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 ('add issue') without disclosing behavioral traits. It doesn't mention permissions needed, side effects, response format, or error handling. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient phrase ('課題の追加') that directly states the tool's action. It's front-loaded with no wasted words, making it highly concise and well-structured for its minimal content.

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 this is a mutation tool (create) with no annotations, no output schema, and siblings that are mostly read operations, the description is incomplete. It doesn't explain what an 'issue' is, how creation works, or what to expect upon success/failure, leaving critical gaps for agent usage.

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 doesn't add param info, which is appropriate here. Baseline is 4 for zero parameters, as the schema fully covers the absence of inputs.

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 '課題の追加' (Japanese for 'add issue') states a verb and resource, but it's vague about what an 'issue' entails in this context and doesn't differentiate from siblings like getIssue or getIssues. It avoids tautology by not just restating the name, but lacks specificity about the system 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. The description doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from sibling names alone. This is inadequate for a creation tool in a system with multiple read 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states it retrieves information, implying a read-only operation, but doesn't cover aspects like authentication needs, error handling, rate limits, or what constitutes 'specific' (e.g., by ID). It lacks behavioral details beyond the basic purpose.

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 in Japanese that directly states the purpose without waste. It's appropriately sized for a simple tool, though it could be more structured if it included usage notes. No fluff or redundancy is present.

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 doesn't explain what 'specific' means, how to identify issues, or what information is returned, leaving gaps for the agent. For a retrieval tool with no structured guidance, it should provide more 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 0 parameters with 100% description coverage, so no parameters need documentation. The description doesn't add parameter details, but with no parameters, the baseline is 4 as it doesn't need to compensate for gaps. It's adequate given the schema's completeness.

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 '特定の課題情報の取得' (retrieves specific issue information) states a clear verb ('取得' - retrieve) and resource ('課題情報' - issue information), but it's vague about what makes an issue 'specific' and doesn't differentiate from sibling tools like 'getIssues' which likely retrieves multiple issues. It's not tautological with the name 'getIssue' but lacks specificity.

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 for 'specific' issues, or how it differs from 'getIssues' (e.g., single vs. multiple issues). Without any usage context, the agent must infer from the 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 the full burden of behavioral disclosure. The description only states the action ('get list of issues') without any behavioral traits such as whether it's read-only, requires authentication, has rate limits, returns paginated results, or what format the output takes. This leaves critical operational details 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 extremely concise ('課題一覧の取得'), which is efficient but under-specified. It's front-loaded with the core action, but the brevity comes at the cost of clarity and completeness. While not verbose, it fails to provide necessary context, making it more of an under-description than ideal conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no annotations, no output schema, and a simple input schema with no parameters, the description is incomplete. It doesn't explain what an 'issue' is in this context, what system it retrieves from, the format of the returned list, or any behavioral aspects. For a list-retrieval tool, this lacks essential 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 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't mention any parameters, which is appropriate since there are none. It correctly implies this tool takes no inputs for listing issues, so it adequately compensates for the lack of parameter 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 '課題一覧の取得' (translation: 'Get list of issues') restates the tool name 'getIssues' in different words, making it a tautology. It doesn't specify what kind of issues, from what system, or with what scope. While it indicates a retrieval action, it lacks the specificity needed to distinguish it from sibling tools like 'getIssue' (singular) or other list-retrieval 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 doesn't mention context, prerequisites, or differences from sibling tools like 'getIssue' (for single issues) or 'getProjects' (for projects). There's no indication of when this tool is appropriate or when other tools should be used instead.

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. While '取得' (get) implies a read operation, it doesn't specify whether this is paginated, filtered, sorted, or what permissions are required. No rate limits, authentication needs, or response format details are mentioned, leaving 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 phrase that directly states the tool's purpose without any wasted words. It's appropriately sized for a simple list 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 list retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what format the projects are returned in, whether there's pagination, what fields are included, or any error conditions. The context signals show this is a simple tool, but even simple tools need basic behavioral context that's missing here.

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 already fully documents the parameter situation. The description doesn't need to compensate for any parameter gaps, and it correctly implies this is a simple list operation without filtering parameters. Baseline for 0 parameters with full schema coverage is 4.

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 'プロジェクト一覧の取得' (Get project list) clearly states the verb ('取得' - get) and resource ('プロジェクト一覧' - project list), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'getSpaces' or 'getUsers', but the resource specificity is clear enough for basic understanding.

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 'getIssues' or 'getSpaces'. There's no mention of prerequisites, context, or comparison with sibling tools, leaving the agent to infer usage based on tool names 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 the full burden of behavioral disclosure. The description only states what the tool does ('get space information') without any additional context about permissions, rate limits, what 'space information' includes, or how the data is returned. For a tool with zero annotation coverage, 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 phrase ('スペース情報の取得') that directly states the tool's purpose without unnecessary words. It's appropriately sized for a no-parameter tool, though it could be more structured if it included additional context. There's no waste, but it's borderline minimal.

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 incomplete for effective use. It doesn't explain what 'space information' entails, how it's formatted, or any dependencies. For a tool with no structured data to supplement it, the description should provide more context about the return values and usage 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?

The input schema has 0 parameters with 100% coverage, meaning there are no parameters to document. The description doesn't need to add parameter semantics beyond the schema, so it meets the baseline. However, it doesn't explicitly state that no parameters are required, which could be slightly improved for clarity.

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 'スペース情報の取得' (Get space information) states a clear verb ('取得' - get) and resource ('スペース情報' - space information), which meets the basic requirement. However, it doesn't distinguish this tool from its siblings like getProjects or getUsers, which follow similar patterns for different resources. The purpose is clear but lacks 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. There are no explicit instructions on when/when-not to use it, nor any mention of prerequisites or context. Given the sibling tools include getProjects and getUsers, which might retrieve related data, the absence of usage guidelines is a significant gap.

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 ('取得' - get) without disclosing behavioral traits like pagination, sorting, filtering capabilities, authentication requirements, rate limits, or what data is returned. This leaves significant gaps for a tool that likely returns a list of users.

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 ('ユーザー一覧の取得') that directly states the purpose without any wasted words. It's appropriately sized for a simple tool with no parameters.

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 minimal but incomplete. Without annotations or output schema, it doesn't explain return values, error conditions, or usage context. For a tool that likely returns user data, more detail on behavior would be 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't mention parameters, aligning with the schema. Baseline is 4 for zero parameters, as it avoids unnecessary information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'ユーザー一覧の取得' (Get user list) clearly states the verb ('取得' - get) and resource ('ユーザー一覧' - user list), providing basic purpose. However, it doesn't differentiate from potential sibling tools like 'getIssues' or 'getProjects' beyond the resource type, making it somewhat vague 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?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'getIssues' and 'getProjects' available, there's no indication of context, prerequisites, or exclusions for selecting this user-focused tool over others.

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 only states what the tool does ('get webhook list') without any information about permissions, rate limits, pagination, or what the returned data looks like. For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient phrase ('Webhook一覧の取得') that directly conveys the core purpose with zero waste. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 0 parameters, no annotations, and no output schema, the description is minimally adequate but lacks important context. It doesn't explain what a webhook list contains, how it's formatted, or any behavioral aspects. For a simple retrieval tool, it meets the minimum viable threshold but leaves gaps in understanding the tool's full behavior.

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 documentation in the description. The baseline for this scenario is 4, as the description doesn't need to compensate for any parameter gaps, though it doesn't explicitly state 'no parameters required' which would warrant a 5.

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 'Webhook一覧の取得' (Get webhook list) clearly states the verb ('取得' - get) and resource ('Webhook一覧' - webhook list), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings, which include various other 'get' operations like getIssues, getProjects, etc., so it doesn't reach the highest 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's no mention of context, prerequisites, or comparison with sibling tools like getIssues or getProjects, leaving the agent to infer usage based on the tool name alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a retrieval operation ('取得'), implying it's likely read-only, but doesn't confirm this or describe any other behavioral traits such as authentication requirements, rate limits, pagination behavior, error conditions, or what '一覧' (list) entails structurally. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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 - a single Japanese phrase that directly states the tool's purpose. There's no wasted language or unnecessary elaboration. However, the lack of English translation or additional context might reduce effectiveness for some agents, and it could benefit from being more front-loaded with essential details if this were a more complex 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 simplicity (0 parameters, no output schema), the description is minimally complete but inadequate for full understanding. While it states what the tool does, it doesn't provide enough context about the return format (what a 'wiki page list' contains), behavioral constraints, or how it fits with sibling tools. For even a simple retrieval tool, more information about the expected output and usage context would be 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?

The tool has 0 parameters with 100% schema description coverage (empty schema). The description doesn't need to compensate for any parameter documentation gaps since there are none. It appropriately doesn't mention parameters, which aligns with the schema. The baseline for 0 parameters is 4, as the description correctly focuses on the tool's purpose rather than non-existent 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 'Wikiページ一覧の取得' (Get list of wiki pages) clearly states the verb ('取得' - get) and resource ('Wikiページ一覧' - wiki page list), making the purpose understandable. However, it doesn't distinguish this tool from potential sibling wiki tools (none exist in the provided list), and the Japanese-only text might limit clarity for non-Japanese agents. It's specific enough to understand what it does but lacks differentiation 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. There are no explicit instructions about when this tool is appropriate, what prerequisites might exist, or how it differs from other list-retrieval tools like getIssues or getProjects. The agent must infer usage from the name and description alone without any contextual hints.

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