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 says the tool 'detects whether bypass succeeded' but does not describe the return format (boolean, score, structured report), any confidence/threshold behavior, permission needs, or whether the analysis is deterministic. That is a significant gap for a tool whose entire value is its verdict output.

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 front-loaded sentence with no filler. It is efficiently sized for the definition given, though the brevity borders on under-specification rather than optimal 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 no annotations and no output schema, the description should explain what the analysis returns (verdict type, fields, interpretation), but it does not. An agent cannot tell what calling this tool yields beyond a vague 'detection'.

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

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

Schema coverage is 100%, with both parameters (response, optional payload_id) fully documented in the schema. The description adds no additional meaning about parameter format or the role of payload_id, so the baseline 3 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?

States a specific verb (分析/analyze) and resource (目标AI系统的响应/target AI system's response), plus the detection goal (whether safety restrictions were bypassed). This clearly distinguishes it from list/get/search/generate siblings, though it doesn't explicitly differentiate from generate_report, which could also involve analysis.

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 invoke this tool, what prerequisite steps (e.g., run_test_sequence) should precede it, or how it relates to generate_report. Usage is only inferable from the name and workflow 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 the full behavioral burden, yet it discloses nothing about the generated output's form, whether the payload is persisted or executed, safety/authorization expectations, or rate limits. Only the generative nature implied by '生成' is communicated.

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

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

A single compact sentence with the mechanism and outcome front-loaded and no wasted words. It is arguably over-brief for a tool with no annotations, but there is no filler or redundancy.

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

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

For a generation tool with no annotations and no output schema, the definition is too thin: it never explains what is returned, whether the payload is stored, or the safety context for producing attack payloads. The 100% schema coverage carries the parameter side, but the descriptive side is materially incomplete.

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 both parameters, including the supported variable placeholders ({{target}}, {{action}}, {{context}}) and the nested variables object. The description adds no meaning beyond the schema, so the baseline 3 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?

The description states a specific verb and resource ('基于模板生成自定义攻击载荷' – generate a custom attack payload from a template) and even names the mechanism (template-based). It is clearly distinguishable from retrieval siblings like search_payloads or get_payload_by_id, though it does not explicitly name them.

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

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

There is no explicit when-to-use guidance, no statement of when to prefer generating a custom payload over fetching an existing one via search_payloads/get_payloads_by_category, and no prerequisites or exclusions. The distinction from sibling retrieval tools is left entirely to inference.

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. Beyond implying a report is generated, it says nothing about side effects, permissions, output persistence, or whether generation is deterministic. A one-line description leaves the behavioral contract largely unspecified.

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

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

The description is a single, short, front-loaded phrase with no redundant or filler content. It is efficient, though brevity here comes at the cost of information rather than from careful trimming.

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 no annotations, no output schema, and a nested array parameter, the description should say more about behavior and usage. A report-generation tool that accepts test results and a format but explains neither its purpose context nor its output is incomplete for an agent to invoke confidently.

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%: both the format enum (markdown/json/html with default) and the test_results array are documented in the schema itself. The description adds nothing beyond the schema, so the baseline of 3 is appropriate.

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

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

The description '生成测试报告' states a verb (生成) and resource (测试报告), so the basic action is clear. However, it does not distinguish this tool from any sibling, several of which (analyze_response, run_test_sequence) also work with test output. It is vague about scope relative to the toolset.

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?

There is no guidance on when to use this tool versus alternatives. Nothing indicates whether it should be called after run_test_sequence, whether it supersedes analyze_response, or under what conditions report generation is appropriate.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it retrieves a payload but does not describe what happens if the ID is not found, whether it requires authentication, or any rate limits. The behavioral traits are largely unspecified.

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

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

The description is a single, concise sentence that front-loads the key information: the action (获取) and the resource (攻击载荷). It is appropriately sized for a simple lookup tool with zero waste.

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

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

Given that the tool has no annotations and no output schema, the description should provide more context about behavior (e.g., error handling, return format). It is incomplete for an agent to call it correctly without assumptions, especially regarding what happens on missing IDs or authentication requirements.

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 description coverage is 100%, so the schema already fully documents the payload_id parameter, including examples. The description adds no additional semantic meaning beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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

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

The description '根据载荷ID获取特定攻击载荷' clearly states a specific verb (获取) and resource (攻击载荷) with the scope of retrieving by ID. It is distinguishable from siblings like list_attack_categories or search_payloads by its ID-based lookup. However, it does not explicitly contrast with siblings like get_payloads_by_category, leaving minor ambiguity.

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. For example, it does not say to use this when a specific payload ID is known, as opposed to get_payloads_by_category or search_payloads. 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 are provided, so the description carries the full behavioral burden. It does not state that this is a read-only lookup, nor does it describe ordering, pagination, result size, or what happens when the category is unknown or empty — all of which matter for a bulk fetch of attack payloads.

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 short sentence with the scope qualifier front-loaded and zero filler. It is efficient, though so terse that concision comes at the cost of the guidance an agent would need.

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 no annotations and no output schema, the description should explain the return shape (payload list, fields, variants) and read-only nature. It supplies none of that, leaving an agent unable to predict what the call returns or how results are bounded.

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 both parameters (category with example IDs, include_variants with a default) are already documented in the schema. The description adds nothing beyond '指定类别', which is the schema baseline, so 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?

States a specific verb and resource ('获取...攻击载荷') with the scope qualifier '指定类别' (specified category), so an agent knows it returns a filtered collection. It does not, however, differentiate itself from the closely related siblings get_payload_by_id or search_payloads, leaving the boundary 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?

There is no statement of when to use this tool versus search_payloads, get_payload_by_id, or list_attack_categories. Usage is only inferable from the name and the required 'category' parameter; no prerequisites or exclusions are given.

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

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

No annotations are provided, so the description carries the burden, and it implies a safe, read-only enumeration with no side effects. That implication is reasonable for a zero-parameter list call, but it is never explicit — no statement about ordering, completeness, or whether results are cached/static.

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 short sentence with no filler, and the resource and return content are front-loaded. It is efficient, though extremely minimal — there is nothing padded but also nothing extra to aid selection.

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 zero-parameter, no-output-schema tool, the description states what is returned (all categories with their descriptions), which is the key missing piece when no output schema exists. It is nearly complete, with the only gap being its relationship to the payload-oriented siblings.

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

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

The tool takes zero parameters, so per the baseline rule a 4 applies. The description correctly signals that no filtering input is accepted by saying it lists ALL categories.

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

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

The description states a specific verb (列出/list) and resource (攻击类别/attack categories) plus the returned detail (及其描述/and their descriptions), which is unambiguous on its own. It does not, however, distinguish itself from the sibling get_payloads_by_category, which an agent could plausibly confuse with a category-listing tool.

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

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

There is no when-to-use guidance, no statement of prerequisites, and no mention of alternatives such as get_payloads_by_category. The agent must infer that this is the discovery/entry-point call before drilling into payloads.

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 behavioral burden. It does not disclose what happens during execution (side effects, duration, outputs, permissions, whether sequences are destructive). The single word '执行' (execute) implies an action but reveals nothing about behavior.

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

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

The description is a single concise sentence with no wasted words. It is front-loaded and clear, though it is arguably too short for a tool with behavioral complexity.

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

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

Given no annotations, no output schema, and a mutation-like action (executing sequences), the description is inadequate. It omits necessary details such as what gets executed, expected outcomes, safety considerations, or 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?

The schema has 100% description coverage and includes an example for sequence_name, so the parameter is well documented in the schema. The description adds no parameter meaning beyond what the schema already provides, so the baseline of 3 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?

The description states a specific verb and resource ('执行预定义的测试序列' = execute a predefined test sequence), which is clearer than a tautology. However, it does not distinguish this tool from siblings like analyze_response or generate_report, and the purpose is generic within the security/payload context.

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

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

There is no guidance on when to use this tool versus alternatives such as analyze_response or list_attack_categories. No prerequisites, no context, no 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 carries the full behavioral burden, yet it says nothing about return format, result limits, pagination, or whether the search is read-only. 'Search' implies a non-mutating operation, but this is inferred, not disclosed.

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 short sentence with no filler, but it is sparse rather than tight — nothing is front-loaded beyond the bare purpose and no secondary information is offered. Adequate but minimal.

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

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

For a two-parameter search tool with no annotations and no output schema, the description should explain result shape, matching behavior, and how it relates to the payload-retrieval siblings. None of that is present, leaving meaningful gaps.

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% — both 'keyword' and 'search_in' are documented in the schema, including the default of '全部' for search_in. The description adds no format, matching-rule, or case-sensitivity details beyond what the schema already provides, so the baseline 3 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?

The description states a specific verb and resource ('搜索' + '攻击载荷') plus the filter condition ('包含特定关键词'), so the agent knows exactly what the tool does. It does not, however, explicitly differentiate itself from the keyword-adjacent siblings get_payloads_by_category or list_attack_categories.

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?

There is no guidance on when to use this search versus list_attack_categories or get_payloads_by_category, and no exclusion or prerequisite is stated. The agent must infer routing purely from the tool names.

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