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

No annotations provided, so description carries full burden. It discloses JS rendering but lacks details on side effects, duration, or resource creation beyond 'launches.'

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?

Single sentence, efficient and front-loaded. Could benefit from slight expansion but is appropriately concise.

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?

With a complex nested settings object and no output schema, the description is minimal. It covers core differentiator but leaves out guidance on settings and return values.

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 descriptions for all parameters; description adds no extra meaning 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?

Description clearly states 'launches an advanced website audit that renders JavaScript' and specifies suitability for SPAs or dynamic content, distinguishing it from standard audit 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?

Explicitly mentions when to use (SPAs/dynamic content requiring JS rendering), implying when not to use (e.g., when standard audit suffices). Does not explicitly name alternatives but context is clear.

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 description carries full burden. It only says 'crawls HTML', lacking details on destructive nature, rate limits, authentication, or what happens to the environment. The name 'create' suggests mutation, but no confirmation.

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?

Single sentence, clear and to the point. The prefix 'Data Tool:' is unnecessary but not harmful. It could be slightly more informative 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?

Given the complexity of 3 parameters and a nested settings object with many fields, and no output schema, the description is too minimal. It does not cover what the audit report looks like, required steps, or expected outcomes.

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%, so baseline is 3. The description adds no extra meaning to parameters beyond the schema. It does not explain how settings affect the audit, which could be valuable for a nested object with many fields.

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 launches a standard website audit that crawls HTML. It distinguishes from the sibling 'DATA_createAdvancedAudit' by noting suitability for static and server-side rendered sites, implying the advanced version is for dynamic sites.

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 guidance on when to use this tool ('Suitable for most static and server-side rendered sites'), implying not for dynamic sites. It does not explicitly mention alternatives but the sibling name creates context. A clearer when-not-to-use would improve.

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?

Despite no annotations, the description discloses critical behavioral traits: the action is permanent ('permanently deletes') and affects all associated data. This gives the agent a clear understanding of the tool's destructiveness. A score of 4 is warranted as it almost fully compensates for the lack of annotations.

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

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

The description is a single, concise sentence that immediately conveys the tool's purpose. It is front-loaded with 'Data Tool' for categorization and wastes no words, making it optimally sized for an AI agent.

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 delete tool with one parameter and no output schema, the description adequately explains the action and its scope. It could mention the need to call listAudits first or confirm the audit_id, but the given information is sufficient for a basic understanding.

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

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

The input schema covers 100% of the single parameter with a clear description. The tool description adds no additional parameter information, which is acceptable given the high schema coverage, earning a baseline score of 3.

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

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

The description clearly states the verb 'deletes' and the resource 'website audit report and all of its associated data', making the purpose unambiguous. It distinguishes itself from sibling tools, many of which are get/export operations or other delete actions on different entities.

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 vs alternatives, no prerequisites (like listing audits to get the audit_id), and no note about irreversibility. Users are left to infer usage context on their own.

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 notes async behavior and task ID, but lacks details on rate limits, data volume limits, or how to use the task ID (e.g., referencing DATA_getBacklinksExportStatus). No annotations exist, so the description carries full burden.

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?

Single sentence with 14 words, front-loaded purpose, zero redundancy.

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

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

Missing critical context for an async tool: no mention of status-checking endpoint (DATA_getBacklinksExportStatus) or how to handle the task ID. Incomplete for its complexity.

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% (only 'target' described). The description adds no parameter information beyond the schema. Enum values for 'mode' are not explained, and 'target' remains vague. Compensation is insufficient.

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 large-scale backlinks asynchronously and returns a task ID. This specifies the verb and resource, distinguishing it from synchronous siblings, but lacks explicit 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?

No guidance on when to use this tool versus alternative backlink tools (e.g., DATA_getAllBacklinks). The description does not mention prerequisites or typical scenarios.

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

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

With no annotations, the description bears full responsibility for disclosing behavioral traits. It only states 'Retrieves metrics' but does not clarify if it is read-only, whether it modifies data, or any other side effects. There is no mention of rate limits, cost, or idempotency.

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 which is concise but omits potentially useful context. It could be more structured, e.g., with a brief note on what metrics are included or how to use the 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?

For a tool with 5 parameters and no output schema, the description lacks completeness. It does not describe the return format, pagination, or error conditions. The schema covers parameter details, but the description fails to synthesize a complete picture for the agent.

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

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

Schema coverage is 100%, so the description adds minimal value beyond the schema. While the description labels it as 'metrics for a bulk list of keywords,' it does not elaborate on parameter meanings or provide examples. Baseline 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 clearly states it retrieves metrics for a bulk list of keywords. The title 'Export Keywords Metrics' aligns well. However, it could better differentiate from sibling tools like DATA_getDomainKeywords which retrieves keywords for a domain rather than metrics on a provided list.

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 such as DATA_getDomainKeywords or DATA_getRelatedKeywords. The description does not mention prerequisites or contexts where this tool is appropriate.

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

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

With no annotations provided, the description must convey behavioral traits. It implies a read-only operation by saying 'Identifies and returns,' which is appropriate. However, it does not explicitly state that no changes are made, nor does it disclose potential dependencies or limits, leaving some uncertainty.

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 only two sentences, front-loading the core action and resource. Every word contributes meaning without redundancy, making it highly concise and well-structured.

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

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

Given the tool's simplicity and full schema coverage, the description is mostly adequate. However, it does not specify the output format (e.g., returns a string), which is a minor gap. It mentions usefulness for AI search queries, which helps contextual completeness.

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

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

The input schema covers all three parameters with descriptions, resulting in high schema coverage. The description adds no additional parameter details beyond what the schema provides, so it meets the baseline but does not enhance understanding.

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

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

The description clearly states the tool's purpose: 'Identifies and returns the brand name associated with a given target domain, subdomain, or URL.' It uses a specific verb ('Identifies and returns') and resource ('brand name'). However, it does not explicitly differentiate from sibling tools like DATA_getAiPromptsByBrand, though the distinction is implicit.

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 the tool is 'Useful for determining what brand name to use in other AI search queries,' providing a context for use. However, it lacks explicit guidance on when not to use it or mention of alternatives, such as directly using domain knowledge or other 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?

With no annotations provided, the description carries full burden for behavioral transparency. It only states it retrieves data, but omits any details about rate limits, authentication requirements, error handling, or whether it is a read-only 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 concise with two sentences, no redundant information, and front-loads the core purpose effectively.

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 lacks details about the return value format, making it somewhat incomplete given no output schema. It does not cover potential errors or limits, which may be important for an agent.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds some value by explaining the aggregated vs engine-specific behavior for the engine parameter, but does not enhance meaning for other parameters 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 verb 'retrieves' and the resource 'a high-level overview of a domain's performance in AI search engines'. It distinguishes between aggregated and engine-specific data, setting it apart from related tools like DATA_getAiOverviewLeaderboard.

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 when to use the tool: returns aggregated data if engine is omitted, or engine-specific data if provided. However, it does not explicitly state when not to use it or mention alternatives among the many sibling tools.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states that it 'Returns brand presence, link presence, share of voice rankings, and leaderboard' but does not disclose potential side effects, authorization requirements, rate limits, or whether it is read-only. Given the absence of annotations, more behavioral detail is needed.

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 consists of two concise sentences that front-load the tool's primary function and outputs. Every sentence adds value, with no redundancy or filler.

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

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

Given the tool's complexity (5 parameters with nested objects, no output schema, and a unique AI focus among siblings), the description adequately covers what the tool does and the kind of data it returns. It does not include return format details, but the absence of an output schema means the agent must rely on the description. The description could be slightly more complete regarding the exact data structure.

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%, meaning the input schema already provides detailed descriptions for all 5 parameters. The description does not add significant value beyond the schema for parameters; it merely rephrases the purpose. Hence a baseline score 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 clearly states the tool's purpose: 'Compare multiple domains/brands in AI search engines'. It specifies the resources (ChatGPT, Perplexity, Gemini, AI Overview, AI Mode) and the outputs (brand presence, link presence, share of voice rankings, leaderboard). This distinguishes it from sibling tools that focus on audits, backlinks, or keywords.

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 states the usage context: 'Use this for AI search comparison, competitor analysis, and visibility benchmarking.' This helps the agent determine when to invoke this tool. However, it does not mention when not to use it or suggest 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?

With no annotations provided, the description must fully disclose behavioral traits. It only states retrieval, but fails to mention pagination behavior, rate limits, authentication needs, or data source characteristics. This is insufficient for a tool with 15 parameters and high complexity.

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

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

The description is a single, clear sentence without unnecessary words. It is appropriately sized but could be slightly improved with additional context without becoming verbose.

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 15 parameters, no output schema, and no annotations, the description is too minimal. It does not explain typical use cases, how filters interact, or what the response structure looks like. The complex filter parameters (e.g., filter_multi_keyword_included) lack any contextual guidance in the description.

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

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

The input schema has 100% description coverage, so each parameter is already explained. The tool description does not add any additional meaning beyond what the schema provides. Baseline is 3 since schema covers parameters well.

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 prompts where a specified brand is mentioned in AI search results. It uses a specific verb ('Retrieves') and resource ('list of prompts'), and the brand parameter distinguishes it from the sibling DATA_getAiPromptsByTarget.

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

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

No guidance is provided on when to use this tool versus alternatives, such as DATA_getAiPromptsByTarget. The description does not specify prerequisites, data freshness, or when not to use it. Usage is only implied by the purpose.

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 carries full burden. It states the tool retrieves data (implying read-only) but does not disclose any behavioral traits such as authentication requirements, rate limits, or what happens if the target is not found.

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 of 18 words, efficiently conveying the core purpose with no extraneous information. It is front-loaded and well-structured.

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

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

Despite the tool having 16 parameters, no output schema, and complex filtering/sorting features, the description provides minimal context. It does not mention pagination, volume, filtering capabilities, or the nature of the returned data, leaving the agent dependent solely on 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 100%, and the schema already provides detailed descriptions for all 16 parameters. The description adds no extra meaning beyond the schema, meeting the baseline for high coverage.

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

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

The description clearly states the action ('Retrieves a list of prompts') and the resource ('that mention the specified target in AI search results'). It distinguishes from the sibling 'DATA_getAiPromptsByBrand' by using 'target' instead of 'brand', though it could explicitly call out the difference.

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 like 'DATA_getAiPromptsByBrand' or 'DATA_getAiOverview'. No mention of prerequisites or context for the tool.

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 carries full burden. It does not disclose any behavioral traits such as read-only nature, rate limits, or pagination behavior. The phrase 'comprehensive list' is vague and does not clarify if all backlinks are returned or limited (though limit parameter is present).

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

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

The description is very concise at one sentence (16 words). However, it starts with 'Data Tool:' which is redundant and wastes space. It is front-loaded with the core action, but could be slightly more efficient without the prefix.

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 17 parameters and many siblings, the description is too terse. It does not explain the return value format (though output param handles it), typical use cases, or how to effectively leverage the filters. For such complex tools, more context is needed for an AI agent to use it correctly.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond stating 'extensive filtering and sorting options,' which is generic. The individual parameter descriptions in the schema are detailed, so the description provides negligible additional 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?

Description clearly states the tool retrieves a comprehensive list of backlinks with filtering/sorting. The verb 'retrieves' and resource 'backlinks' are specific. However, it does not explicitly distinguish from siblings like DATA_getBacklinksRaw or DATA_getBacklinksCount, which might return similar data, so it misses full 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?

No guidance on when to use this tool vs alternatives. There is no mention of prerequisites, when not to use it, or what scenarios are best suited for this tool. For instance, if a user only needs backlinks count, a sibling tool might be more efficient.

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 describes a read operation ('retrieves') but does not explicitly state it is read-only, nor does it mention any behavioral traits such as authentication needs, rate limits, or potential side effects. The description is insufficient for an AI agent to understand the tool's safety profile.

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 has two sentences but includes the redundant prefix 'Data Tool:' which adds no value since the tool name already indicates it is a data tool. It is not overly verbose but could be more concise.

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 lacks an output schema and does not explain what 'full context' entails. For a tool with two parameters and many siblings, it leaves the agent uncertain about the return value and scope. More detail is needed for completeness.

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

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

Schema description coverage is 100%, with both parameters ('date' and 'audit_id') clearly described in the schema. The description adds no additional meaning beyond what the schema provides, so it meets the baseline expectation.

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 historical snapshot of an audit run, specifying the verb 'retrieves' and the resource 'historical snapshot of a specific audit run'. This distinguishes it from sibling tools like DATA_listAudits which lists audits, and other audit-related 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 does not provide any guidance on when to use this tool versus alternatives, nor does it mention when not to use it. It lacks explicit context for selection among many sibling tools that deal with audits and data retrieval.

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 must disclose behavioral traits. It mentions pagination but lacks information on read-only nature, authorization requirements, rate limits, or data freshness. The description is minimal.

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

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

The description is a single concise sentence, though it includes an unnecessary 'Data Tool:' prefix. It conveys the main purpose efficiently.

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

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

No output schema is provided, and the description does not clarify the return format beyond 'list of URLs'. With siblings covering many similar tools, more detail about pagination and expected response would help.

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%, so the baseline is 3. The description adds no extra meaning beyond the schema, which already describes each parameter adequately.

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

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

The description clearly states the tool retrieves a paginated list of URLs affected by a specific issue within an audit. It uses a specific verb and resource, and differentiates from sibling DATA_getIssuesByUrl which does the opposite. However, the 'Data Tool:' prefix is redundant.

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

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

No guidance is provided on when to use this tool versus alternatives like DATA_getIssuesByUrl or other audit tools. The description only states what the tool does without 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?

No annotations are provided, so the description carries full burden. It discloses the report contents but does not mention prerequisites (audit must be completed), side effects (none, read-only), or authorization needs. The agent cannot infer that this is a non-destructive read operation beyond the 'get' naming convention.

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 concise sentences, front-loading the purpose and immediately listing what the report includes. No redundant or vague language.

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 retrieval with one parameter and no output schema, the description is fairly complete. However, it lacks error handling guidance (e.g., invalid audit_id) and does not differentiate from other audit-related get tools despite the sibling list. Adequate but with room for improvement.

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% for the single required parameter audit_id. The description adds context that the audit must be completed, which is not in the schema description. This adds minor value, meeting the baseline of 3.

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 the full, detailed report for a completed website audit, listing included contents (health score, domain properties, broken down checks). This specific verb-resource combination distinguishes it from siblings like DATA_getAuditStatus or DATA_listAudits.

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 the tool should be used after an audit is completed, but does not explicitly state when to use this versus alternatives like getAuditStatus or getAuditHistory. With many audit-related siblings, guidance on when to use this tool is minimal.

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 describes the behavior (checking status) and real-time nature, but does not explicitly state that it is read-only or mention any permissions or side effects. It is adequate but not thorough.

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

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

The description is a single concise sentence that front-loads the tool type ('Data Tool') and purpose. It contains 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?

Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is complete. It explains the purpose, the input, and the expected output states without needing additional details.

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

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

Schema description coverage is 100% for the single parameter 'audit_id'. The description adds minimal extra meaning beyond the schema's 'Unique identifier of the audit to check.' The phrase 'specific website audit' is implied by the schema. Baseline score 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 clearly states the tool checks the real-time status of a website audit, specifying possible states (queued, processing, finished). This distinguishes it from sibling tools like create, delete, or analytical 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 does not mention when not to use it or suggest related tools for different purposes.

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. It labels the tool as 'Data Tool' but does not disclose behavioral traits such as read-only status, authentication requirements, rate limits, or any side effects. The description is insufficient for an agent to understand operational constraints.

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 of 17 words, concise and front-loaded with the core action. However, it lacks any structural formatting (e.g., bullet points) and does not emphasize key 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?

With 5 parameters, high schema coverage, no output schema, and no annotations, the description provides adequate but incomplete context. It omits information about output format (though schema defines 'output'), pagination limits, and potential errors. The lack of return value description is a gap.

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

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

Schema description coverage is 100%, so each parameter is already documented. The tool description restates 'sorting and limit options' but adds no new meaning beyond the schema. Baseline score 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 clearly states the tool retrieves anchor texts for backlinks to a specified target, with sorting and limit options. This is a specific verb-resource combination ('retrieves anchor texts') that distinguishes it from sibling tools like getAllBacklinks which return full backlinks 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 implies use when anchor text data is needed, but does not provide explicit guidance on when to prefer this over similar tools (e.g., getBacklinksRaw, getAllBacklinks). No exclusions or alternative tool recommendations are given.

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

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

No annotations exist, so the description carries full responsibility for behavioral disclosure. It only states 'Fetch authority metrics' without specifying which metrics are returned (e.g., domain authority score, page authority score, etc.), nor does it explain authentication, rate limits, or response structure. The absence of an output schema worsens the gap.

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

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

The description is a single, front-loaded sentence with no filler. However, it could be more informative without sacrificing conciseness, e.g., by noting what authority metrics include. Still, it avoids redundancy and earns its place.

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

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

Given the lack of output schema and the large set of sibling tools, the description fails to fully equip the agent. It does not explain return values, contrast with similar tools (getDomainAuthority, getPageAuthority), or provide usage examples, leaving the agent underinformed for correct 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 100%, so the description adds no new meaning beyond the schema descriptions. The parameter descriptions in the schema are adequate ('Target to assess authority...', 'Response format. Default: json.'). At baseline 3, no extra value is provided by the tool description.

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

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

The description clearly states the verb 'Fetch', the resource 'authority metrics', and the scope 'target (domain, host or URL)'. It distinguishes from sibling tools like getDomainAuthority or getPageAuthority by emphasizing its applicability to any target format, including root domain, subdomain, or full URL.

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 related siblings such as getDomainAuthority or getPageAuthority. The description does not mention any prerequisites, exclusions, or alternative tools, leaving the agent to infer usage context without explicit direction.

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

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

No annotations are provided, so the description carries the full burden. It discloses batch request support but does not mention whether the operation is read-only, rate limits, or authentication needs. Basic transparency but could be improved.

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

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

The description is very concise: two sentences that clearly state the purpose and the batch capability. No unnecessary words; front-loaded with key 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?

The tool has three parameters, all well-described in schema, but no output schema exists. The description does not clarify what the return value looks like (e.g., a count number). For a simple tool, 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?

All parameters are described in the input schema (100% coverage). The description adds no new meaning beyond 'supports batch requests', which is already implied by the target schema allowing arrays. Baseline score applies.

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 returns the total number of backlinks for a target and supports batch requests. The name directly corresponds to the function. Among siblings like getBacklinksAnchors or getBacklinksSummary, this tool is uniquely identified by 'count'.

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 'supports batch requests' but offers no guidance on when to use this tool versus alternatives (e.g., getBacklinksSummary). No exclusions or recommended contexts 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 carries the full burden. It discloses the async nature and possible statuses, but omits details on error handling, authentication, or rate limits.

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, no filler, 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?

For a simple status check with one parameter, the description covers input and output adequately, though it does not address potential edge cases like expiration of the download URL.

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 schema already describes the parameter with 100% coverage, and the description adds value by specifying the source of the task ID (from exportBacklinksData method).

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 checks the status of an asynchronous backlinks export task, specifying the exact purpose and distinguishing it from siblings like other data retrieval or audit 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 implies usage as a follow-up to an export call, but does not explicitly state when to use it versus alternatives or provide when-not 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?

No annotations are provided, so the description must disclose behavioral traits. It mentions sorting and limit controls (already in schema) but omits details like pagination behavior, whether results are exhaustive, rate limits, or permission requirements. The description adds minimal value beyond the input schema.

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 that is direct and to the point. Every word adds value: it identifies the tool category ('Data Tool'), the action ('Fetch'), the resource, and key features (sorting and limit controls). No unnecessary text.

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 there is no output schema, the description should clarify what the output contains. It does not describe the return format (e.g., list of URLs with counts) or error handling. The tool's role is clear, but for a data retrieval tool, the lack of output details leaves a gap.

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 detailed parameter descriptions, so baseline is 3. The description adds the phrase 'with sorting and limit controls' but does not provide extra meaning beyond what the schema already offers. No examples or typical usage are included.

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 fetches 'site pages that have backlinks' with sorting and limit controls, specifying the verb 'Fetch' and resource 'site pages with backlinks'. This distinctly differentiates it from siblings like DATA_getAllBacklinks (which returns backlinks, not pages) and other backlink 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 does not mention prerequisites, recommended scenarios, or when not to use it. The only context is the tool name and description, which requires the agent to infer usage from its function.

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 carry the full behavioral burden. It mentions batch requests but does not disclose whether the tool is read-only, destructive, or has rate limits. The term 'Data Tool' weakly implies read-only, but it's not explicit.

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, front-loaded with the core purpose ('Returns key statistics'). No fluff. Could be slightly more structured but overall concise.

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 explain return values. It mentions 'key statistics' but does not list them, leaving ambiguity. For a tool with 3 parameters and batch support, more detail on output structure is needed.

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

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

Input schema covers all parameters with descriptions, achieving 100% coverage. The description adds the concept of batch requests via 'target' array, which goes beyond the schema. Baseline 3 is appropriate as the description adds marginal 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 returns key statistics like backlinks count and referring domains, with batch support. The verb 'returns' and resource 'key statistics' are specific. However, it does not differentiate from sibling tools like DATA_getBacklinksCount or DATA_getBacklinksSummary, which may 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 explicit guidance on when to use this tool versus alternatives such as getBacklinksCount (just count) or getBacklinksRefDomains (only ref domains). The description implies it's for summary stats but lacks when-not and alternative 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?

Without annotations, the description carries full burden. It discloses cursor-based pagination and returns all backlinks but lacks details on side effects, rate limits, or authentication. For a read-only data tool, this is adequate but not rich.

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?

Single sentence that is front-loaded with the tool's purpose and pagination mechanism. Every word contributes value; no redundancy.

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

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

Given 7 parameters and no output schema, the description could provide more guidance on pagination flow or response structure. It is adequate for a simple listing but lacks completeness for complex iteration.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds context by mentioning cursor-based pagination related to the 'next' parameter, but otherwise does not add significant meaning 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 returns all backlinks pointing to a target using cursor-based pagination. It specifies the resource (backlinks) and action (returns), and distinguishes from sibling tools like DATA_getBacklinksCount or DATA_getBacklinksAnchors.

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 usage for large datasets via pagination but does not explicitly provide guidance on when to use this tool versus alternatives like DATA_getAllBacklinks or other backlinks tools. No when-not-to-use or exclusion criteria are given.

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

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

No annotations provided, so description must disclose behavior. It only mentions retrieval with sorting/limiting, but omits read-only nature, pagination, rate limits, or output structure.

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?

Single sentence of 21 words, front-loaded with 'Data Tool:' (slightly redundant). No wasted words, but could be slightly more structured.

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

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

Given 5 parameters, no output schema, and no annotations, the description underspecifies what the tool returns and lacks context on output format or behaviors beyond basic retrieval.

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?

Input schema has 100% coverage with descriptions for all 5 parameters. Description adds no extra meaning beyond stating 'options for sorting and limiting results,' which is already implied.

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?

Describes a specific verb ('Retrieves') and resource ('list of referring domains pointing to the specified target'), clearly distinguishing this from sibling tools that handle backlinks, anchors, or audits.

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 like DATA_getAllBacklinks or DATA_getBacklinksAnchors. Missing context such as 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?

No annotations are provided, so the description must disclose behavioral traits. It only says 'retrieves a summary' without specifying what metrics are included, whether it is read-only, or any other behavioral details.

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

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

The description is a single, clear sentence that is front-loaded with the tool category and purpose. It is concise but could include more context.

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 large number of sibling backlink tools and the lack of output schema, the description is incomplete. It does not specify what the summary contains or how it differs from similar tools.

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 descriptions for all parameters. The description adds no additional meaning beyond the schema, so 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 clearly states it retrieves a summary of backlink metrics for targets, but does not differentiate from sibling tools like DATA_getBacklinksMetrics or DATA_getBacklinksCount.

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 other backlink tools. The description does not provide context for appropriate usage 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?

No annotations are provided, so the description must carry the full burden. It mentions pagination but does not disclose sort order, rate limits, error handling for invalid audit_id, or whether the list includes metadata like crawl dates. This leaves significant behavioral gaps.

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

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

The description is a single sentence that is mostly concise but includes the redundant prefix 'Data Tool:'. It could be streamlined without losing 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 a simple list tool, the description covers the core purpose. However, it does not mention output format, ordering of results, or pagination details beyond 'paginated list'. Minor gaps given the tool's simplicity.

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 clear descriptions for each parameter. The description does not add extra context beyond what the schema provides, such as explaining how limit and offset work together or default behaviors. Baseline score 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 clearly states the tool returns a paginated list of all URLs found during an audit, providing a complete sitemap. It uses a specific verb ('Returns') and resource ('crawled pages'), and distinguishes it from sibling tools like getAuditReport or getAuditPagesByIssue.

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

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

No guidance is provided on when to use this tool versus alternatives such as getAuditPagesByIssue or getAuditReport. There is no mention of prerequisites or scenarios where this tool is appropriate.

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

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

No annotations are provided, so the description must cover behavioral traits. It explains the output (daily backlink counts) but omits details such as rate limits, pagination, data freshness, or any constraints on the target parameter beyond what is in the schema.

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 that front-loads the core purpose. Every word contributes meaning, and there is no redundant or verbose 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?

For a tool with no output schema, the description adequately explains the return value format (daily counts). However, it does not address potential edge cases like empty date ranges or unsupported targets, but given the overall simplicity it is mostly sufficient.

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 75%, with descriptions for target, date_to, and date_from. The description adds no new parameter-level context beyond the schema. It does not explain the 'mode' parameter or its interaction with 'target', leaving some 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?

The description clearly states the tool returns a number of live backlinks for every day within a specified date range for a specified target. It uses specific verbs and resources, distinguishing it from related tools like DATA_getBacklinksCount that may return aggregated counts.

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 its many siblings, nor does it mention prerequisites, limitations, or alternative tools. This is a critical gap given the large sibling 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?

No annotations are provided, and the description only states what the tool returns without disclosing behavioral traits such as data retrieval limits, error handling, or side effects.

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

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

The description is a single concise sentence that front-loads the core purpose without extraneous words, earning its place with clear 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 output schema, the description provides basic understanding but lacks details about the return format or example usage, leaving some gaps for the agent.

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

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

Schema description coverage is 67%, so some parameters ('target', 'histogramMode') are described but 'mode' lacks description. The tool description does not add meaning beyond the schema, resulting in adequate but not enhanced parameter 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 clearly states the verb 'Returns information' and the resource 'distribution of Domain InLink Rank (Domain Authority)'. It specifies the scope 'of all the domains that reference a specific target', distinguishing it from similar tools like DATA_getDomainAuthority.

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 usage for retrieving distribution data but provides no explicit guidance on when to use this tool versus siblings, nor any exclusions or prerequisites.

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

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

No annotations are provided, and the description does not disclose any behavioral traits like pagination, data range, or rate limits. It only states the basic retrieval action.

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?

One sentence efficiently states the purpose with no wasted words, though it could include more context without harming 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?

With 6 parameters, no output schema, and no annotations, the description is too sparse. It does not explain return format, pagination details, or data range constraints, leaving significant gaps for the agent.

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

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

Schema description coverage is 100%, so the schema fully documents parameters. The description adds no new information beyond what is already in the schema, meeting baseline expectations.

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 paid ads for a specific domain, using a specific verb and resource, distinguishing it from siblings like getDomainAdsByKeyword.

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, no mention of when not to use, and no exclusions 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?

With no annotations provided, the description must disclose behavioral traits. It only says 'retrieves', implying a read operation, but omits details like pagination, data scope, auth needs, or whether it's destructive. The schema reveals pagination but the description adds no value.

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?

A single sentence front-loading the core purpose. No filler words; every word earns its place.

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

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

Given 6 parameters, no output schema, and no annotations, the description is too minimal. It lacks details on output format, date range behavior, pagination, and interpretation of results.

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

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

Schema coverage is 100% with descriptions for all 6 parameters. The tool description adds no extra meaning beyond what the schema already provides, so baseline 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 the verb 'retrieves' and the resource 'paid ads', scoped to 'a specific keyword'. This clearly distinguishes it from siblings like getDomainAdsByDomain which is by 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 on when to use this tool versus alternatives (e.g., getDomainAdsByDomain). The description does not mention exclusions, prerequisites, or context for 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?

No annotations provided. The description does not disclose behavioral traits such as data freshness, rate limits, or whether the tool is read-only. It only restates 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?

Single sentence, no filler, directly to the point. Could be slightly more informative without losing brevity.

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, so the description should hint at the return structure. It does not. Also lacks explanation of 'InLink Rank' or 'Domain Authority'. Minimal context given.

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 one parameter 'target'. The description adds some context by listing acceptable inputs (root domain, host, or URL) but does not clarify how different input types are handled. Baseline 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 clearly states it returns information about the domain InLink Rank (Domain Authority) for the root domain of a target page. It uses a specific verb and resource, and distinguishes from siblings like DATA_getPageAuthority and DATA_getDomainAuthorityHistory.

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. Sibling tools exist for page authority and history, but the description does not mention when to prefer this one.

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?

Annotations are absent, so the description carries the full burden. It indicates it returns a histogram (read-like operation) but does not disclose behavioral traits like whether it is read-only, any rate limits, or side effects. The name suggests get, but no explicit confirmation.

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?

Single sentence, directly stating the core function. No extraneous text.

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?

Missing output schema and limited parameter documentation. Does not describe histogram details (buckets, range, return format). Incomplete for an agent to fully understand the result.

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%, with 'target' documented but 'mode' only described by enum values. The description does not explain what 'mode' or 'target' control beyond the schema's minimal description. It fails to compensate for the schema gap.

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

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

The description clearly states the tool returns a histogram of Domain Authority for referring domains linking to the target. It uses specific verbs ('Returns') and resource ('bucketed histogram'), and distinguishes from sibling tools like DATA_getDomainAuthority and DATA_getDistributionOfDomainAuthority by specifying 'histogram'.

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 DATA_getDomainAuthority or DATA_getDistributionOfDomainAuthority. No context about prerequisites or scenarios.

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

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

The description discloses that the target is resolved to PLD, which is a behavioral trait. No annotations exist, so the description carries the burden. However, it does not mention data freshness, rate limits, or what happens if no history is available.

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, no redundant information. Clearly describes core functionality and key behavioral detail. Efficient and front-loaded.

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

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

While the tool has 4 parameters with good schema coverage, the description does not mention return format, ordering, bounds, or pagination. With no output schema, more detail about the returned data structure would improve completeness.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds minimal value beyond schema, only clarifying PLD resolution which is already implied in the schema's description 'PLD is extracted'. No additional context for date range or granularity.

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 returns historical Domain InLink Rank values for a target domain and explains PLD resolution. This distinguishes it from siblings like getDomainAuthority (current) and getPageAuthorityHistory (page-level).

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 for historical authority data but does not explicitly specify when to use this tool versus alternatives like getDomainAuthority for current values or getPageAuthorityHistory for page history. No when-not-to-use or exclusion criteria are given.

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

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

With no annotations, the description carries full burden but only states basic functionality. It does not disclose behavioral traits such as read-only nature, rate limits, data freshness, or side effects. The agent lacks essential behavioral context.

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

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

The description is a single sentence with no wasted words. However, it could be slightly more structured by front-loading key aspects like the tool's category or adding a brief note on parameter usage.

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 4 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the response format, pagination, or limitations, leaving the agent with significant ambiguity about how to use the tool effectively.

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

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

Schema coverage is 100%, so baseline is 3. The description adds minimal value: it mentions 'organic or paid' which aligns with the type parameter, but does not clarify semantics of stats, domain, or source beyond what the schema already defines.

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 specifies the action ('retrieves a list'), the resource ('competitors for a domain'), and distinguishes between organic and paid types. This effectively differentiates it from sibling tools like getDomainKeywords or getDomainAdsByDomain.

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, nor any context on selecting between organic and paid modes. The description does not address prerequisites 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?

No annotations are provided, so the description must disclose behavioral traits. It only states it retrieves data, without mentioning if it is read-only, pagination behavior, or any side effects. The description is insufficient for a data tool.

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

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

The description is a single concise sentence that front-loads the core purpose. No unnecessary 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?

Despite 37 parameters and no output schema, the description does not mention return format, pagination, or key usage notes. Users would need to infer behavior from the schema alone.

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%, so the baseline is 3. The description adds no additional meaning beyond the schema; all parameter details are in the input schema itself.

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 keywords for a domain, specifying both organic and paid search. It uses a specific verb and resource, distinguishing it from sibling tools like DATA_getDomainKeywordsComparison.

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 usage for retrieving domain keywords but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among sibling 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 provided, so the description carries full burden. It discloses the comparison logic and diff modes but lacks details on pagination, rate limits, data freshness, or whether the tool is read-only. The description is honest but incomplete for behavioral expectations.

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 sentences with clear front-loading of purpose. Every sentence adds value, no redundancy. Well-structured for quick parsing.

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 11 parameters and no output schema, the description explains the core functionality and usage well. It covers the main use cases but could be slightly more complete by mentioning pagination or return format, though those are in 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 100%, so the baseline is 3. The description adds value for 'domain' and 'compare' by explaining their roles in the gap analysis, but it does not elaborate on other parameters like 'cols' or 'order_field' beyond what the schema provides.

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 analyzes and compares keyword rankings of two domains, with explicit modes for common keywords and keyword gap. The swapping advice clarifies how to get the reverse gap, distinguishing it from single-domain tools like DATA_getDomainKeywords.

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 when to use diff=0 vs diff=1 and provides a workaround for the reverse gap. It does not explicitly compare to sibling tools like DATA_getDomainCompetitors, but the context is clear enough for an agent to select this tool for pairwise comparison.

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 responsibility for behavioral transparency. It only states it's a data tool that fetches data, implying a read operation, but does not explicitly confirm read-only nature, side effects, permissions, or rate limits. This is insufficient for safe use.

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

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

The description is a single sentence, which is concise. However, it includes the redundant prefix 'Data Tool:' and lacks structured information. It could be more informative without being longer.

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 having 4 parameters and no output schema, the description is extremely brief. It does not explain what 'domain overview by database' entails, how the parameters interact (e.g., url vs domain), or what the return format looks like. This leaves significant gaps for an agent.

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

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

Schema description coverage is 100%, so the input schema adequately documents all parameters. The description adds no additional meaning beyond what the schema provides, resulting in a baseline score of 3.

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

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

The description clearly states the action ('Fetch domain overview by database') and includes the API endpoint. However, it does not distinguish this tool from similar siblings like DATA_getDomainOverviewWorldwide or DATA_getDomainOverviewHistory, leaving ambiguity about what 'by database' specifically means.

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

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

No guidance is provided on when to use this tool versus alternatives. The description lacks any context about appropriate usage scenarios, prerequisites, or when to choose other domain overview tools from the sibling 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?

No annotations exist, so description must disclose behavioral traits. It states it retrieves data but does not mention rate limits, data freshness, or whether it is read-only. Adequate but lacks depth.

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?

Single sentence is concise and front-loaded with the tool's purpose. However, it could benefit from a brief structured breakdown of 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?

No output schema, and description does not explain return values or format. For a data retrieval tool, describing the output structure would aid completeness.

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

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

Schema coverage is 100% with descriptions for all parameters. Description adds no extra meaning beyond the schema, so baseline score 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 clearly states it retrieves historical data for domain traffic and keyword rankings, which aligns with the tool name and distinguishes it from sibling tools focused on audits, backlinks, or other data.

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

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

No guidance on when to use this tool versus alternatives like DATA_getDomainKeywords or DATA_getDomainOverviewWorldwide. No when-to-use or when-not-to-use context 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 present, and the description does not disclose behavioral traits such as read-only status, authentication requirements, rate limits, or side effects. The phrase 'Data Tool' weakly implies read-only, but this is insufficient for 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 sentence that is concise and directly states the tool's purpose. It is appropriately sized without unnecessary 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?

The description is very minimal. There is no output schema, and the description does not explain what the response contains (e.g., structure, data fields). Given the tool's four parameters, more context is needed for complete understanding.

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

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

Schema description coverage is 100%, so the input schema fully explains each parameter. The description adds no further clarification beyond what is already in the schema, which meets the baseline but does not exceed it.

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 an aggregated worldwide overview of domain metrics. It is specific with verb and resource but does not differentiate from sibling tools like DATA_getDomainOverviewDatabases or DATA_getDomainOverviewHistory, though the name provides some distinction.

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

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

No guidance is provided on when to use this tool versus alternatives. The description lacks any mention of context, prerequisites, or scenarios for which this tool is best suited.

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 convey behavioral traits. It only states it returns a paginated list but does not disclose pagination behavior, data freshness, rate limits, or that this is a read-only operation. The description lacks sufficient detail for an agent to understand side effects or constraints.

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 that is direct and front-loaded. It contains no fluff and succinctly conveys the core purpose.

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

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

With 5 parameters (including a nested filter array) and no output schema, the description should cover return structure, pagination details, and filter usage. It only mentions 'paginated list' without explaining offset/limit. The description is incomplete for an agent to effectively invoke the tool without additional schema parsing.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description does not add extra meaning beyond what's in the schema. For instance, the filter array is complex but the description doesn't explain how to build filters. The description remains at baseline because it doesn't compensate for schema descriptions.

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 is clear: 'Returns a paginated list of every hyperlink discovered across the entire site during the audit.' It uses a specific verb ('Returns') and resource ('paginated list of hyperlinks') and distinguishes from sibling tools by focusing on hyperlinks found during an audit, not other link 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?

No guidance on when to use this tool versus alternatives (e.g., other getBacklinks tools). The description only states what it does, not when to use it or when to avoid it. For example, it doesn't clarify if this is for internal links only or all links, nor does it mention prerequisites.

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