BugEzy

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

With no annotations, the description must carry the full behavioral burden. It does add the useful filter that only warn/error logs are returned, but it fails to state read-only behavior, return format, pagination, or ordering. This is a significant disclosure 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 short, but the second English phrase 'Console logs.' is redundant and does not earn its place. The first clause is concise and clear, but the redundancy hurts overall 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?

For a tool with no output schema and no annotations, the description is too minimal. It does not describe what the returned logs look like, whether it returns an array, how errors are handled, or the role of report_id. The context is insufficient for reliable 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 coverage is 0% and the description does not explain the report_id parameter. The parameter name is somewhat self-explanatory, but the description adds no additional meaning, leaving the agent to infer that report_id identifies the report whose console logs should be fetched.

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 identifies the tool's verb (取得/get) and resource (Console logs), and further qualifies the scope as warn/error logs. This distinguishes it from sibling tools like get_terminal_logs and get_network_errors.

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 gives no guidance on when to use this tool instead of the many sibling tools. It only restates the function in Chinese and English without mentioning alternatives or exclusions.

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?

The description discloses that authentication via user_email and session_token is required and that it targets the current page. However, with no annotations, it does not mention whether the operation is read-only, the response format, or error handling behavior, leaving gaps for a potentially risky 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 short and front-loaded, but it duplicates the same information in Chinese and English, making it slightly redundant. It contains no fluff and earns its place, though the bilingual repetition could be streamlined.

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 two parameters and no output schema, the description covers the core purpose and auth requirement. However, it does not describe the output format or how console and network errors are combined, which could be relevant for an agent invoking the 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?

Schema descriptions already cover both parameters with clear details, including the optionality of session_token when a token is present in the MCP URL. The tool description merely restates 'requires user_email and session_token' without adding new semantic value beyond the 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 'Live console/network errors' and specifies 'current page' and scope, making the action and resource evident. However, it does not explicitly differentiate from sibling tools like get_console_logs or get_network_errors, which could overlap.

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 about when to use this tool versus the separate console or network error tools. The description only states what it does, not the appropriate context or alternatives, leaving the agent to infer usage.

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 is the only source of behavioral information, but it only states the core function of retrieving 4xx/5xx errors. It does not disclose read-only status, report scoping, or output format, leaving significant behavioral ambiguity.

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 but contains redundancy: the second sentence 'Network errors.' repeats the first in English. This minor waste prevents a higher score, though it remains easily digestible.

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 does not provide enough context for the tool's invocation. It omits the role of report_id and expected return data, making the description only minimally 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?

The input schema has one required parameter, report_id, with no description coverage. The tool description does not explain what report_id refers to or how it should be used, so the agent has no parameter semantics beyond the schema type.

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 network errors, and specifies HTTP status codes 4xx/5xx, making the purpose explicit. The resource is distinct from siblings like get_console_logs, though it does not explicitly differentiate itself.

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 get_live_errors or get_console_logs. No exclusions, prerequisites, or preferred contexts 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, the description carries the behavioral disclosure burden. The verb '取得/get' implies a read-only operation, and the listed fields describe what will be returned. However, it does not mention error behavior, whether the report_id refers to a specific report, or any response format details, leaving some ambiguity.

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 and front-loaded with the core meaning, which is good. The bilingual repetition ('Page info' duplicating '取得頁面資訊') is slightly redundant, but it does not harm clarity and keeps the description compact.

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 one parameter and no output schema, the description covers the purpose and key fields, but it lacks context about how report_id links to the report and what the agent should expect in terms of response format or potential failures. This is adequate but not fully 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?

The input schema has one required parameter (report_id) with 0% schema description coverage, and the tool description does not explain the meaning or purpose of report_id beyond its name. The description lists output fields but not how the parameter maps to the returned page info, so the agent gets minimal parameter guidance.

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

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

The description clearly states the tool's purpose with a specific verb ('取得/get') and resource ('頁面資訊/page info'), and explicitly enumerates the included fields (URL, title, browser, resolution). This distinguishes it from sibling tools like get_console_logs or get_timeline, which target different data types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives such as get_report_overview or get_rrweb_events. There are no exclusions, prerequisites, or context hints about how page info fits into a debugging 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?

With no annotations provided, the description carries the full burden. It discloses the content and explicitly states that raw data is excluded, setting expectations. It does not mention error behavior or performance, but for a simple read-only tool this is adequate.

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 two short sentences in different languages that reinforce the same message. It is front-loaded with the core purpose and contains no wasted words.

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 one parameter, no output schema, and no annotations, the description is sufficiently complete. It lists the included components (metadata, counts, AI bug summary) and excludes raw data. It could mention output format or error handling, but that is not critical for such a focused overview tool.

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

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

The description does not explain the report_id parameter, and schema description coverage is 0%. However, the parameter name is self-explanatory and the tool requires only one. The description does not add semantic value beyond the schema, but the low parameter complexity limits the impact.

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 report overview containing metadata, counts, and an AI bug summary, and explicitly excludes raw data. This specificity distinguishes it from sibling tools like get_console_logs or get_rrweb_events, which focus on raw 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?

The description provides clear context on what the tool returns (an overview, not raw data) and implicitly signals that it is appropriate for high-level report summaries. However, it does not explicitly name alternatives or state when not to use it, so it lacks strong exclusionary guidance.

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 must carry the full burden, and it does disclose a key behavioral trait: the data volume is large (⚠ 資料量大). However, it does not describe the return format, pagination behavior, or any performance implications beyond the warning, leaving notable 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 extremely concise, using two short phrases to state the purpose and the warning. It is front-loaded with the core action and the most important caveat, and every word contributes useful information without 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?

For a single-parameter tool, the description gives the essential purpose and a data volume warning, but with no output schema or annotations, it should say more about what the returned events look like and how this tool relates to get_rrweb_summary. The description is minimally adequate but leaves gaps around return structure and selection criteria.

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 only report_id with no description, and the description provides no parameter-level detail. The schema coverage is 0%, so the description should compensate, but it does not mention the required report_id or explain how it relates to fetching the events. The parameter name is self-explanatory, but the description adds no semantic value.

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 '完整 DOM 事件' (complete DOM events) and explicitly says 'Full rrweb events,' identifying the resource and scope. The word 'Full' also distinguishes it from the sibling tool get_rrweb_summary, implying this is the raw, complete event data rather than a summary.

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 is given for when to use this tool versus alternatives. The only hint is the data volume warning, which suggests caution but does not state when to prefer get_rrweb_summary or other tools. There are no explicit 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?

With no annotations, the description carries the full burden. It explicitly states the tool produces a summary and does not return complete data, which is a key behavioral trait. It also specifies the content of the summary (count/duration/type distribution). However, it does not mention auth, rate limits, or response format, but for a simple read tool this is acceptable.

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 with parenthetical clarifications. It front-loads the purpose and adds the key 'no full data' exclusion. The English 'rrweb summary' is somewhat redundant but does not detract.

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 only one parameter and no output schema, the description provides the essential information: what it returns (event count/duration/type distribution) and what it excludes (complete data). It does not describe the report_id parameter, but that is covered under parameter semantics. The description is sufficiently complete for an agent to know when to invoke it and what to expect.

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 does not mention the single required parameter report_id. The description adds no meaning about what report_id is, its format, or how it affects the result. The parameter name is self-explanatory, but the description fails to compensate for the lack of schema 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 tool provides a summary of DOM trajectories (rrweb data), specifically listing what the summary includes (event count, duration, type distribution). It also explicitly says it does not return complete data, which distinguishes it from the sibling tool get_rrweb_events.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this tool is for obtaining aggregated summary metrics rather than full rrweb event data, giving clear context for when to use it. However, it does not explicitly name alternative tools or state when-not-to-use conditions, so it falls short of a 5.

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?

Discloses the significant token cost of images (~3,000-8,000 per image), which is critical behavioral info in the absence of annotations. It also notes high-quality AI analysis, giving agents a sense of processing overhead.

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 concise Chinese sentences plus a short English title. The core purpose is front-loaded, and the token warning is efficiently integrated. No redundant wording.

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 output schema, and the description covers purpose and token cost. However, it does not explain the metadata-returning behavior when include_images is false, which is only partially covered by the schema.

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 50% (include_images has a description, report_id does not). The description indirectly adds context about token usage relevant to include_images, but it does not clarify report_id or directly explain parameter behavior.

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 '取得報告截圖圖片（視覺 Bug 用）' (get report screenshot images for visual bugs), providing a specific verb, resource, and use case. It is distinct from sibling tools like get_console_logs and get_network_errors.

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?

Explicitly recommends use for visual bugs and advises using only when needing to see the screen ('建議只在需要看畫面時使用'). It provides clear context and an implied exclusion, though it does not name alternative 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 present, so the description carries the full burden. It discloses authentication requirements (user_email + session_token), that it is a paid feature, and that it provides real-time logs. However, it does not explicitly state read-only behavior, data retention, or error response details. The parameter description in the schema mentions '只讀你自己的終端機日誌' (read only your own logs), but that is not reinforced in the main description, which says '取得某使用者' (get a user's) - a slight ambiguity.

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 compact and front-loaded with the primary purpose. It repeats information in Chinese and English, which is somewhat redundant, but each sentence earns its place (purpose, auth/paid, setup command). No excessive fluff, but the English summary could be removed for better 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 (2 params, no output schema) and well-documented parameters, the description covers the essential context: what it does, auth and paid requirements, and the necessary developer setup command. It lacks a description of the return format or pagination behavior, but for a log retrieval tool with a well-known domain, this is acceptable. The mention of 'stderr/throw/crash' adds useful scope information.

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 100% with both parameters having detailed descriptions, so the baseline is 3. The tool description does not add new parameter-level meaning; it repeats the auth requirement and mentions the npx setup command indirectly. It also says 'requires user_email and session_token' while the schema marks session_token as optional (only user_email is required), creating minor ambiguity. Thus no value beyond the 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 function: '取得某使用者終端機的即時錯誤日誌' (get a user's terminal real-time error logs), specifying stderr/throw/crash. This distinguishes it from siblings like get_console_logs or get_network_errors, as it is specifically for terminal error logs. The verb and resource are 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 concrete prerequisites: requires user_email and session_token, is a paid feature, and developers must run 'npx bugezy-watch -- <command>' to set up log capture. It does not explicitly compare to sibling tools, but the specificity of 'terminal error logs' implies when to use it. This is clear practical guidance, but lacks explicit alternative/exclusion statements.

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 discloses that the tool combines and chronologically sorts multiple data types, which is a valuable behavioral trait. However, it does not mention whether it's read-only, how it handles missing reports, or the exact output structure, leaving some transparency 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 front-loaded with the core purpose but includes a redundant final sentence 'Full report timeline' that repeats the preceding Chinese text, adding no new information. It could be trimmed without loss of meaning.

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 an aggregate tool with no output schema, the description explains what data sources are included and that the result is a complete chronological storyline. It could be more specific about the return format, but the description gives enough context for an AI to understand the tool's role and scope.

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% for the single parameter (report_id), and the schema already provides a clear description. The tool description does not add further parameter meaning, so the baseline of 3 is appropriate.

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 a specific verb and resource: '取得一份報告的完整時間軸' (get a report's complete timeline). It also clearly differentiates from sibling tools by listing the included data types (Console, Network, voice, markers, network environment, storage) and explicitly noting it avoids calling individual 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 explicitly recommends using this tool to grasp the complete bug context and explicitly names the alternative approach of calling console/network/voice tools individually. However, it lacks an explicit 'when not to use' statement, so it's not a full 5.

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

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

No annotations are provided, and the description only states what the tool returns (monthly stats). It does not disclose additional behavioral traits such as authentication requirements, read-only status, or potential latency, but for a simple stats retrieval, the basic return value is communicated.

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 two sentences—one Chinese, one English—and contains no fluff. The key information is front-loaded, making it easy to skim.

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 no-parameter, no-output-schema tool, the description sufficiently covers the tool's purpose and the data it provides. It could mention whether historical data is available, but given there are no parameters, the scope is clear.

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, and the schema is empty. The description accordingly adds no parameter-specific meaning, which is acceptable; the return criteria (current month) are conveyed 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 it retrieves MCP usage statistics for the current month, including call count, token consumption, and savings. The verb 'get' plus resource 'usage stats' is specific and distinguishes it from sibling logging/error 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?

No explicit when-to-use or alternative guidance is provided, but the tool's unique focus on usage stats makes its purpose self-evident. There are no exclusions or alternatives mentioned, so it relies on implicit 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 only states the resource ('Developer voice transcript') and the action ('get'), but does not disclose read-only nature, potential side effects, authentication, error behavior, or return format. This is a minimal label rather than behavioral 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 short and front-loaded, but contains redundant bilingual repetition ('取得開發者語音描述' and 'Developer voice transcript' convey the same meaning). It is concise but not optimally structured; one language would suffice.

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 one-parameter getter with no output schema, the description provides the basic purpose but omits details like return value format, error handling, and what 'voice transcript' entails. Given the lack of annotations, the description is under-specified, though the tool's simplicity mitigates the gap somewhat.

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 fails to mention the parameter 'report_id' or any details about it. While the parameter name and type are self-explanatory, the description adds no value; the agent gets no additional context about the parameter's semantics or format.

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 indicates the tool retrieves a developer voice transcript (中文轉錄), which is a specific resource distinct from sibling tools like console logs or network errors. The verb '取得/get' and the noun phrase 'voice transcript' define the purpose unambiguously.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when needing the developer's voice transcript, but provides no explicit guidance on when to prefer this over alternatives or any exclusion criteria. There is no mention of alternatives or context, so the usage guidance is merely 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?

With no annotations provided, the description carries the full burden. It discloses the authentication requirement and implies user-specific filtering. However, it does not mention read-only behavior, error handling, or return format. The user_email schema description adds a security default, but that's outside the main description.

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, front-loaded sentence that states the purpose and authentication requirement without filler. The bilingual repetition (Chinese and English) is slightly redundant but serves a multilingual audience and is not excessive.

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?

This is a simple list tool but has 4 parameters, no annotations, and no output schema. The description covers only purpose and authentication, leaving url and limit unexplained and failing to describe return values or pagination behavior. It is insufficient for a 4-parameter tool with no structured support.

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 50% (user_email and session_token have descriptions, but url and limit do not). The main description repeats the requirement for user_email and session_token but adds no new meaning, and it fails to compensate for the undocumented url and limit 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's function: 'List a user's bug reports' with a specific verb and resource. It also specifies the authentication requirement. However, it does not explicitly differentiate from sibling tools like get_report_overview, though 'bug reports' is distinct from the log-related siblings.

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 notes that user_email and session_token are required for identity verification, which is a clear precondition. However, it provides no guidance on when to use this tool over alternatives (e.g., get_report_overview) and lacks any exclusions or 'when not to use' statements.

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