n8n-workflow-tester-safe

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 'append a node JSON object', implying a write/mutation operation, but doesn't disclose critical traits: whether this requires specific permissions, if it's idempotent, what happens on failure, or the response format. For a mutation tool with zero annotation coverage, this is a significant gap 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.

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word contributes directly to understanding the tool's purpose without unnecessary elaboration.

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

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

Given the complexity (mutation with nested objects), lack of annotations, no output schema, and low parameter coverage, the description is incomplete. It doesn't address behavioral aspects, parameter details, or output expectations, making it inadequate for safe and effective use by an AI agent without additional context.

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

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

The description mentions 'node JSON object' and 'existing workflow', which loosely maps to the 'node' and 'workflowId' parameters, but with 0% schema description coverage, it adds minimal value. It doesn't explain the structure of the 'node' object, expected properties, or format for 'workflowId', leaving parameters largely undocumented beyond their names.

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

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

The description clearly states the action ('Append') and resource ('node JSON object to an existing workflow'), making the purpose understandable. It distinguishes from siblings like 'create_workflow' (creates new) and 'update_workflow' (modifies existing), though it doesn't explicitly mention these alternatives. The verb 'append' is specific but could be more detailed about what 'append' entails in this 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., workflow must exist), exclusions (e.g., not for modifying nodes), or compare to siblings like 'update_workflow' or 'connect_nodes'. Usage is implied by the action but lacks explicit context for selection.

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 'Create a main connection', implying a write operation, but lacks details on permissions, side effects (e.g., if connections are reversible), error handling, or rate limits. This is a significant gap for a mutation tool, making it only marginally transparent.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, making it easy to parse quickly, which is ideal for conciseness.

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

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

Given the complexity of a 5-parameter mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain the parameters, behavioral traits, or return values, leaving critical gaps for an AI agent to understand how to invoke and interpret the tool correctly in context.

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 0%, meaning all 5 parameters are undocumented in the schema. The description adds no information about what 'workflowId', 'source', 'target', 'sourceIndex', or 'targetIndex' mean or how they should be used. It fails to compensate for the schema's lack of descriptions, leaving parameters semantically unclear.

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

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

The description clearly states the action ('Create a main connection') and resource ('between two nodes in an existing workflow'), making the purpose understandable. However, it doesn't explicitly distinguish this from sibling tools like 'add_node_to_workflow' or 'update_workflow', which might also involve workflow modifications, 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.

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

The description provides minimal guidance by mentioning 'in an existing workflow', implying a prerequisite, but offers no explicit advice on when to use this tool versus alternatives like 'add_node_to_workflow' or 'update_workflow'. There's no mention of specific scenarios, exclusions, or comparisons with siblings, leaving usage unclear.

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

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

With no annotations, the description carries the full burden but only states the basic action without disclosing behavioral traits like permissions needed, whether the workflow is immediately active, error handling, or response format. It mentions JSON input but doesn't elaborate on structure or constraints.

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

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

The description is a single, efficient sentence with zero waste, front-loading the key action and resource appropriately. Every word earns its place.

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

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

Given the complexity (creation tool with nested object parameter, no annotations, no output schema), the description is incomplete. It lacks details on input format, behavioral expectations, and output, leaving significant gaps for an AI agent to use it correctly.

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

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

Schema description coverage is 0%, so the description must compensate but only vaguely references 'JSON' without explaining the 'workflow' object's structure, required fields, or examples. This adds minimal meaning beyond the bare schema.

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

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

The description clearly states the action ('Create') and resource ('new n8n workflow from JSON'), making the purpose unambiguous. It distinguishes from siblings like 'update_workflow' or 'delete_workflow' by specifying creation, though it doesn't explicitly contrast with 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?

No guidance is provided on when to use this tool versus alternatives like 'update_workflow' or prerequisites. The description implies usage for initial workflow creation but lacks explicit context or exclusions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is 'Delete,' implying a destructive mutation, but doesn't elaborate on critical aspects like whether deletion is permanent, requires specific permissions, triggers side effects, or returns confirmation data. This leaves significant gaps for a tool that performs a potentially irreversible operation.

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

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

The description is a single, direct sentence with zero wasted words. It front-loads the core action and resource, making it highly efficient and easy to parse, which is ideal for a simple tool like this.

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

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

Given the tool's complexity (a destructive operation with no annotations or output schema), the description is incomplete. It lacks details on behavioral traits (e.g., irreversibility, permissions), expected outcomes, or error handling, leaving the agent under-informed for safe and effective use.

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

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

The description adds minimal meaning beyond the input schema, which has 0% coverage but only one parameter ('workflowId'). It clarifies that 'workflowId' is used to identify the workflow to delete, but doesn't specify format (e.g., UUID) or sourcing (e.g., from 'get_workflow_summary'). With low schema coverage but only one parameter, the baseline is met without compensating fully.

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

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

The description clearly states the action ('Delete') and resource ('an n8n workflow by ID'), making the purpose immediately understandable. It distinguishes from siblings like 'create_workflow' or 'update_workflow' by specifying deletion, though it doesn't explicitly contrast with other destructive operations like 'remove' tools that might exist elsewhere.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing workflow ID), consequences (e.g., irreversible deletion), or when to choose deletion over archiving or other options, 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.

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 running a test and returning results, but lacks details on execution behavior (e.g., side effects, error handling, or performance implications). This is inadequate for a tool that likely involves computation and output generation.

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, efficient sentence that front-loads the core action and outcome without unnecessary words. Every part earns its place by conveying essential information in a compact form.

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

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

Given the lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It omits critical details about parameters, behavioral traits, and output structure, making it insufficient for an agent to reliably use this tool in a complex workflow environment.

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

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

Schema description coverage is 0%, so the description must compensate but fails to do so. It does not explain what 'configPath' or 'payloadName' represent, their formats, or how they relate to the test. This leaves both parameters undocumented, hindering effective tool invocation.

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

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

The description clearly states the action ('Run a single payload test') and the outcome ('return evaluation score + issues'), which is specific and actionable. It distinguishes itself from siblings like 'test_workflow' or 'run_workflow_suite' by focusing on a single test with evaluation metrics, though it doesn't explicitly name alternatives.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'test_workflow' or 'run_workflow_suite'. The description implies usage for testing but lacks context on prerequisites, scenarios, or exclusions, leaving the agent to infer based on tool names alone.

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 the tool returns counts but doesn't specify format, data freshness, permissions required, or error handling. This is inadequate for a tool that likely involves data retrieval from an external catalog.

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, efficient sentence that front-loads the core action and resources. Every word earns its place, with no redundancy or unnecessary details, making it easy to parse quickly.

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

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. However, it lacks details on return format, error cases, or integration context, which could be helpful for an agent invoking this tool.

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

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds context by mentioning the source ('imported n8n catalog'), which provides useful semantic information beyond the empty schema.

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

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

The description clearly states the verb ('Return counts') and the resources ('catalogued nodes, triggers, and credentials'), specifying what the tool does. It distinguishes itself from siblings by focusing on catalog statistics rather than workflow operations, though it doesn't explicitly name alternatives for similar counting tasks.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for accessing the imported n8n catalog, or compare it to siblings like 'list_node_types' or 'list_triggers' that might overlap in functionality.

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 'fetches' details, implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns structured data, or handles errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior beyond the basic action.

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

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

The description is extremely concise and front-loaded, consisting of a single sentence that directly states the tool's purpose. Every word earns its place, with no redundant information or unnecessary elaboration, 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.

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

Given the complexity (a read operation with one parameter) and lack of annotations and output schema, the description is incomplete. It doesn't explain what 'full execution details' include, the return format, error handling, or authentication needs. For a tool in a workflow management context with siblings like 'get_execution_trace', more context is needed to understand its role and output fully.

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

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

The description adds minimal meaning beyond the input schema. It mentions 'execution ID' as the parameter, which aligns with the schema's single 'executionId' property. However, with 0% schema description coverage, the schema provides no details about the parameter's format or constraints. The description doesn't compensate by explaining what an execution ID is, its format, or where to obtain it, leaving the parameter semantics largely undocumented.

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

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

The description clearly states the verb ('Fetch') and resource ('full execution details'), specifying it's done 'by execution ID'. It distinguishes from siblings like 'list_executions' (which lists multiple) and 'get_execution_trace' (which likely provides trace-specific details). However, it doesn't explicitly contrast with 'get_workflow_summary' or 'evaluate_workflow_result', which might also retrieve execution-related data, leaving some 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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid execution ID), exclusions (e.g., not for listing executions), or compare to siblings like 'list_executions' for multiple items or 'get_execution_trace' for trace-specific data. The description implies usage by stating 'by execution ID', but this is minimal and lacks explicit 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 burden of behavioral disclosure. It states the tool returns a 'lightweight per-node trace summary', which hints at read-only behavior and output format, but lacks details on permissions, rate limits, error handling, or what 'lightweight' entails (e.g., limited fields vs. full traces). 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.

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

The description is a single, efficient sentence that front-loads the core action ('return') and resource. There is no wasted wording, and it directly conveys the tool's function without unnecessary elaboration, making it highly concise and well-structured.

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

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

Given the tool's complexity (retrieving trace data), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover behavioral aspects like safety, output format, or error conditions, leaving significant gaps for an AI agent to understand how to use it effectively in context with 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 input schema has 1 parameter (executionId) with 0% description coverage, so the schema provides no semantic context. The description adds no parameter information beyond implying 'executionId' is needed for trace retrieval. It doesn't explain format, sourcing, or constraints. With low schema coverage, the description fails to compensate adequately, resulting in a baseline score.

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

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

The description clearly states the verb ('return') and resource ('lightweight per-node trace summary for an execution'), making the purpose understandable. It distinguishes from siblings like 'get_execution' (full execution details) and 'list_executions' (multiple executions) by specifying it returns trace summaries. However, it doesn't explicitly contrast with all siblings, keeping it at 4 rather than 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an executionId from another tool), exclusions, or comparisons to siblings like 'get_execution' or 'evaluate_workflow_result'. Without such context, users must infer usage from the name alone.

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. It states the action ('Get') but doesn't describe what 'full schema/details' includes, whether it's a read-only operation, error handling for invalid types, or response format. For a tool with no annotation coverage, this lacks critical behavioral context.

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

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes to understanding the purpose.

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

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

Given the complexity (1 parameter, no annotations, no output schema), the description is incomplete. It doesn't explain what 'full schema/details' entails, how to use the output, or error scenarios. For a tool that retrieves detailed information, more context on the return value and usage is needed to be fully helpful.

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

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

The input schema has 1 parameter with 0% description coverage, so the description must compensate. It mentions 'a specific node type' which hints at the 'nodeType' parameter's purpose, but doesn't explain what constitutes a valid node type, format examples, or where to find available types. This adds minimal semantic value beyond the schema's structure.

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

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

The description clearly states the verb ('Get') and resource ('full schema/details for a specific node type'), making the purpose understandable. It distinguishes from siblings like 'list_node_types' (which lists types) by specifying retrieval of details for a single type. However, it doesn't explicitly contrast with 'validate_node_type' or 'search_nodes', leaving some 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. It doesn't mention prerequisites (e.g., needing a valid node type name), exclusions, or comparisons to siblings like 'list_node_types' (for browsing) or 'validate_node_type' (for checking validity). Usage is implied but not explicitly defined.

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. It states 'Fetch a workflow summary,' implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, what the summary includes, or if it's cached. This 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.

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it highly concise and well-structured.

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

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

Given the complexity of fetching data, no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain what a 'workflow summary' entails, potential errors, or return format, leaving the agent with insufficient context for effective use.

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

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

The description mentions 'by workflow ID,' which aligns with the single parameter 'workflowId' in the schema. However, with 0% schema description coverage, the description doesn't add details like ID format or examples. It compensates minimally, so the baseline score of 3 is appropriate given the schema's lack of descriptions.

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

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

The description clearly states the action ('Fetch') and resource ('workflow summary from n8n by workflow ID'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_execution' or 'list_executions', which might also retrieve workflow-related data, so it doesn't reach the highest score.

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. With many sibling tools like 'get_execution' or 'list_executions' that might overlap in retrieving workflow information, there's no indication of context, prerequisites, or exclusions for usage.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only operation by using 'List', but doesn't specify permissions, rate limits, pagination behavior, or what 'recent' means (e.g., time range or default limit). This leaves significant gaps for a tool that likely interacts with execution data.

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

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

The description is a single, efficient sentence with no wasted words. It front-loads the core action ('List recent executions') and adds optional filtering details concisely, making it easy to parse and understand quickly.

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

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

Given the complexity (a list operation with filtering), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain return values, error conditions, or behavioral nuances like ordering or default behaviors, leaving the agent with insufficient context for reliable use.

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 0%, so the description must compensate but only partially does. It mentions filtering by 'workflowId and status', covering two of the three parameters, but omits 'limit' entirely and provides no details on parameter formats, constraints, or interactions (e.g., how filtering combines). This is inadequate given the low schema coverage.

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

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

The description clearly states the verb ('List') and resource ('recent executions'), making the purpose specific and understandable. It distinguishes from siblings like 'get_execution' (which retrieves a single execution) by indicating it returns multiple items, though it doesn't explicitly contrast with all similar tools like 'get_execution_trace'.

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 like 'get_execution' or 'get_execution_trace'. It mentions optional filtering but doesn't specify scenarios where filtering is appropriate or when other tools might be better suited, leaving the agent with minimal usage context.

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

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

No annotations are provided, so the description carries full burden. It states the tool lists node types but does not disclose behavioral traits such as whether it's a read-only operation, if it requires authentication, potential rate limits, or the format of the returned list. This 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.

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

The description is a single, efficient sentence with no wasted words. It is front-loaded with the core purpose ('List available node types') and includes necessary context ('from the connected n8n instance'). Every part earns its place, making it highly concise and well-structured.

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

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

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks details on behavior, usage context, or output format. For a simple list tool, this is adequate but with clear gaps, aligning with a score of 3 as the minimum viable.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description does not add parameter details, which is appropriate, but it could have mentioned the lack of parameters. Baseline for 0 parameters is 4, as it adequately handles the absence of inputs.

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

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

The description clearly states the action ('List') and resource ('available node types'), specifying the source ('from the connected n8n instance'). It distinguishes from siblings like 'get_node_type' (singular) and 'search_nodes' (search vs list), though not explicitly. However, it lacks explicit sibling differentiation, preventing 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.

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

No guidance is provided on when to use this tool versus alternatives like 'get_node_type' (for a specific type) or 'search_nodes' (for filtered results). The description implies usage for listing all types but offers no context on prerequisites, exclusions, or comparisons to sibling tools.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists trigger nodes but doesn't describe what a 'trigger node' entails, how the listing is formatted (e.g., pagination, sorting), or any behavioral traits like permissions needed, rate limits, or whether it's a read-only operation. This 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.

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

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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

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

Given the complexity (listing operation with no parameters) and lack of annotations and output schema, the description is incomplete. It doesn't explain what 'trigger nodes' are, how they relate to the n8n catalog, or what the return values look like, leaving the agent with insufficient context to use the tool effectively.

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

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

The input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details since there are none, which is appropriate. Baseline is 4 for 0 parameters, as the description doesn't need to compensate for any schema gaps.

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

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

The description clearly states the action ('List') and the resource ('trigger nodes from the imported n8n catalog'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate this tool from sibling tools like 'list_executions' or 'list_node_types', which also list different types of catalog items, so it doesn't fully distinguish from siblings.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'list_triggers' over other listing tools like 'list_node_types' or 'search_nodes', nor does it specify any prerequisites or exclusions for usage, leaving the agent without contextual direction.

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

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

With no annotations, the description carries full burden but only states the basic action and output. It doesn't disclose critical behavioral traits such as whether this is a read-only or destructive operation, authentication needs, rate limits, or execution details (e.g., synchronous/asynchronous).

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, efficient sentence that front-loads the core action and outcome with zero waste. It's appropriately sized for the tool's apparent 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, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on parameters, behavioral context, and output structure, making it inadequate for a tool that likely involves complex execution.

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

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

Schema description coverage is 0%, and the description adds no meaning beyond the schema. It doesn't explain what 'configPath' represents (e.g., file path, identifier) or its format, leaving the single parameter undocumented.

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

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

The description clearly states the action ('Run all payloads') and resource ('workflow config'), specifying it processes multiple payloads and returns results with scores. However, it doesn't differentiate from siblings like 'test_workflow' or 'evaluate_workflow_result', which might have overlapping purposes.

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

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

No guidance is provided on when to use this tool versus alternatives like 'test_workflow' or 'evaluate_workflow_result'. The description implies usage for batch processing but lacks explicit context, prerequisites, or exclusions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the search function but doesn't describe the return format (e.g., list of nodes with details), pagination behavior, error conditions, or performance characteristics. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a search tool and front-loads the key information.

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

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

Given the complexity of a search operation, no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't explain what the search returns, how results are structured, or the semantics of the 'onlyTriggers' parameter, leaving the agent with insufficient context to use the tool effectively.

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

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

The schema description coverage is 0%, meaning neither parameter ('query' and 'onlyTriggers') is documented in the schema. The description only mentions 'by name', which partially explains the 'query' parameter but doesn't clarify its format (e.g., exact match vs. substring) or the purpose of 'onlyTriggers'. This fails to compensate for the schema's lack of documentation.

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

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

The description clearly states the action ('Search') and resource ('nodes from the imported n8n catalog'), with the specific scope 'by name' distinguishing it from potential sibling tools like 'suggest_nodes_for_task' or 'list_node_types'. However, it doesn't explicitly differentiate from 'get_node_type' which might retrieve a single node by ID rather than searching by name.

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 like 'suggest_nodes_for_task' (for task-based suggestions) or 'list_node_types' (for unfiltered listing). There's no mention of prerequisites (e.g., needing an imported catalog) or exclusions (e.g., not for workflow execution).

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. It states the tool suggests nodes but does not explain how suggestions are generated, if there are rate limits, authentication needs, or what the output format looks like. 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.

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and every part earns its place, making it highly concise and well-structured.

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

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

Given the tool's complexity (suggesting nodes based on natural language), lack of annotations, no output schema, and low schema coverage, the description is insufficient. It does not explain how suggestions are made, what the output includes, or any behavioral traits, leaving the agent with inadequate information for effective use.

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

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

The input schema has one parameter ('task') with 0% description coverage. The description adds meaning by specifying it's a 'natural-language task', which clarifies the parameter's purpose beyond the schema. However, it does not provide examples or constraints, so it partially compensates but not fully, aligning with the baseline for moderate coverage.

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

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

The description clearly states the tool's purpose: 'Suggest relevant n8n nodes from the imported catalog for a natural-language task.' It specifies the verb ('suggest'), resource ('n8n nodes'), and scope ('from the imported catalog'), but does not explicitly differentiate it from sibling tools like 'search_nodes' or 'list_node_types', which prevents a score of 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention when to prefer it over 'search_nodes' or 'list_node_types', nor does it specify prerequisites like needing an imported catalog. Without any usage context or exclusions, it scores low.

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 the tool runs a test, implying execution and potential side effects, but does not detail outcomes, error handling, or performance aspects like rate limits. This is inadequate for a tool that likely performs operations with consequences.

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, efficient sentence that directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

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

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

Given the complexity of running tests, no annotations, no output schema, and low parameter coverage, the description is incomplete. It does not cover return values, error cases, or behavioral nuances, leaving significant gaps for the agent to infer usage in a workflow context.

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

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

Schema description coverage is 0%, so the schema provides no parameter details. The description mentions 'configPath' and 'payloadName' implicitly but does not explain their meanings, formats, or examples. It adds minimal value beyond naming the parameters, failing to compensate for the lack of schema documentation.

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

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

The description clearly states the action ('Run') and the resource ('a single payload test from a workflow config JSON file'), making the purpose understandable. However, it does not explicitly differentiate this tool from sibling tools like 'run_workflow_suite' or 'evaluate_workflow_result', which might involve similar testing or evaluation functions, so it 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.

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing a valid config file or payload, or compare it to siblings like 'run_workflow_suite' for broader testing. This leaves the agent with minimal context for tool selection.

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 'Replace an existing n8n workflow,' implying a mutation operation, but lacks critical details: it doesn't specify if this is destructive (overwrites the entire workflow), requires authentication, has rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap 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.

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

The description is a single, efficient sentence with zero waste—it directly states the tool's action and key parameters. It's appropriately sized and front-loaded, making it easy to parse quickly without unnecessary elaboration.

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

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

Given the complexity (mutation tool with nested objects), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks essential context: behavioral traits (e.g., destructiveness), parameter details, error handling, and output expectations. For a tool that replaces workflows, this leaves too many unknowns for effective use.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'workflowId' and 'workflow' (JSON), but adds minimal semantic value: it doesn't explain the format of 'workflowId' (e.g., string identifier) or the structure of the 'workflow' object (e.g., JSON schema for n8n workflows). With 2 parameters and low coverage, this is inadequate.

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

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

The description clearly states the action ('Replace') and resource ('existing n8n workflow by ID with JSON'), making the purpose understandable. It distinguishes from siblings like 'create_workflow' (new vs. replace) and 'delete_workflow' (replace vs. remove), though it doesn't explicitly name them. However, it lacks specificity about what 'replace' entails (e.g., full overwrite vs. partial update).

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing workflow ID), exclusions (e.g., not for partial updates), or refer to sibling tools like 'create_workflow' for new workflows or 'delete_workflow' for removal, 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.

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

With no annotations, the description carries full burden but lacks behavioral details. It mentions validation and suggestions, but doesn't disclose error handling (e.g., invalid inputs), performance traits (e.g., response time), or side effects (e.g., if it modifies data). This is a significant gap for a 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.

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. Every word contributes directly to explaining the tool's function, making it appropriately sized and well-structured.

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

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

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It covers the basic purpose but lacks details on parameters, return values (e.g., validation results or match lists), and behavioral context, which are essential for effective tool use by an agent.

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

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

Schema description coverage is 0%, so the description must compensate but adds minimal parameter insight. It implies 'nodeType' is validated against a catalog, but doesn't explain format expectations (e.g., string patterns), examples, or how suggestions are generated, failing to address the undocumented parameter adequately.

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

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

The description clearly states the action ('validate') and target ('node type'), specifying it checks against the 'imported n8n catalog' and provides 'suggest close matches'. It distinguishes from siblings like 'get_node_type' (which likely retrieves details) by focusing on validation and suggestions, though it doesn't explicitly name alternatives.

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

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

No explicit guidance on when to use this tool versus alternatives is provided. The description implies usage for validating node types, but it doesn't specify prerequisites (e.g., after importing a catalog) or contrast with siblings like 'search_nodes' or 'suggest_nodes_for_task', leaving the agent to infer context.

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