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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Crea' implies a write operation, it doesn't specify permissions needed, whether creation is idempotent, error conditions, or what happens on success. This is inadequate for a mutation tool with zero annotation coverage.

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

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 and front-loaded with the core action.

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

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

For a creation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what constitutes a valid flow, what the response looks like, or error handling. Given the complexity of creating workflow objects, more context is needed.

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

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

Schema description coverage is 100%, so all parameters are documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema, meeting the baseline score when schema does the heavy lifting.

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

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

The description clearly states the action ('Crea un nuevo flujo de trabajo') and resource ('en HiveFlow'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'execute_flow' or 'pause_flow' beyond the creation aspect, which prevents a perfect score.

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

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, when not to use it, or how it relates to sibling tools like 'list_flows' or 'get_flow', leaving the agent to infer 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'registra' implies a write/mutation operation, the description doesn't disclose what permissions are needed, whether this operation is idempotent, what happens if a server with the same name exists, or what the expected response format is. For a mutation tool with zero annotation coverage, this represents significant gaps in behavioral 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 that gets straight to the point with zero wasted words. It's appropriately sized for the tool's function and front-loads the essential 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?

For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after registration, what gets returned, error conditions, or how this operation fits into the broader MCP server lifecycle. Given the complexity of registering a new server and the lack of structured output information, the description should provide more context about the operation's consequences and results.

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

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

With 100% schema description coverage, the input schema already documents all 4 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

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

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

The description clearly states the action ('Registra' - registers) and the resource ('un nuevo servidor MCP en HiveFlow'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from sibling tools like 'create_flow' or 'list_mcp_servers' in terms of what makes this registration operation unique.

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 'list_mcp_servers' or other creation tools. There's no mention of prerequisites, appropriate contexts, or exclusions for this registration operation.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Ejecuta' implies a write/mutation operation, but the description doesn't reveal whether this is synchronous/asynchronous, what permissions are needed, whether it's idempotent, what happens on failure, or any rate limits. It provides minimal 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.

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

The description is a single, efficient Spanish sentence with zero wasted words. It's appropriately sized and front-loaded with the core action. Every word earns its place in conveying the basic purpose.

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

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

For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what execution means, what the expected outcome is, error conditions, or how this interacts with sibling tools. Given the complexity implied by 'execute' and lack of structured behavioral data, more context is needed.

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

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

Schema description coverage is 100%, so the schema already documents both parameters (flowId and inputs) adequately. The description adds no additional parameter semantics beyond what's in the schema. Baseline 3 is appropriate when the schema does the heavy lifting for parameter 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 'Ejecuta un flujo de trabajo específico' clearly states the action (execute) and resource (workflow), but it's vague about what execution entails and doesn't differentiate from sibling tools like pause_flow or resume_flow. It provides basic purpose but lacks specificity about what 'execute' means 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?

No guidance is provided about when to use this tool versus alternatives like pause_flow, resume_flow, or get_flow_executions. The description doesn't mention prerequisites (e.g., needing an existing flow), exclusions, or contextual factors that would help an agent choose appropriately among siblings.

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 'gets details' but doesn't describe what those details include (e.g., metadata, status, configuration), whether it's a read-only operation, potential errors (e.g., invalid flowId), or response format. 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's front-loaded with the core action ('Obtiene detalles') and resource, making it easy to parse. Every part of the sentence earns its place by conveying essential information concisely.

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 read operation with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'detalles' entail, potential outputs, or error conditions. For a tool that likely returns structured data about flows, more context is needed to help an agent use it effectively beyond just knowing it retrieves details.

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

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

The schema description coverage is 100%, with the single parameter 'flowId' documented as 'ID del flujo'. The description adds no additional meaning beyond this, such as format examples (e.g., UUID) or where to obtain the ID. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema adequately handles parameter semantics without extra description.

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

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

The description clearly states the verb 'obtiene' (gets) and the resource 'detalles de un flujo específico' (details of a specific flow), which directly communicates what the tool does. It distinguishes itself from siblings like list_flows (which lists multiple flows) by focusing on a single flow. However, it doesn't explicitly mention the resource type (e.g., workflow, data flow) beyond 'flujo', which keeps it from being fully specific.

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 flowId), exclusions, or comparisons to siblings like get_flow_executions (which might retrieve execution details) or list_flows (for browsing flows). Without such context, an agent must infer usage from the tool name and schema 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 retrieves history, implying it's a read-only operation, but doesn't confirm this or describe other traits like rate limits, authentication needs, error conditions, or what the output looks like (e.g., list format, pagination). 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 in Spanish that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool, though it could be slightly more informative without losing conciseness. No structural issues are present.

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 moderate complexity (retrieving execution history with parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, usage context, or output details, leaving significant gaps for an AI agent to understand how to invoke and interpret results 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 100% description coverage, with clear documentation for both parameters ('flowId' and 'limit' with a default). The description doesn't add any meaning beyond the schema—it doesn't explain parameter interactions, valid formats for 'flowId', or how 'limit' affects results. Given the high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.

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

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

The description clearly states the action ('Obtiene el historial de ejecuciones') and resource ('de un flujo'), which translates to 'Gets the execution history of a flow'. It specifies what the tool does without being tautological. However, it doesn't explicitly differentiate from sibling tools like 'get_flow' or 'execute_flow', which prevents a perfect score.

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

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 this over 'get_flow' (which might retrieve flow metadata) or 'execute_flow' (which might trigger a new execution), nor does it specify prerequisites like needing an existing flow ID. This lack of contextual guidance limits its utility for an AI agent.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'list' implies a read operation, it doesn't specify whether this requires authentication, what permissions are needed, whether results are paginated (beyond the optional limit parameter), or what format the output takes. For a listing tool with zero annotation coverage, this is insufficient 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 in Spanish that directly states the tool's purpose. There's no wasted verbiage or unnecessary elaboration. While it could be more specific about scope, it's appropriately concise for a basic listing tool description.

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

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

For a listing tool with 2 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'all workflows' means in context, doesn't mention authentication requirements, doesn't describe output format, and provides no guidance on when to use this versus sibling tools. The description should do more to compensate for the lack of structured metadata.

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 no parameters at all. However, with 100% schema description coverage, both parameters ('status' and 'limit') are well-documented in the schema with descriptions and enum values. The baseline score of 3 is appropriate when the schema does the heavy lifting, though the description adds no additional parameter context beyond what's already in the structured 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 states 'Lista todos los flujos de trabajo del usuario' which translates to 'Lists all user workflows'. This clearly identifies the verb ('list') and resource ('workflows'), but it's vague about scope - 'all' could mean all workflows in the system or just the current user's workflows. It doesn't distinguish this tool from sibling tools like 'get_flow' or 'get_flow_executions'.

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 siblings like 'get_flow' (for individual workflows), 'get_flow_executions' (for execution history), and 'list_mcp_servers' (for server listing), there's no indication of when this bulk listing tool is preferred over more specific queries. No usage context or exclusions are mentioned.

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

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

No annotations are provided, so the description carries the full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose any behavioral traits such as pagination, sorting, rate limits, authentication needs, or what happens if no servers are configured. For a 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 in Spanish that directly states the tool's purpose without any waste. It's appropriately sized and front-loaded, with every word contributing to clarity. No unnecessary details or redundancy are present.

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 minimal. It states what the tool does but lacks completeness: no output format, no behavioral context (e.g., list format, error handling), and no usage guidelines. For even a simple list tool, this leaves gaps in understanding how to effectively use it.

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 with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't add parameter information beyond this, but with no parameters, a baseline of 4 is appropriate as there's nothing to compensate for. No value is added, but none is needed.

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 ('Lista los servidores MCP') and resource ('configurados en HiveFlow'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'list_flows' or 'get_flow', which also list resources but different types. The purpose is clear but lacks sibling differentiation.

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

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention any context, prerequisites, or exclusions. With sibling tools like 'get_mcp_server' (implied but not listed) potentially existing, there's no indication of when to list all servers versus retrieve a specific one.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('pausa') but doesn't explain what 'pausa' entails (e.g., does it stop execution immediately, save state, require permissions, or have side effects?). 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 ('Pausa un flujo activo') that directly states the tool's purpose. It is front-loaded with no unnecessary words, making it easy for an AI agent to parse quickly. Every word earns its place, achieving optimal conciseness.

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

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

Given the tool's complexity (a mutation operation on flows), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like effects, permissions, or error conditions, nor does it explain return values. For a tool that modifies state, this leaves critical gaps for an AI agent to understand its full 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 input schema has 100% description coverage, with 'flowId' documented as 'ID del flujo a pausar'. The description doesn't add any meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting for parameter 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 'Pausa un flujo activo' clearly states the action (pausa/pause) and the target resource (un flujo activo/an active flow). It distinguishes from siblings like 'resume_flow' by specifying the opposite action. However, it doesn't explicitly differentiate from other flow management tools beyond the verb, keeping it from 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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., the flow must be active), exclusions (e.g., cannot pause a non-existent flow), or when to choose this over other flow-related tools like 'execute_flow' or 'resume_flow'. This lack of context reduces its utility for an AI agent.

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 resumes a paused flow but doesn't disclose any behavioral traits such as permissions required, side effects, error conditions, or what happens if the flow isn't paused. This is a significant gap for a mutation tool with zero annotation coverage.

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

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

The description is a single, efficient sentence in Spanish 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 tool's complexity (a mutation operation to resume flows), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what happens upon resumption, potential errors, or return values. For a tool with behavioral implications, more context is needed to guide the agent 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 100% description coverage, with the single parameter 'flowId' documented as 'ID del flujo a reanudar'. The description doesn't add any additional meaning beyond this, such as format examples or constraints. Since schema coverage is high, the baseline score of 3 is appropriate, as the schema does the heavy lifting.

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

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

The description 'Reanuda un flujo pausado' clearly states the action (reanudar/resume) and target resource (flujo/flow). It distinguishes from siblings like pause_flow, execute_flow, and get_flow by specifying it resumes paused flows. However, it doesn't explicitly mention it's for paused flows only versus other states, which slightly reduces specificity.

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 execute_flow or create_flow. It doesn't mention prerequisites (e.g., the flow must be paused) or exclusions. The context is implied but not explicit, leaving the agent to infer usage from the name and description alone.

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