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

No annotations exist, so description carries full burden. It only states the action without disclosing side effects, error conditions, or requirements like authentication. Minimal 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?

Description is brief with a one-line summary followed by a structured Args list. Efficient and clear, though the summary could be more descriptive.

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 3-parameter tool without output schema, the description covers parameter semantics but omits behavioral context like return values or common errors. Adequate but not complete.

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 has 0% description coverage, but the tool description's Args list explains all three parameters: issue_id (issue number), note (content, Markdown possible), and status_id (optional status change, default keep). Adds significant meaning beyond bare schema types.

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?

Description clearly states the tool adds a comment to an issue with optional status change. Verb 'add' and resource 'comment' are specific, distinguishing it from siblings like create_issue or get_issue.

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 on when to use vs alternatives, no context for when not to use or prerequisites. Only a raw parameter list.

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 only states the tool creates an issue. It does not disclose side effects, idempotency, authorization requirements, or whether duplicates are prevented. The mutation nature is implied but not elaborated.

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 with a one-line summary followed by a bullet list of parameters. Every sentence adds value, and the structure is front-loaded and easy to scan.

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?

While parameter semantics are well-covered, the description omits return value details, error conditions, and behavioral context (e.g., consequence of duplicates). Given no output schema and no annotations, more completeness would help agent decisions.

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% description coverage, but the description compensates fully by explaining each parameter's meaning, including formats (YYYY-MM-DD), markdown support, and references to list_enumerations for tracking and priority IDs.

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 starts with '새 이슈 생성' (Create new issue), clearly stating the verb and resource. It distinguishes from sibling tools like get_issue or list_issues by focusing on creation.

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 a parameter hint to use list_enumerations for tracker_id, but lacks explicit guidance on when to use this tool versus others, or any prerequisites beyond required parameters.

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?

Given no annotations, the description discloses key behavioral traits: inline rendering for images, error for non-images, and suggestion to use content_url. It lacks details on authentication or side effects, but for a download tool, this is sufficient.

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 relatively concise, with the key action in the first sentence. The usage guidance and parameter info are front-loaded. Slight redundancy in repeating '첨부파일' could be tightened, but overall well-structured.

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

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

The description covers the core functionality and edge cases (image vs non-image) without an output schema. It lacks details on error messages or return format, but the tool's behavior is sufficiently explained 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?

The description adds minimal meaning beyond the input schema: it only restates the parameter as 'attachment file ID'. With 0% schema coverage, the description should compensate but does not provide additional context or constraints.

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: downloading attachments and inline display for images. It distinguishes itself by specifying behavior for two types of attachments, which is not covered by sibling 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 explicit guidance on when to use this tool (for image attachments) and what to do for non-images (use content_url directly). However, it does not explicitly contrast with sibling tools, though no sibling handles downloads.

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 provided. Description does not disclose error handling, authentication needs, rate limits, or what happens if issue doesn't exist.

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?

Two sentences summarizing purpose and parameters. No redundant information.

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?

Covers basic function and parameters but lacks output format details and edge case handling. Acceptable for simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Description adds full explanation for both parameters beyond schema titles, including example for issue_id and default for include_comments.

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?

Description clearly states tool retrieves issue details including body, comments, and attachments. It distinguishes from siblings like list_issues and add_comment.

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 on when to use this tool versus alternatives (e.g., list_issues for summaries). Missing context about prerequisites or limitations.

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 fully carries the behavioral burden. It transparently explains the tool returns two types of tasks (incomplete assigned tasks and recently updated tasks) without side effects, though it omits details like rate limits or data freshness guarantees.

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 with a clear main sentence and bullet-pointed details. No unnecessary words; each sentence adds value.

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 parameters and no output schema, the description sufficiently explains the tool's purpose and output. It could detail the output format further, but overall it is complete for an agent to understand 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 zero parameters (100% coverage), so the description adds value by describing the output structure (two sub-sections). This clarifies what the tool returns, going beyond the empty 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 clearly states the tool retrieves today's tasks at once ('오늘 봐야 할 일감 한 번에 조회') and lists two specific sections: my_open_issues and recently_updated. This distinguishes it from sibling tools that focus on single issues or general lists.

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 mentions it is structured for morning alert scripts, implying usage for daily overviews. However, it does not explicitly state when not to use it or compare alternatives, leaving usage guidance implied.

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 provided, so the description must disclose behavioral traits. It only says '조회' (retrieve), implying read-only, but does not state what happens if the page does not exist, whether permissions are needed, or if the content is returned as raw text or structured data.

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?

Description is short and front-loaded with the main action. The Args block is structured clearly. However, it could be more concise by omitting the redundant parameter listing that duplicates the schema.

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?

No output schema exists, so the description should at least hint at what is returned (e.g., page content in markdown). It lacks this, making it incomplete for an agent to know what to expect. Error cases are also not covered.

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 coverage is 0%, so the description must compensate. It provides brief labels: '프로젝트 식별자' (project identifier) and '페이지 제목' (page title), which add minimal context over the schema's 'Project Id' and 'Page Name'. No formatting, sources, or examples are given, leaving ambiguity.

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?

Description states '위키 페이지 내용 조회' (Retrieve wiki page content), clearly indicating a read operation on a specific resource. While it distinguishes from sibling tools like 'list_wiki_pages' (list) and 'update_wiki' (update), it does not specify the exact scope of content returned.

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 on when to use this tool vs alternatives. It does not mention prerequisites, such as needing a project_id from another source, or when to use 'list_wiki_pages' first to find a page_name.

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 discloses that the tool returns IDs for three enumeration categories. For a simple read-only listing tool, this is adequate; no destructive actions or side effects are implied.

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, using a single sentence and bullet points. Every word adds value, and the structure is clear and scannable.

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 tool with no parameters and no output schema, the description provides all necessary context: what the tool returns and why it is used. It is complete for its complexity level.

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 zero parameters, so baseline is 4. The description adds meaning by listing the enumeration categories, which goes beyond the empty 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 clearly states it provides ID lists needed for issue creation/filtering, specifying three types (trackers, statuses, priorities). This is distinct from sibling tools like list_issues or create_issue, which operate on actual issues.

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 implicitly tells when to use this tool (when needing IDs for issue creation/filtering), but does not explicitly exclude scenarios or mention alternatives. However, the context is clear enough for an agent.

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 the burden. It discloses parameter behaviors (defaults, allowed values) but lacks details on pagination, return format, or edge cases like empty results. It adequately explains input but not output 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 concise: a one-line purpose followed by a structured Args block with one line per parameter. No extraneous text, every sentence serves a purpose. Front-loaded with 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?

Input parameters are well explained, but the description lacks details about the output (e.g., what fields are returned, structure of issue objects). Given no output schema, this gap reduces completeness. Error handling or ordering behavior beyond sort is also missing.

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 fully compensates by explaining all 7 parameters with context such as defaults, allowed values (e.g., status: 'open','closed','*'), and format (e.g., sort: 'updated_on:desc'). This adds significant 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 clearly states the tool's purpose as '일감 목록 조회' (List issues), which is a specific verb+resource combination. It distinguishes itself from siblings like get_issue (single issue) and create_issue by focusing on listing multiple issues.

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 explains parameters for filtering but does not explicitly state when to use this tool versus alternatives like get_issue or list_projects. No usage guidance or exclusions are provided.

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 must disclose behavioral traits. It only states the tool lists projects without mentioning pagination, authentication, rate limits, or any side effects. This is minimal and 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 sentence with no wasted words. It is concise and front-loaded, though it could be expanded slightly with behavioral details without losing 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?

The tool is simple with no parameters and an output schema exists (not shown). The description covers the basic purpose and fields returned. It is adequately complete for a straightforward list operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters, so schema description coverage is trivially 100%. The description adds no parameter information, but none is needed. Baseline score of 4 for no 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 tool retrieves a list of Redmine projects with specific fields (identifier, name, description). It is a specific verb+resource combination, but does not differentiate from sibling tools that target other resources, which is acceptable.

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 explicit guidance on when to use this tool versus alternatives is provided. However, the simple purpose of listing projects makes usage straightforward and implied.

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 must disclose behavioral traits. It only states the basic action without mentioning read-only nature, pagination, error handling, or any side effects. The output schema exists but behavior like listing all pages versus paginated is not specified.

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 short, with one sentence followed by an Args list. It is concise and avoids unnecessary words. However, it could be structured more efficiently by including the parameter description inline without the separate Args block.

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?

Despite the tool being simple with one parameter and having an output schema, the description lacks critical context such as usage guidelines, behavioral traits, and sufficient parameter semantics. An agent would need additional assumptions 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 coverage is 0%, so description should compensate. The description of 'project_id' as '프로젝트 식별자' merely repeats the schema's 'Project Id' in Korean, adding no further meaning about format, source, or constraints. It is almost a tautology.

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 '프로젝트의 위키 페이지 목록' which clearly indicates listing wiki pages of a project. The verb 'list' and resource 'wiki pages' are specific. While it does not explicitly differentiate from siblings like 'get_wiki' or 'update_wiki', the action is distinct enough.

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 on when to use this tool versus alternatives such as 'get_wiki' or 'list_issues'. There are no prerequisites, context, or exclusion criteria mentioned. The description is purely factual without usage 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?

Description explains upsert behavior (create if not exists, update if exists). No annotations provided, but the description conveys key behavioral traits clearly.

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?

Very concise: two lines for purpose, then structured argument list. No wasted words, front-loaded with main action.

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?

Covers all 5 parameters meaningfully. Missing return information but no output schema exists. Adequate for typical 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?

0% schema description coverage, but description adds meaningful explanations for each parameter, e.g., 'text: 본문 (Textile 또는 Markdown)' and 'parent_title: 상위 페이지 제목 (계층 구조)'. Adds value beyond schema titles.

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?

Description clearly states 'create/update wiki page (create if not exists, update if exists)' with specific verb and resource. Distinguishes from siblings like 'get_wiki' and 'list_wiki_pages'.

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 explicit guidance on when to use vs alternatives, but the purpose is self-explanatory given siblings. Adequate but lacks explicit context.

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