Flowise MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
The four create_prediction variants are closely related but have distinct, clearly described purposes (base, with history, with files, with lead). Chatflow management and node exploration tools are clearly separated. The main ambiguity is choosing among the prediction variants, but context usually resolves it.
Naming Consistency5/5
All tools follow a consistent snake_case verb_noun pattern. List/get for retrieval, create/update/delete for chatflow operations, and create_prediction for execution. Modifiers like with_history, with_files, and with_lead are appended consistently.
Tool Count5/5
With 12 tools, the server is well-scoped. It covers chatflow CRUD, multiple prediction modes, and node catalog exploration without unnecessary bloat. Each tool serves a clear purpose in the Flowise domain.
Completeness4/5
The tool set provides full lifecycle coverage for chatflows (create, read, update, delete) and a good range of prediction options. It also exposes node catalog information. Minor gaps like lead management or prediction history are not core to the Flowise workflow and can be worked around.
Average 3.6/5 across 12 of 12 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No high-severity vulnerability alerts
- No code scanning findings
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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 bears full responsibility for disclosing behavioral traits. It only states that it creates a chatflow, omitting information about authentication requirements, whether the tool overwrites existing flows, error handling, or the structure of the response. The description adds no concrete behavioral context 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately conveys the core action and subject. There is no filler or redundant information. It is appropriately short and front-loaded, aligning with conciseness best practices.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with four parameters, nested objects, no annotations, and no output schema, the description is notably underspecified. It doesn't explain what the user should expect in a successful response, how to structure flowData correctly, or mention related tools like list_nodes for node definitions. The description covers only the bare minimum, leaving significant gaps for a new user.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema documents all parameters with descriptions, achieving 100% coverage. The description's mention of 'nodes and edges configuration' adds slight contextual reinforcement for flowData, but overall it contributes little beyond the schema. The baseline of 3 is appropriate because the schema carries the semantic load.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Create') and clearly identifies the resource ('a new chatflow in Flowise') along with the key configuration aspect ('nodes and edges'). This distinguishes it from list/get/update/delete operations, though it doesn't explicitly differentiate from the create_prediction siblings. The purpose is clear 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 Guidelines2/5
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 update_chatflow or create_prediction. It doesn't mention prerequisites, typical scenarios, or exclusions. Users must infer its 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states that a chatflow is run and a response is returned, with no details on side effects, authentication requirements, rate limits, or output format. This is insufficient for the agent to anticipate consequences beyond the obvious request-response.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, front-loaded with the core action and object. No unnecessary words or repetition, making it an efficient and lean description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has four parameters including a nested overrideConfig and no output schema, yet the description offers no information about return structure, error behavior, or side effects. It also fails to contextualize how this base version relates to the three specialized prediction tools. Given the complexity and lack of annotations, the description leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides detailed descriptions for all four parameters, achieving 100% coverage. The description adds no additional semantic information about parameter usage or relationships. Baseline 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a Flowise chatflow with a question and returns a response, using a specific verb and resource. It distinguishes this as the generic chatflow interaction tool, but doesn't explicitly differentiate from specialized siblings like create_prediction_with_history or create_prediction_with_files.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this to interact with AI workflows configured in Flowise,' providing general context for when to use the tool. It lacks any guidance on when to choose this over the sibling variants (with_history, with_files, with_lead) or when not to use it, leaving usage implied rather than explicitly delineated.
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 simply states that it gets information, but does not mention whether the node must exist, how errors are handled, whether any permissions are required, or what constitutes 'detailed information.' The read-only nature is implied by 'Get,' but not explicitly stated, and no other behavioral traits are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that directly states the purpose. It is front-loaded with the verb and resource, contains no filler, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description is too sparse. It does not explain what the response contains, what happens if the node name is invalid, or how the result relates to sibling tools. The tool is simple, but a bit more context about the return value or typical use would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the single parameter nodeName, including an example. The description adds 'by its name,' which just reiterates the schema. Since schema description coverage is 100%, the baseline of 3 applies; the description does not meaningfully enhance the parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: retrieving detailed information about a specific node type by name. The verb 'Get' plus the resource 'specific node type' makes the purpose unambiguous, and it distinguishes itself from sibling tools like list_nodes and get_nodes_by_category by focusing on a single named node.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It doesn't mention that list_nodes can be used to discover available node names or that get_nodes_by_category is the appropriate tool when filtering by category. There is no explicit when-to-use or when-not-to-use guidance.
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, the description must disclose side effects, permissions, or operational traits, but it only says 'Run'. The tool name suggests it creates a prediction, yet the description does not reveal whether this is a mutating operation, what happens to uploaded files, or any required auth/rate limits. This is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action, and every word adds value. It is appropriately concise with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, nested upload object, no output schema) and absence of annotations, the description is under-specified. It does not mention expected return behavior, error scenarios, or prerequisite conditions like base64 encoding of file data. The description leaves too much for the agent to infer without additional guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all five parameters, so the baseline is 3. The description's mention of 'file attachments' adds a small element of clarity regarding the 'uploads' parameter but provides no additional meaning for chatflowId, question, chatId, or overrideConfig.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Run') and resource ('Flowise chatflow'), and the phrase 'with file attachments' distinctly separates it from sibling tools like create_prediction. It is specific and understandable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for use when file attachments are required, but it does not explicitly state when to prefer this over create_prediction_with_history or create_prediction_with_lead, nor does it mention any exclusion criteria. No alternatives are named.
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 responsibility for disclosing behavioral traits. It only says 'Run a Flowise chatflow with conversation history' but fails to mention whether a prediction record is created, any side effects, authentication requirements, or what the response looks like. This is a black-box description for a potentially mutating operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no filler, front-loading the verb and resource while highlighting the key differentiator (history). Every word earns its place, making it concise and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, nested objects, and no output schema or annotations, the description is far too brief. It omits critical context such as return values, prerequisites (e.g., chatflow must exist), and how the conversation history is processed, leaving significant gaps for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides descriptions for all 5 parameters, so the schema alone offers high coverage. The description adds minimal value beyond the schema, only linking 'conversation history' to the history parameter without extra detail on how it is used or formatted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Run'), the resource ('Flowise chatflow'), and the distinguishing feature ('with conversation history'), which differentiates it from siblings like create_prediction and create_prediction_with_files. The scope is specific 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when conversation history is needed, but it does not explicitly guide the agent on when to choose this tool over its alternatives (e.g., create_prediction without history, or create_prediction_with_files). No exclusions or alternative tools are named, leaving the agent to infer the context.
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 'run' and 'capture' but does not explain side effects (e.g., what prediction record is created, whether data persists), permissions, return value, or what 'capture' concretely does. This is a significant gap for a tool that likely mutates state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 11 words, front-loaded with the action. Every word is purposeful and there is no fluff. It is appropriately concise for a tool whose parameters are well-documented in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 parameters, no annotations, no output schema, and several sibling tools. The description is too minimal to be complete: it doesn't clarify what a 'prediction' means, what happens with the lead email, whether chatId is needed for context, or what the response contains. The schema covers parameters but not the broader usage context or behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all parameters, so the baseline is 3. The description adds no extra meaning beyond the schema; for example, 'capture a lead email' reflects the leadEmail parameter but does not elaborate on how it's used or any constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Run a Flowise chatflow and capture a lead email for the conversation.' This includes a specific verb+resource and explicitly distinguishes from sibling tools like create_prediction or create_prediction_with_history by highlighting the lead email capture.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when running a chatflow while needing to capture a lead email, but it does not explicitly mention alternatives or exclusions. Given the sibling tools, there is no direct guidance on when to choose this over create_prediction or other variants.
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. It adds the critical warning 'This action is irreversible', which is valuable. However, it does not disclose permissions, cascading effects, or error behavior, leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the action and target. The second sentence adds a meaningful warning without fluff. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, no output schema), the description covers the core purpose and key caveat of irreversibility. It lacks return/error details, but those are less critical for a delete operation and the schema covers the input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter chatflowId is described as 'The ID of the chatflow to delete'. The description adds no additional meaning beyond the schema, matching the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the specific verb 'Delete' and resource 'chatflow from Flowise', making it unmistakable. It also implicitly differentiates from siblings like create_chatflow, update_chatflow, and get_chatflow by focusing on deletion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention that this should be used only when permanent removal is intended, nor does it contrast with update_chatflow or get_chatflow.
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, the description must convey behavioral details. It does not mention whether the update is partial or full replacement, required permissions, return values, or side effects. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the action and scope. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite complete parameter descriptions in the schema, the tool lacks annotations and an output schema. The description does not clarify whether the update returns the updated chatflow, how partial updates are handled, or what errors may occur. This leaves the tool inadequately specified for agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides descriptions for all four parameters (100% coverage), so the baseline is 3. The tool description adds no additional meaning beyond the schema, and it even mentions 'metadata' which has no explicit parameter, causing slight ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Update') and resource ('existing chatflow') and lists the scopes (configuration, nodes, edges, or metadata). This clearly distinguishes it from sibling tools like get_chatflow, create_chatflow, and delete_chatflow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'existing chatflow' clearly indicates the tool is for modifying already-created chatflows, implying that creation is handled by create_chatflow. However, it does not explicitly mention alternatives or exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations provided, so the description carries the full burden. It transparently indicates a read-only operation ('Get'), but does not disclose any behavioral details such as pagination, ordering, or potential limitations. For a simple retrieval tool this is adequate, but it adds no extra context beyond the operation itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the action and object, and includes practical examples. Every word earns its place, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no annotations and no output schema, the description sufficiently explains what it does. However, it does not specify the return format or any pagination behavior, which would have been helpful, but is not critical for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the 'category' parameter with examples. The description repeats these examples but does not add any new semantics beyond what the schema provides. With 100% schema description coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('nodes') with a clear scope ('by category'), and includes examples of valid categories. This distinguishes it from siblings like list_nodes (all nodes) and get_node (single node), making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving nodes filtered by category, but does not explicitly state when to prefer this over list_nodes or get_node, nor does it mention alternatives. The context is clear enough, but lacks explicit exclusions or alternative tool references.
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?
No annotations are provided, so the description carries the burden. It indicates a read-only action ('List') but does not disclose return format, potential filtering options, or whether the list is complete or paginated. Minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that is perfectly concise. Every word adds value, and there is no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple list tool with no parameters, annotations, or output schema. The description covers the core purpose and implies the return value (a list of node types). It could mention alternatives or return structure, but is adequate for this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description naturally cannot add parameter details. Per the rubric, 0 parameters receives a baseline of 4, and the description is not expected to compensate for missing schema info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('available node types in Flowise'), clearly distinguishing it from siblings like list_chatflows. It also clarifies that these nodes are for building chatflows, adding useful context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage as a way to get all node types, but does not explicitly mention alternatives such as get_nodes_by_category or get_node. There is no guidance on when to use this tool instead of a more specific one.
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, the description carries the burden of disclosing behavior. It mentions that the output includes the full configuration with nodes and edges, providing some return-value transparency. However, it does not state whether the operation is read-only, what happens if the ID is not found, or any permission prerequisites. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant phrases. Every word adds meaning: 'specific ... by ID' narrows to a single resource, and 'full configuration with nodes and edges' clarifies the return content. Ideal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter retrieval tool with no output schema, the description sufficiently explains the input (chatflowId) and the expected output (full configuration with nodes and edges). It is complete enough for an agent to invoke correctly without needing additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema fully describes the chatflowId parameter. The description merely echoes 'by ID' and does not add new meaning to the parameter beyond what the schema already provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with a clear resource ('a specific chatflow by ID') and adds scope ('including its full configuration with nodes and edges'). This distinguishes it from sibling list_chatflows, which retrieves a collection, and from create/update/delete operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the appropriate use case: retrieving a single chatflow's full configuration when the ID is known. This contextively contrasts with list_chatflows, but it does not explicitly state when not to use it or name alternatives. Clear context with no exclusions earns a 4.
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, the description carries the full burden. It describes the return format (IDs, names, metadata) and scopes to 'all', implying a read-only operation. This is transparent enough for a simple list tool, though it could mention any pagination or absence of filtering.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences that each add necessary information: what the tool does and what it returns. No waste, no repetition, and front-loaded with the verb.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with no output schema or annotations, this description covers the essential aspects: the action, the resource, and the returned fields. Minor gaps like possible response size or ordering do not significantly reduce completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the baseline of 4 applies per the rubric. The description adds no parameter-specific detail, and none is needed given the zero-parameter schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' with a clear resource ('chatflows') and scope ('all'), making it immediately distinguishable from sibling tools like get_chatflow. It also states the returned data (IDs, names, metadata), which fully clarifies the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'List all chatflows' clearly implies use when the agent needs the complete set, as opposed to get_chatflow for an individual item. However, it does not explicitly mention alternatives or when-not-to-use, so it does not fully meet the 5-level criterion.
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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