpose.

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 (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't cover parameter meanings, behavioral details like pagination or authentication, or output format. For a tool that likely returns a list of repositories, more context is needed to use it effectively without trial and error.

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 2 parameters with 0% description coverage (no schema descriptions). The tool description doesn't mention any parameters, failing to compensate for the lack of schema documentation. It doesn't explain what 'per_page' or 'sort' do, their defaults, or how they affect the listing, leaving parameters semantically unclear.

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 ('List') and resource ('your GitHub repositories'), making the purpose immediately understandable. However, it doesn't differentiate from sibling GitHub tools like 'boj_github_get_repo' or 'boj_github_search_code', which would require more specificity about scope or filtering capabilities.

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 (e.g., authentication), context for listing repositories (e.g., personal vs. organizational), or comparison to sibling tools like 'boj_github_get_repo' for single repos or 'boj_github_search_code' for code-based searches.

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. 'Merge a pull request' implies a write operation that modifies repository state, but it doesn't disclose critical behaviors: authentication requirements, whether merging is destructive or reversible, rate limits, error conditions (e.g., merge conflicts), or what happens on success (e.g., closes PR). This leaves significant gaps for safe agent 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, direct sentence with zero wasted words. It's front-loaded with the core action and resource. While overly brief for completeness, it achieves maximum efficiency in its given form without redundancy or fluff.

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 (a mutation operation with 4 parameters), lack of annotations, 0% schema coverage, and no output schema, the description is severely incomplete. It doesn't address behavioral risks, parameter meanings, usage context, or expected outcomes. For a GitHub merge tool, this leaves the agent guessing about critical operational details.

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 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'owner', 'repo', 'pull_number', or 'method' represent, their formats, or that 'method' has enum values (merge, squash, rebase). With 4 parameters completely undocumented in both schema and description, this is inadequate for proper tool invocation.

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 'Merge a pull request' clearly states the action (merge) and resource (pull request) with a specific verb. It distinguishes this tool from sibling GitHub tools like 'boj_github_create_pr' or 'boj_github_get_pr' by focusing on merging rather than creation or retrieval. However, it doesn't specify the platform (GitHub) which is implied by the tool name but could be more explicit.

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., pull request must be in a mergeable state), exclusions (e.g., not for draft PRs), or related tools (e.g., use 'boj_github_get_pr' to check status first). The agent must infer usage from the tool name and context 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 but offers no information about how the search works, what permissions are required, rate limits, pagination behavior, or what the response contains. 'Search code on GitHub' is a minimal statement that doesn't describe any behavioral traits beyond the basic action implied by the name.

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 at just three words, with zero wasted language. It's front-loaded with the essential action and target, making it immediately scannable and efficient.

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 search operation, no annotations, no output schema, and poor parameter documentation, the description is incomplete. It doesn't explain what the tool returns, how results are structured, or provide any context about GitHub's code search capabilities, leaving significant gaps for an agent trying to use this tool 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 1 parameter with 0% description coverage, meaning the schema provides no documentation about the 'query' parameter. The description doesn't compensate by explaining what the query parameter should contain (e.g., search syntax, supported operators, examples), leaving the parameter's semantics completely 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 'Search code on GitHub' clearly states the action (search) and target resource (code on GitHub), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'boj_github_search_issues', which performs a similar search operation but for issues rather than code.

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. There are multiple GitHub-related sibling tools (e.g., 'boj_github_search_issues', 'boj_github_get_file', 'boj_github_list_repos') that serve different purposes, but the description doesn't indicate when this code search tool is appropriate versus those other options.

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 for behavioral disclosure. It only states the action ('Search issues and PRs') without any information about permissions required, rate limits, pagination, output format, or whether this is a read-only operation. This leaves critical behavioral traits unspecified.

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 no wasted words. It's appropriately sized for a simple tool and front-loaded with the core action, making it easy 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 no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain what the search returns, how results are structured, or any behavioral aspects like authentication or limits. For a search tool with one parameter, more context is needed to be fully helpful.

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 0%, with one parameter 'query' undocumented in the schema. The description adds no information about what the query parameter should contain (e.g., search syntax, filters, GitHub query language), failing to compensate for the schema gap. It merely implies searching without parameter details.

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 'Search issues and PRs on GitHub' clearly states the verb (search) and resource (issues and PRs on GitHub), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'boj_github_list_issues' or 'boj_github_list_prs', which appear to list rather than search, so it misses full 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. With siblings like 'boj_github_list_issues' and 'boj_github_list_prs' that might serve similar listing functions, there's no indication of when search is preferred over list operations or what specific search capabilities this offers.

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, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this requires authentication, has rate limits, returns an issue ID, or what happens on failure. For a mutation tool, this lack of transparency is a significant gap.

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 no wasted words. It's front-loaded and appropriately sized for its content, though brevity contributes to under-specification rather than 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?

For a mutation tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on behavior, parameters, and expected outcomes, making it inadequate for effective tool 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 0%, and the description adds no parameter information. It doesn't explain what 'project_id', 'title', or 'description' mean, their formats, or constraints. With 3 parameters undocumented, this fails to compensate for the schema gap.

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 'Create a GitLab issue' clearly states the action (create) and resource (GitLab issue), but it's vague about scope and lacks differentiation from sibling tools like boj_github_create_issue. It doesn't specify what an 'issue' entails in GitLab context, making it minimally adequate but with gaps.

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. It doesn't mention prerequisites (e.g., authentication), compare to siblings like boj_gitlab_list_issues or boj_github_create_issue, or indicate when not to use it. This leaves the agent without contextual usage direction.

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 only states the action ('Create') without any details on permissions required, side effects, error handling, rate limits, or what the tool returns. This is inadequate for a mutation 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 extremely concise with just three words, front-loaded with the core action. There is no wasted language, though this brevity contributes to the lack of detail in other dimensions.

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 creating a merge request (a mutation operation), the absence of annotations and output schema, and 0% schema description coverage, the description is completely inadequate. It provides no behavioral context, parameter guidance, or usage instructions, leaving critical gaps for 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 0%, meaning none of the 4 parameters (project_id, title, source, target) are documented in the schema. The description adds no information about what these parameters mean, their formats, or how they interact, failing to compensate for the schema gap.

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 'Create a merge request' clearly states the action (create) and resource (merge request), but it's vague about scope and lacks differentiation from sibling tools like 'boj_gitlab_create_issue' or 'boj_github_create_pr'. It doesn't specify what system or context this applies to beyond the tool name hinting at GitLab.

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. There are multiple sibling tools for creating items (e.g., 'boj_gitlab_create_issue', 'boj_github_create_pr'), but the description offers no context, prerequisites, or comparisons to help an agent choose appropriately.

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 'Get a GitLab project' but doesn't clarify if this is a read-only operation, what data is returned, error handling, authentication needs, or rate limits. This leaves significant gaps for an AI 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 extremely concise with just four words, front-loading the core purpose without any wasted text. It efficiently communicates the essential action and resource, though this brevity contributes to gaps in other dimensions.

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 insufficiently complete. It doesn't explain what 'get' returns (e.g., project details, metadata), error conditions, or how it differs from sibling tools, leaving the AI agent with inadequate 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?

The input schema has 100% description coverage, with the parameter 'project_id' documented as 'Project ID or URL-encoded path'. The description adds no additional semantic context beyond this, so it meets the baseline score of 3 where the schema handles parameter documentation 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 action ('Get') and resource ('a GitLab project'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'boj_gitlab_list_projects' or specify what 'get' entails (e.g., retrieving metadata vs. full project data).

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 like 'boj_gitlab_list_projects' for listing multiple projects or other GitLab tools. The description lacks context about prerequisites, such as needing a specific project ID, or when this tool is appropriate.

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 full burden for behavioral disclosure. 'List GitLab project issues' implies a read-only operation but doesn't specify authentication requirements, rate limits, pagination behavior, or what data is returned. For a tool with zero 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 with zero wasted words. It's appropriately sized for a simple listing tool and front-loads the essential information immediately.

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 tool with 2 parameters, 0% schema description coverage, no annotations, and no output schema, the description is insufficient. It doesn't compensate for the lack of structured documentation about parameters, behavior, or return values. The description alone doesn't provide enough context for reliable 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 0%, meaning neither parameter has any documentation in the schema. The description provides no information about parameters beyond what's inferred from the tool name. It doesn't explain what 'project_id' represents, what format it expects, or what the 'state' enum values mean in context.

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 'List GitLab project issues' clearly states the action (list) and resource (GitLab project issues), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'boj_gitlab_list_projects' or other listing tools in the server, 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. There are multiple sibling tools for listing (e.g., boj_gitlab_list_projects, boj_gitlab_list_mrs, boj_gitlab_list_pipelines) and no indication of when this specific issue-listing tool is appropriate versus other GitLab or GitHub issue tools.

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 'List merge requests', implying a read-only operation, but doesn't specify permissions, rate limits, pagination, or what data is returned. This is inadequate for a tool with parameters and no output schema, as critical behavioral traits are missing.

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 'List merge requests', a single phrase that is front-loaded and wastes no words. It efficiently conveys the core action, though this brevity contributes to gaps in other dimensions.

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, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't cover parameter meanings, behavioral aspects like permissions or output format, or usage context. For a tool with this complexity, more information is needed to be adequately helpful.

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 0%, so the schema provides no parameter descriptions. The description adds no information about parameters, failing to explain 'project_id' or 'state' (including the enum values like 'opened', 'closed'). This leaves parameters undocumented, with the description not compensating for the schema gap.

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 'List merge requests' clearly states the verb ('List') and resource ('merge requests'), making the basic purpose understandable. However, it lacks specificity about scope (e.g., for a project, user, or all) and doesn't differentiate from sibling tools like 'boj_gitlab_list_issues' or 'boj_gitlab_list_projects', which reduces clarity in a multi-tool context.

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. The description doesn't mention context, prerequisites, or exclusions, such as how it relates to sibling tools like 'boj_gitlab_create_mr' or 'boj_gitlab_list_issues'. This leaves the agent without explicit direction 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. 'List CI/CD pipelines' implies a read-only operation, but it doesn't specify critical details like authentication requirements, rate limits, pagination behavior, or what data is returned (e.g., pipeline statuses, IDs). This leaves significant gaps in understanding how the tool behaves in practice.

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 phrase, 'List CI/CD pipelines', which is front-loaded and wastes no words. While it may be too brief for completeness, it efficiently conveys the core action without unnecessary elaboration.

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 CI/CD pipeline listing tool with no annotations, no output schema, and a parameter with 0% schema coverage, the description is incomplete. It doesn't address key aspects like return values, error handling, or operational constraints, making it inadequate for the agent to use the tool effectively without additional context.

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 one parameter ('project_id') with 0% description coverage, meaning the schema provides no semantic details. The description adds no information about parameters, failing to explain what 'project_id' represents (e.g., a GitLab project ID or name) or its format, which is insufficient given the low schema 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 'List CI/CD pipelines' clearly states the verb ('List') and resource ('CI/CD pipelines'), providing a basic understanding of the tool's function. However, it doesn't differentiate from sibling tools like 'boj_gitlab_list_issues' or 'boj_gitlab_list_mrs', which follow a similar pattern for different resources, making the purpose somewhat generic rather than specific.

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. The description lacks context such as prerequisites (e.g., authentication), when it's appropriate (e.g., for monitoring pipelines), or comparisons to other GitLab tools like 'boj_gitlab_list_projects', leaving the agent without usage direction.

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 full burden but only states the basic action. It lacks details on behavior such as pagination (implied by 'per_page' param), authentication requirements, rate limits, or output format (e.g., list structure, fields returned). This is inadequate for a tool with potential complexity.

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 no wasted words. It is front-loaded and directly states the tool's function, making it easy 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 no annotations, 0% schema coverage, no output schema, and one undocumented parameter, the description is incomplete. It doesn't explain key aspects like how projects are filtered (e.g., by user, visibility), what data is returned, or behavioral constraints, leaving significant gaps for 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?

Schema description coverage is 0%, so the description must compensate but adds no parameter information. The 'per_page' parameter is undocumented in both schema and description, leaving its purpose (e.g., pagination control) unclear. This fails to address the coverage gap.

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 'List your GitLab projects' clearly states the action (list) and resource (GitLab projects), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'boj_gitlab_get_project' or 'boj_github_list_repos', which would require specifying scope or ownership details.

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. It doesn't mention prerequisites (e.g., authentication), context (e.g., personal vs. group projects), or compare to siblings like 'boj_gitlab_get_project' for single projects or GitHub tools for cross-platform needs.

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 states 'Set up a push mirror', implying a write/mutation operation, but doesn't disclose behavioral traits such as required permissions, whether it's idempotent, potential side effects (e.g., overwriting existing mirrors), or error handling. This leaves significant gaps for safe agent use.

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 sentence, 'Set up a push mirror', which is appropriately concise and front-loaded. However, it's under-specified rather than efficiently informative, slightly reducing its effectiveness.

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, 0% schema coverage, no output schema, and 2 parameters, the description is incomplete. It lacks details on usage context, parameter semantics, behavioral transparency, and expected outcomes, making it insufficient for a mutation tool in a complex domain like GitLab.

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 0%, so the description must compensate. It adds no meaning beyond the schema—doesn't explain what 'project_id' or 'target_url' represent (e.g., GitLab project ID format, valid URL patterns for mirrors). With 2 undocumented parameters, this is inadequate, scoring below the baseline of 3 for high schema 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 'Set up a push mirror' clearly states the action (set up) and resource (push mirror), but it's vague about what a 'push mirror' entails in this context (e.g., GitLab repository mirroring). It doesn't distinguish from sibling tools like boj_gitlab_list_projects or boj_gitlab_create_mr, which are unrelated but share the GitLab domain.

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. It doesn't mention prerequisites (e.g., needing an existing GitLab project), exclusions, or related tools like boj_gitlab_get_project for verifying project_id. The context is implied from the tool name but not explicitly 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 the full burden of behavioral disclosure. It states the action ('Check') but doesn't describe what the check entails (e.g., ping, status codes, uptime), what the output might look like, or any side effects like rate limits. 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 with no wasted words. It's front-loaded with the core action and resource, making it easy to scan and understand quickly. This is an excellent example of 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's simplicity (0 parameters, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks details on behavior and usage context. For a health check tool, more information on expected outputs or typical use cases would enhance completeness, but it's adequate for basic understanding.

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 the schema fully documents the absence of inputs. The description doesn't need to add parameter details, and it correctly implies no inputs are required, aligning with the schema. A baseline of 4 is appropriate for a zero-parameter tool.

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 ('Check') and resource ('BoJ server health status'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools, as none appear to be health-check related, so this is adequate but not exceptional.

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. The description lacks context about when health checks are appropriate, such as after deployment or during troubleshooting, which would help an agent decide when to invoke it.

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 this is a list operation, implying it's read-only and non-destructive, but doesn't mention any behavioral traits like rate limits, authentication needs, pagination, or error handling, which are critical for a tool with no structured annotations.

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 key action ('List all BoJ cartridges') and specifies the returned data without any fluff. Every word serves a purpose, making it highly concise and well-structured for quick understanding.

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), the description is adequate but has gaps. It lacks behavioral context (e.g., how data is formatted or if it's paginated) and doesn't differentiate from siblings, making it minimally viable but incomplete for optimal agent use without additional structured data.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and the baseline score for 0 parameters is 4, as it avoids unnecessary details while being complete in this context.

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 ('List all') and the resource ('BoJ cartridges'), specifying the data fields returned (domains, protocols, tiers, availability). However, it doesn't explicitly differentiate from sibling tools like 'boj_cartridges' or 'boj_cartridge_info', which appear related, leaving some ambiguity about when to choose this specific tool.

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 sibling tools like 'boj_cartridges' and 'boj_cartridge_info' that seem related to cartridges, there's no indication of context, prerequisites, or exclusions to help an agent select appropriately among them.

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 lists operations but doesn't disclose behavioral traits like authentication requirements (implied by 'authenticate' operation but not explained), rate limits, response formats, or error handling. For a multi-operation tool with no annotations, this is insufficient.

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 and front-loaded, listing key operations in a single sentence. It avoids unnecessary words, though it could be slightly more structured (e.g., grouping operations). Every part contributes to understanding the tool's 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 tool's complexity (multiple operations, nested params object, no output schema, and no annotations), the description is incomplete. It lacks details on authentication, operation-specific behaviors, return values, and error cases, making it inadequate for an AI agent to use effectively without trial and error.

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 parameters. The description adds minimal value by hinting at operation types but doesn't provide additional semantics beyond what's in the schema (e.g., details on 'params' object). Baseline 3 is appropriate given high schema 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 tool performs 'Hugging Face operations' and lists specific operations like search models, model info, inference, spaces, and datasets. It provides a verb+resource combination but doesn't differentiate from siblings since all other tools are unrelated (browser, cloud, GitHub, etc. operations).

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. The description merely lists operations without indicating context, prerequisites, or exclusions. There's no mention of when to choose specific operations or how this tool relates to other ML/AI tools.

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 'Academic research' and lists operations, but fails to describe critical behaviors such as authentication needs (implied by the 'authenticate' operation in the schema), rate limits, error handling, or what the tool returns (since there's no output schema). This is inadequate for a tool with multiple operations and no structured safety hints.

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 very concise—a single phrase listing key operations. It's front-loaded with the domain ('Academic research') and wastes no words, though it could be more structured (e.g., separating operations with commas or bullet points). Every word contributes to the purpose, making it efficient.

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 (multiple operations via the 'operation' parameter, nested 'params' object, and no output schema), the description is incomplete. It doesn't explain how to use the operations, what inputs are needed for each, or what to expect in return. With no annotations and rich input schema, the description should provide more context 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?

Schema description coverage is 100%, so the schema already documents all parameters (operation, api_key, params) with descriptions and an enum for operation. The description adds minimal value beyond the schema by listing some operation types (e.g., 'search papers, citations, references, authors'), but it doesn't provide additional syntax, format details, or usage examples. This meets the baseline for high schema 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 tool's purpose as 'Academic research — search papers, citations, references, authors', which specifies the domain (academic research) and the main operations (search, citations, references, authors). It distinguishes from most sibling tools which are focused on browser automation, cloud services, GitHub/GitLab operations, and other domains, though it doesn't explicitly differentiate from other potential research tools that might exist.

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 lists operations but doesn't indicate prerequisites (e.g., authentication requirements), when to choose specific operations, or how it compares to other tools in the sibling list (e.g., if there are overlapping functionalities). This leaves the agent with minimal context for decision-making.

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