Vectra AI MCP Server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation4/5
Most tools have distinct purposes, but there is some overlap that could cause confusion. For example, list_detection_ids, list_detections_with_basic_info, and list_detections_with_details all serve similar functions with varying detail levels, which might lead to misselection. However, descriptions help clarify differences, and other tools like create_assignment or get_detection_pcap are clearly unique.
Naming Consistency5/5Tool names follow a consistent verb_noun pattern throughout, such as create_assignment, get_account_details, list_detections_with_details, and mark_detection_fixed. All tools use snake_case, and verbs like create, get, list, delete, and mark are applied predictably across different nouns, making the set easy to navigate.
Tool Count3/5With 23 tools, the count is borderline high for the security investigation domain, potentially feeling heavy. While the tools cover various aspects like assignments, detections, entities, and users, some could be consolidated (e.g., multiple detection listing tools) to reduce complexity without losing functionality.
Completeness4/5The tool set provides comprehensive coverage for security investigation workflows, including CRUD operations for assignments and notes, detailed retrieval for accounts, hosts, and detections, and listing functions with filtering. Minor gaps exist, such as no tools for updating assignments or managing users beyond listing, but agents can likely work around these with the available tools.
Average 3.1/5 across 23 of 23 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions filtering, sorting, and that it returns a JSON string, but lacks critical details: whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior (beyond the 'limit' parameter), or what happens when no matches are found. For a tool with 9 parameters and no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with three sentences that cover purpose and return format. It's front-loaded with the main functionality. However, the 'Returns:' section could be integrated more smoothly, and there's some redundancy ('Use this to get a list...' repeats the purpose). Overall efficient but with minor structural improvements possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, filtering/sorting functionality) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and multiple sibling tools, it should provide more context about behavioral traits and usage differentiation. The description meets basic requirements but leaves gaps in guidance and transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds minimal value beyond the schema, only mentioning 'filtering and sorting options' generically without explaining specific parameters or their interactions. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'List detection IDs with filtering and sorting options', which provides a clear verb ('List') and resource ('detection IDs'). However, it doesn't distinguish this tool from sibling tools like 'list_detections_with_basic_info' or 'list_detections_with_details', leaving ambiguity about when to use each. The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 mentions 'Use this to get a list of detection IDs based on various criteria', but doesn't specify scenarios where this is preferred over similar tools like 'list_detections_with_basic_info' or 'get_detection_count'. No explicit when/when-not instructions or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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. While it mentions the tool 'returns entities with all their detailed information,' it doesn't address critical behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or what happens when filters return no results. The description is insufficient for a tool with 8 parameters and no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise with three sentences, but the structure is problematic. The second sentence 'Returns: str: Formatted string with list of detections.' contains a significant contradiction - it mentions 'detections' while the tool is about 'entities.' This error undermines the description's effectiveness despite its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, no annotations, but with output schema), the description is incomplete. While the output schema exists (reducing the need to explain return values), the description fails to address behavioral aspects, usage context, and contains a factual error about returning 'detections' instead of 'entities.' For a filtering tool with many parameters, more comprehensive guidance is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 thoroughly. The description adds minimal value beyond the schema - it mentions 'various filters' and that it returns 'detailed information,' but provides no additional parameter semantics, syntax examples, or clarification beyond what's in the structured schema. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List entities (hosts & accounts) in Vectra platform based on various filters.' It specifies the resource (entities) and action (list) with filtering context. However, it doesn't explicitly differentiate from sibling tools like 'lookup_entity_info_by_name' or 'list_entity_detections', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools that also retrieve entity information (e.g., 'lookup_entity_info_by_name', 'get_account_details', 'get_host_details'), there's no indication of when this filtered listing approach is preferred over more specific lookup tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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. It mentions that it 'Returns: str: Formatted string with assignment details' and 'Raises: Exception: If assignment creation fails', which adds some context beyond the basic action. However, it lacks critical details like whether this is a mutating operation (implied by 'Create'), what permissions are required, or any side effects, leaving significant gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear purpose statement followed by return and error information in separate lines. It avoids unnecessary verbosity, though the formatting with quotes and indentation could be slightly cleaner. Every sentence serves a purpose, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there's an output schema (implied by 'Returns' in the description) and the input schema has full coverage, the description covers the basics: action, return type, and error handling. However, for a creation tool with no annotations, it should ideally include more behavioral context, such as mutational impact or prerequisites, to be fully complete. It's adequate but has clear gaps in usage guidance and transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear details for all three parameters (e.g., 'ID of the user to assign the entity to'). The description adds no additional parameter semantics beyond what's in the schema, such as explaining relationships between parameters or usage examples. With high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Create') and resource ('investigation assignment for an account or host'), making the purpose unambiguous. However, it doesn't explicitly differentiate this tool from its siblings like 'delete_assignment' or 'list_assignments', which would require mentioning it's specifically for creation rather than deletion or listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing existing entities or users, or when to choose this over other assignment-related tools like 'list_assignments_for_user'. This lack of context leaves the agent without direction on appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the tool 'Adds' a note (implying a write operation) and mentions a return confirmation, but lacks details on permissions, side effects, error conditions, or rate limits. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first sentence. The second sentence about returns is somewhat redundant given the output schema, but overall it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's mutation nature and lack of annotations, the description is incomplete—it doesn't address behavioral risks or context. However, the presence of an output schema reduces the need to explain return values, and the schema covers parameters well, making it minimally adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add an investigation note') and target resource ('to an entity (host or account)'), making the purpose immediately understandable. It distinguishes from siblings by focusing on note creation rather than assignments, detections, or listings, though it doesn't explicitly contrast with similar tools since none exist in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or exclusions, leaving the agent to infer usage solely from the tool name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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 mentions that it returns a JSON string and can raise an exception on failure, which adds some behavioral context. However, it lacks details on permissions, rate limits, side effects, or what 'assignment details' entail, leaving significant gaps for a tool that likely accesses sensitive investigation data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose. The 'Returns' and 'Raises' sections are useful but could be more integrated. No wasted sentences, though it could be slightly more polished in structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is an output schema (implied by 'Has output schema: true'), the description doesn't need to detail return values. However, with no annotations and a tool that likely involves sensitive data access, the description should provide more behavioral context (e.g., authentication needs, data sensitivity). It's minimally adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the parameters. The description does not add any meaning beyond what the schema provides (e.g., it doesn't explain the relationship between entity_ids and entity_type or provide examples). Baseline 3 is appropriate as the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieve') and resource ('investigation assignment for a specific account'), making the purpose understandable. However, it specifies 'account' while the input schema includes both 'account' and 'host' entity types, creating a slight mismatch. It doesn't explicitly distinguish from siblings like 'list_assignments' or 'get_assignment_detail_by_id'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'list_assignments' or 'get_assignment_detail_by_id'. The description only states what the tool does without context about prerequisites, appropriate scenarios, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic purpose and return type. It doesn't mention whether this is a read-only operation (implied but not explicit), potential rate limits, authentication requirements, or how the count is calculated (e.g., real-time vs cached). The description adds minimal behavioral context beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences: one stating the purpose and one describing the return value. Both sentences earn their place by providing essential information. The structure is front-loaded with the main purpose first. There's no unnecessary verbiage or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (7 parameters, filtering logic) and the presence of an output schema (implied by 'Returns: str'), the description is minimally adequate. It states what the tool does and what it returns, but doesn't provide context about performance, limitations, or relationship to sibling tools. With no annotations and rich parameter schema, the description could do more to guide usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'specified criteria' but doesn't elaborate on what those criteria are. However, with 100% schema description coverage, all 7 parameters are well-documented in the schema with clear descriptions, defaults, and formats. The description adds no parameter semantics beyond what the schema already provides, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the total count of detections matching the specified criteria.' This is a specific verb+resource combination (get + count of detections). However, it doesn't explicitly differentiate from sibling tools like 'list_detection_ids' or 'list_detections_with_basic_info', which might also return counts or filtered lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'list_detection_ids', 'list_detections_with_basic_info', and 'list_detections_with_details' available, there's no indication whether this tool is preferred for count-only queries or how it differs functionally from those listing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions that it returns a JSON string and may raise an exception on failure, but lacks critical details like authentication requirements, rate limits, whether it's read-only (implied but not stated), or what specific details are included in the response.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief with three sentences that each serve a purpose: stating the action, describing the return value, and noting potential errors. It's front-loaded with the core purpose, though the formatting with separate 'Returns' and 'Raises' sections could be more integrated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (though not shown here), the description doesn't need to explain return values in detail. However, for a tool with no annotations and multiple similar siblings, the description should provide more context about when to use it and what distinguishes it from alternatives to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents the single 'detection_id' parameter. The description adds no additional parameter information beyond what's in the schema, maintaining the baseline score of 3 for adequate but not enhanced parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Get complete detailed information for a particular detection,' which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_detection_summary' or 'list_detections_with_details,' which likely provide less detailed or more aggregated information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools related to detections (e.g., get_detection_summary, list_detections_with_details), there's no indication of when this detailed view is preferred over other options or what prerequisites might exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It mentions the return type (Base64 encoded pcap data or error message) and potential exceptions, which adds some behavioral context. However, it lacks details on permissions, rate limits, or side effects, which are critical for a tool that retrieves sensitive data like pcap files.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by return and exception details. It's appropriately sized with no redundant information. However, the formatting with 'Returns:' and 'Raises:' sections is slightly verbose for a short description, but still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (implied by 'Has output schema: true'), the description doesn't need to explain return values in detail. However, for a tool with no annotations and potential complexity in handling pcap data, the description could benefit from more context on error conditions or usage constraints. It's minimally adequate but has gaps in behavioral transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'detection_id' well-documented in the schema. The description doesn't add any additional meaning beyond what the schema provides, such as format examples or constraints. Baseline 3 is appropriate since the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('pcap file for a specific detection'), making the purpose unambiguous. It distinguishes from siblings like get_detection_details or get_detection_summary by focusing on pcap retrieval. However, it doesn't explicitly differentiate from all siblings, such as list_detection_ids, which also involves detections but with different outputs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. For example, it doesn't mention prerequisites like needing a valid detection_id from list_detections or compare to other detection-related tools. The description only states what it does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions the tool returns a JSON string, it doesn't describe pagination behavior, rate limits, authentication requirements, or what happens when no assignments match filters. For a listing tool with zero annotation coverage, 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences that directly address purpose and return value. However, the 'Returns:' section is somewhat redundant since an output schema exists, and the formatting with extra whitespace slightly reduces structural efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and 100% schema description coverage, the description covers basic purpose adequately. However, for a tool with multiple sibling listing alternatives and no annotations, it should provide more contextual guidance about when to use this specific tool versus others.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters. The description mentions 'optional filtering by timestamp and resolved state' which aligns with the schema but adds no additional semantic context beyond what's already in the parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('investigation assignments'), making the purpose immediately understandable. It distinguishes from siblings like 'list_assignments_for_user' by specifying 'all investigation assignments', though it doesn't explicitly contrast with that sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_assignments_for_user' or 'get_assignment_detail_by_id'. It mentions optional filtering but doesn't explain when filtering is appropriate or what scenarios warrant using this tool over other listing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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 mentions the return type ('JSON string with list of assignments'), which is helpful, but lacks details on permissions, rate limits, pagination, error handling, or whether it's a read-only operation. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first sentence. The second sentence about returns is useful but could be integrated more seamlessly. Overall, it's efficient with minimal waste, though minor structural improvements could enhance readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is partially complete. It covers the basic purpose and return format, but lacks behavioral context (e.g., permissions, pagination) and usage guidelines. The output schema reduces the need to explain return values, but more operational details would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters (user_id and resolved). The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate when the schema handles parameter documentation effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('investigation assignments assigned to a user/analyst'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_assignments' (which might list all assignments without user filtering) or 'get_assignment_detail_by_id' (which retrieves details for a specific assignment), missing full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_assignments' (for all assignments) or 'get_assignment_for_entity' (for entity-based assignments), nor does it specify prerequisites or exclusions, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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 states the tool returns 'full details' and a JSON string, which is helpful, but lacks critical behavioral context: it doesn't mention whether this is a read-only operation, if there are rate limits, pagination behavior, or what 'full details' entails compared to other tools. The description adds some value but leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: one stating the purpose and one describing the return value. It's front-loaded with the core functionality. However, the second sentence could be omitted since an output schema exists, making it slightly redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (so return values are documented elsewhere) and schema coverage is 100%, the description is minimally adequate. However, for a tool with no annotations and multiple sibling tools offering similar functionality, it should provide more context on differentiation and behavioral traits to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters (entity_id and state). The description adds no additional parameter semantics beyond what's in the schema, such as explaining what an 'entity' represents or the implications of different states. Baseline 3 is appropriate when the schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all detections with full details for a specific entity'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_detection_ids' or 'list_detections_with_basic_info', which offer similar listing functionality but with different detail levels.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_detection_ids' (which might list IDs only) or 'list_detections_with_basic_info' (which might provide less detail). It mentions filtering by entity and state but doesn't explain why one would choose this over other detection-listing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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. It states the tool returns a JSON string with a list of users, which is helpful, but lacks critical details: it doesn't mention pagination behavior (despite a 'limit' parameter), authentication requirements, rate limits, or whether this is a read-only operation. For a list tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first sentence. The second sentence clarifies the return type, which is useful. There's no wasted text, but it could be slightly more structured (e.g., bullet points for key behaviors). Overall, it's efficient but not perfectly polished.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no annotations, but with an output schema), the description is minimally adequate. The output schema likely covers return values, so the description's mention of a JSON string is redundant. However, it lacks behavioral context (e.g., pagination, auth) and usage guidelines, making it incomplete for optimal agent understanding. It meets the bare minimum but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 4 parameters (role, last_login_after, email, limit) with descriptions, defaults, and constraints. The description adds no parameter-specific information beyond what's in the schema, but it does imply filtering capability through the phrase 'List users in the Vectra platform.' Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List users in the Vectra platform.' It specifies the verb ('list') and resource ('users'), and distinguishes it from siblings like list_assignments or list_entities. However, it doesn't explicitly differentiate from other user-related tools (none exist in the sibling list), so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for filtering, or comparison to other tools in the sibling list (e.g., when to use this versus get_account_details). The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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. It mentions that it returns a JSON string and raises an exception on failure, but lacks details on permissions, rate limits, side effects, or error handling specifics. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear purpose statement followed by return and error information in separate lines. However, the inclusion of 'Raises: Exception' is somewhat vague and could be more specific, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description does not need to explain return values in detail. It covers the basic purpose and error handling, but lacks context on usage relative to siblings and behavioral traits, which are important for a tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting the 'assignment_id' parameter. The description does not add any semantic details beyond what the schema provides, such as valid ID ranges or examples. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('retrieve') and resource ('details of a specific investigation assignment'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_assignment_for_entity' or 'list_assignments', which might retrieve similar data in different contexts, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 sibling tools like 'list_assignments' for broader queries or 'get_assignment_for_entity' for entity-specific assignments, leaving the agent to infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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. It states the tool returns a 'formatted string' but doesn't describe the format, potential errors, rate limits, authentication needs, or whether it's a read-only operation. While 'Get' implies a safe read, more behavioral context would help the agent use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose. The second sentence elaborates on the summary content, and the 'Returns:' section is clear. However, the second sentence is somewhat redundant with the first, and the structure could be tighter by merging these points.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, 100% schema coverage, output schema exists), the description is reasonably complete. It explains what the tool retrieves and the return format. The output schema handles return values, so the description doesn't need to detail them. However, it lacks context about when to use this versus sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the parameter 'detection_id' clearly documented. The description adds no additional parameter semantics beyond what's in the schema. According to the rules, with high schema coverage (>80%), the baseline score is 3 even without param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a concise summary of a detection' and lists the specific fields included (ID, name, category, etc.). It distinguishes this from sibling tools like 'get_detection_details' or 'get_detection_count' by focusing on a formatted summary rather than raw data or counts. However, it doesn't explicitly contrast with these siblings in the text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_detection_details' or 'list_detections_with_basic_info'. It mentions what the tool does but offers no context about prerequisites, typical use cases, or exclusions. The agent must infer usage from the tool name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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. It mentions the return format ('JSON string with list of entities'), which adds some context, but fails to address critical aspects like authentication needs, rate limits, error handling, or whether the operation is read-only or has side effects. For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with two sentences that directly state the purpose and return value. There is no wasted language, and it is front-loaded with the main action. However, the formatting includes extra whitespace and quotes, slightly detracting from perfect efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. It explains the purpose and return format, but with no annotations and multiple sibling tools, it lacks context on usage scenarios and behavioral traits. The output schema handles return values, so the description's brevity is acceptable but not fully informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description does not add parameter information, which is appropriate here. A baseline score of 4 is given as it compensates adequately for the lack of parameters by not introducing unnecessary details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List entities that are currently in lockdown.' It specifies the verb ('List') and resource ('entities in lockdown'), making the action and target explicit. However, it does not differentiate from sibling tools like 'list_entities' or 'list_detections_with_basic_info', which reduces clarity in a crowded namespace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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, context, or exclusions, such as how it differs from 'list_entities' or when lockdown status is relevant. This lack of usage context leaves the agent without direction in selecting among similar listing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses key behaviors: error handling (returns message if account not found, raises exception on request error) and return format (JSON string). However, it doesn't mention authentication requirements, rate limits, performance characteristics, or whether this is a read-only operation (though 'get' implies it).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably structured with purpose statement followed by return behavior, but contains redundancy (repeating 'detections, scoring information...' in both purpose and returns sections). The 'Returns:' section could be more concise, and some sentences could be tightened for better front-loading of key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, detailed retrieval), no annotations, but with 100% schema coverage and an output schema (implied by 'Returns' section), the description provides adequate context. It covers purpose, return format, and error handling, though could benefit from more behavioral context about the operation's characteristics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 7 parameters thoroughly. The description adds minimal value beyond the schema - it mentions customization parameters generically but doesn't explain specific parameter interactions or provide additional semantic context. 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get complete detailed information about a specific account entity' with specific resources listed (detections, scoring information, associated accounts, etc.). It distinguishes itself from siblings like 'get_host_details' by focusing on accounts rather than hosts, but doesn't explicitly contrast with other account-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. While it mentions customization parameters, it doesn't explain when this detailed retrieval is appropriate versus simpler listing tools like 'list_entities' or 'lookup_entity_info_by_name' available in the sibling tool list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
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 adds some useful context: it describes error handling (returns message if host not found, raises exception on request error) and hints at the return format ('Formatted string with detailed information'). However, it doesn't cover important aspects like authentication requirements, rate limits, or whether this is a read-only operation (though 'Get' implies reading).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence clearly states the purpose. The 'Returns:' section adds necessary behavioral details without redundancy. However, the formatting with line breaks and indentation slightly reduces readability, and the error handling details could be more integrated into the main flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (single parameter, read operation implied), no annotations, and no output schema, the description is partially complete. It covers the basic purpose and error handling but lacks guidance on when to use versus alternatives, authentication needs, or detailed return format beyond 'formatted string.' The absence of an output schema means the description should ideally provide more about the return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'host_id' parameter fully documented. The description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get complete detailed information about a specific host entity.' It specifies the verb ('Get'), resource ('host entity'), and scope ('complete detailed information'). However, it doesn't explicitly differentiate from sibling tools like 'lookup_host_by_ip' or 'lookup_entity_info_by_name', which appear to serve similar host/entity lookup functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'lookup_host_by_ip' (for IP-based lookup) or 'lookup_entity_info_by_name' (for name-based lookup), nor does it specify prerequisites or constraints beyond needing a host ID. The agent must infer usage from the tool name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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 mentions the return type ('JSON string with list of detections ids') but lacks critical behavioral details: whether this is a read-only operation, if it requires authentication, pagination behavior (given the 'limit' parameter), rate limits, or what happens with large result sets. For a list tool with 9 parameters, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured in three sentences: purpose, usage guidance, and return value. Each sentence adds value, with no redundant information. However, the return value statement could be integrated more smoothly, and it's slightly front-loaded but not perfectly optimized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 parameters, no annotations, but 100% schema coverage and an output schema exists), the description is minimally adequate. The output schema means the description doesn't need to explain return values in detail, but it lacks behavioral context for a list operation (e.g., pagination, limits, or error handling). It covers the basics but leaves gaps in operational transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 9 parameters with descriptions, defaults, and constraints. The description adds no parameter-specific information beyond the general mention of 'filtering options.' This meets the baseline of 3, as the schema does the heavy lifting, but the description doesn't enhance understanding of parameter interactions or semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List detections with basic information and filtering options.' It specifies the verb ('list'), resource ('detections'), and scope ('basic information'). However, it doesn't explicitly distinguish this from sibling tools like 'list_detection_ids' or 'list_detections_with_details' beyond mentioning 'quick overview without detailed information,' which is somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance: 'Use this to get a quick overview of detections without detailed information.' This suggests when to use it (for quick overviews) but doesn't explicitly state when to use alternatives like 'list_detection_ids' (for just IDs) or 'list_detections_with_details' (for detailed info). No explicit exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool lists detections with filtering and sorting, but fails to describe critical behaviors such as whether it's read-only (implied but not stated), pagination handling (limit parameter exists but not explained in description), rate limits, authentication requirements, or error conditions. This leaves significant gaps 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose in the first sentence. The second sentence adds context about returns, but the 'Returns:' section is redundant given the output schema exists. Overall, it's efficient with only minor waste, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, filtering/sorting functionality) and the presence of an output schema, the description is minimally adequate. It states the purpose and return format, but lacks behavioral context (e.g., read-only nature, pagination) and usage differentiation from siblings. With no annotations, it should provide more operational guidance to be fully complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds no specific parameter semantics beyond mentioning 'filtering and sorting options' generically. It does not explain parameter interactions, default behaviors beyond what's in the schema, or usage examples. This meets the baseline for high schema coverage but adds minimal extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'List detections with filtering and sorting options' and specifies it returns 'a detailed list of detections based on various criteria.' This distinguishes it from sibling tools like 'list_detection_ids' and 'list_detections_with_basic_info' by emphasizing detailed information and filtering capabilities. However, it doesn't explicitly contrast with these specific siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning 'filtering and sorting options' and 'various criteria,' suggesting when to use this tool for detailed, filtered lists. However, it lacks explicit guidance on when to choose this over alternatives like 'list_detection_ids' (for IDs only) or 'list_detections_with_basic_info' (for less detail), and does not specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
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 adds some context: marking as fixed closes the detection as 'remediated' (implying a status change), and it mentions potential failure with an exception. However, it lacks details on permissions needed, side effects (e.g., notifications), rate limits, or idempotency. The description doesn't contradict annotations, as there are none.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three sentences: purpose, elaboration on 'fixed', and return/error info. It's front-loaded with the core action. However, the 'Returns:' and 'Raises:' sections are somewhat redundant given the output schema, and the elaboration could be more integrated, but overall it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with two parameters), no annotations, and an output schema (which handles return values), the description is moderately complete. It covers the basic action and error handling but lacks context on when to use it, behavioral nuances, or integration with sibling tools. It's adequate but has clear gaps for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for both parameters (detection_ids and mark_fixed). The description adds no additional parameter semantics beyond what the schema provides, such as format constraints or examples. The baseline score of 3 is appropriate since the schema does the heavy lifting, but the description doesn't compensate with extra insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('marks or unmark') and resource ('detection as fixed'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from potential siblings like 'close_detection' or 'update_detection_status' that might exist in other contexts, though among the provided sibling tools, it's distinct as the only one that modifies detection status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., detection must be open to mark as fixed), exclusions (e.g., cannot mark already-fixed detections), or compare it to sibling tools like 'list_detections_with_details' for context. The agent must infer usage solely from the name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
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 adds useful context beyond basic functionality: case-insensitive partial name matching, return format details (formatted string with specific fields), and handling of no matches. However, it doesn't cover critical behavioral traits like error handling, rate limits, authentication requirements, or whether this is a read-only operation (implied but not stated).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by behavioral details and return format. Every sentence adds value—no redundant or wasted text. However, the structure could be slightly improved by separating behavioral notes from return specifications more clearly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given 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 simple single-parameter tool, the description is moderately complete. It covers purpose, search behavior, and return format adequately. However, for a tool in a security/entity management context, it lacks details on permissions, data freshness, or error scenarios, which would enhance completeness for agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'entity_name' fully documented in the schema ('Name or partial name of the entity to look up. No spaces allowed.'). The description adds minimal value beyond the schema, only reinforcing 'partial names' matching. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retrieve information about an entity (account or host) by its name' with specific verbs ('Retrieve information') and resources ('entity'). It distinguishes from siblings like 'get_account_details' or 'get_host_details' by focusing on name-based lookup rather than ID-based or other criteria. However, it doesn't explicitly contrast with 'lookup_host_by_ip' (IP-based lookup) or 'list_entities' (bulk listing), leaving some sibling differentiation incomplete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'Search is case-insensitive and can match partial names' and the return behavior, suggesting it's for fuzzy name matching. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_account_details' (for specific accounts by ID) or 'lookup_host_by_ip' (for IP-based lookups). No when-not-to-use or prerequisite information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it describes the return format (formatted string with specific fields), success case (host info), failure cases (no matches found), and error handling (raises exception). However, it doesn't mention rate limits, authentication needs, or whether the operation is read-only (though implied by 'Retrieve').
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with three focused sentences: purpose statement, success return format, and two failure scenarios. It's front-loaded with the core functionality. Minor improvement could be merging the two failure cases into one sentence for even tighter structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with full schema coverage and no output schema, the description provides good completeness: it explains what the tool does, what it returns in different scenarios, and error behavior. For a simple lookup tool, this covers essential context, though it could briefly mention read-only nature or performance characteristics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing complete documentation for the single parameter 'host_ip'. The description doesn't add any parameter-specific semantics beyond what's in the schema (e.g., no examples of valid IP formats or edge cases), so it meets the baseline for high schema coverage without extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Retrieve information') and target resource ('about a host entity by its IP address'), distinguishing it from siblings like 'get_host_details' (which likely uses different identifiers) and 'lookup_entity_info_by_name' (which uses names instead of IPs). The verb+resource combination is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the parameter specification (IP address lookup) but doesn't explicitly state when to use this tool versus alternatives like 'get_host_details' or 'lookup_entity_info_by_name'. No guidance is provided about prerequisites, error conditions beyond basic returns, or comparative advantages with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
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 mentions the tool is for deletion/unassignment and notes potential failure with 'Raises: Exception: If deleting assignment fails,' adding some context. However, it lacks details on permissions, reversibility, or side effects, which are important for a destructive operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by usage guidelines and return/error information in a structured format. Every sentence earns its place without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a destructive operation with no annotations, the description covers purpose, usage, parameters, and output/errors well. However, it could be more complete by addressing behavioral aspects like auth needs or side effects, though the output schema reduces the need to explain return values in detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the baseline is 3. The description adds value by explaining how to obtain the assignment_id ('Use list_assignments... to fetch assignment IDs'), providing practical guidance beyond the schema's technical definition, which justifies a higher score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Unassign or delete') and resource ('investigation assignment by its ID'), distinguishing it from sibling tools like list_assignments or create_assignment. It explicitly mentions what the tool does beyond just restating the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool by stating 'Use list_assignments and list_assignments_for_user to fetch assignment IDs,' indicating prerequisites and distinguishing it from alternative tools for fetching IDs. It clearly sets the context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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