el-buen-agente-mcp

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

With no annotations provided, the description carries the full burden. It discloses that the tool receives an agent definition and returns a structured evaluation brief, and that it applies data-based counterarguments and self-criticism. This adequately describes the non-destructive, analytical behavior without side effects.

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 two sentences long, front-loaded with the main purpose, and contains no unnecessary words. Every sentence adds essential information: what it does, when to use, and what it produces.

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 has two parameters, no output schema, and no annotations, the description covers the necessary inputs and high-level output ('brief de evaluación estructurado'). It could be more specific about the output structure, but it is sufficient for a tool of this complexity.

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

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

Schema coverage is 100%, and the description adds value beyond the schema by advising 'Cuanto más completa, mejor la evaluación,' which gives the agent practical guidance on parameter usage. The language parameter is also clearly explained with enum options.

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 applies the challenger/red-team pattern to agent definitions or decisions, specifying it produces structured counterarguments, self-criticism, and a quality gate. It distinguishes itself from siblings like 'challenger_decision' by mentioning it's useful as a second adversarial pass, implying a distinct use case.

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 explicitly states 'Útil como segunda pasada adversarial,' providing clear context for when to use the tool. However, it does not explicitly state when not to use it or list alternative tools, relying on implication from the sibling set.

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 provided, so description entirely responsible for behavioral disclosure. It states the tool 'audits' and 'returns a brief' but does not explicitly confirm it is read-only (non-destructive) or specify any write operations. The lack of clarity on side effects reduces 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?

Description is a single coherent paragraph, front-loaded with the core purpose, and covers most aspects without extraneous detail. Slightly verbose but still concise for the scope.

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 output schema, the description should explain return structure. It only says 'brief de evaluación estructurado', which is vague. Complex audit tool with multiple axes (3 layers, governance, etc.) would benefit from listing expected output sections. Adequate but not complete.

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

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

Schema coverage is 100%, so baseline is 3. Description briefly mentions 'agent_definition' as the input but adds no extra detail beyond the schema (e.g., no example values, format hints, or constraints). The 'language' parameter is also absent from 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?

Description clearly states the tool audits agent context across specific dimensions (3 layers, relevance, integration, etc.) with a clear verb ('audita') and resource ('contexto del agente'). However, it does not distinguish from sibling audit tools like 'evaluar_sistema' or 'revisar_rol_y_frontera', which may overlap in purpose.

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

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

No guidance on when to use this tool versus siblings. Does not specify prerequisites, expected input format beyond 'definición completa', or when not to use it. The context of the sibling tools list (e.g., 'evaluar_autonomia', 'recomendar_flujo') is not leveraged to set boundaries.

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. It discloses that the tool does not block but informs, and generates three reasons. It lacks details on authentication, rate limits, or side effects, which would be expected for a tool without annotations. Still, the core behavior is 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 two concise sentences. The first front-loads the core purpose and output, the second adds a key behavioral constraint. No wasted words.

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?

Despite no output schema, the description sufficiently explains the output (3 reasons). For a simple tool with 3 parameters and low complexity, it covers the main usage. Missing details like read-only nature or output format, but adequate.

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

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

Schema coverage is 100%, so the schema already describes all three parameters. The description does not add extra meaning beyond what the schema provides (e.g., clarifying formats or defaults). The baseline of 3 is appropriate as the description adds no parameter-specific value.

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 that the tool generates a brief to challenge a specific agent decision with three data-driven reasons against it. It distinguishes itself by specifying it doesn't block but informs, setting it apart from siblings like 'aplicar_challenger' which likely takes action.

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 explains when to use the tool (to challenge a decision) and what it does not do ('no bloquea, informa al humano'). However, it doesn't explicitly mention when not to use it or provide alternatives, though the context of sibling tools implies a complementary tool.

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 weight. It discloses that the tool is a hard gate (strict compliance required before merge, not after), returns a point-by-point verdict, and is evaluative rather than destructive. This adds valuable behavioral context beyond the schema.

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?

Two sentences with no wasted words. The first sentence front-loads the main action, the second adds critical timing and outcome. Efficient 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 output schema, the description conveys the key points: action, timing, and return type (point-by-point verdict). It lacks details on the verdict format (e.g., pass/fail per point) but is largely complete for a tool with simple parameters and clear purpose.

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

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

Schema coverage is 100% (2 parameters fully described). The description does not add semantic meaning beyond the schema—'agent_definition' is mentioned but schema already explains it. Baseline 3 applies.

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

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

The description clearly states the tool runs a 19-point checklist against an agent definition, explicitly calling it the 'gate final' before merging, which distinguishes it from sibling tools like 'validar_veredicto' and 'construir_agente'.

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 specifies this is the final step before merge, giving clear timing context. It does not explicitly mention alternatives or when not to use, but the role as final gate is enough for an agent to understand its placement.

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 discloses the transformation (takes iterated definition, produces final artifact) and lists output components, but does not detail side effects, state changes, or dependencies beyond the input parameters.

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?

Two sentences: first defines purpose and deliverable, second gives usage condition. No redundancy, every word earns its place. Front-loaded with 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?

For a tool with no output schema, the description lists output components (identity, tools, etc.) but lacks explicit return structure or error conditions. However, given the parameter count (4) and clear usage context, it is sufficiently complete for an agent to decide when and how to invoke.

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 covers all 4 parameters with descriptions (100% coverage). The description only vaguely references the core parameter ('toma la definición iterada') without adding new semantics beyond what the schema already provides.

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 it is the 'CIERRE' step that produces the final artifact after iterations, listing specific components (identity layer, tools, limits, etc.). It references a specific sibling (checklist_nacimiento) to indicate precondition, distinguishing it from other steps.

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?

Explicitly says 'Llamala cuando checklist_nacimiento dé APTO', providing a clear trigger. While it doesn't enumerate when NOT to use it, the precondition is well-defined and the context of being the closing step implies exclusivity.

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 responsibility. It lacks disclosure of side effects (e.g., whether the tool modifies anything), authentication needs, rate limits, or return behavior. The description focuses on what the tool evaluates but not on its operational traits.

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 dense sentence listing multiple aspects. While it packs information, it is not front-loaded with a clear primary action and could be more structured for readability.

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?

The description does not specify what the tool returns (e.g., a report, score, or feedback). Given the absence of an output schema, the agent lacks understanding of the invocation outcome. For a tool dealing with evaluation plans, this is a significant gap.

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%, with both parameters documented. The tool description adds context about the agent_definition parameter ('the more complete, the better the evaluation') and the language enum, but overall adds limited additional meaning beyond the 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 the tool evaluates or helps create an agent's evaluation plan, listing specific dimensions, metrics, and other components. This provides a clear verb and resource, distinguishing it from siblings like 'evaluar_sistema' which likely evaluate the agent directly. However, the dual role (evaluate vs. create) introduces slight 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 implies usage for evaluation plan assessment or creation but does not explicitly state when to use this tool versus alternatives. No exclusions or specific context are given, leaving the agent to infer from the name and sibling list.

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. It discloses that the tool evaluates and verifies mechanisms but does not explicitly state whether it has side effects (e.g., read-only). The behavior is inferred as safe evaluation, but the description lacks explicit safety/permission disclosure.

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 two sentences, no fluff, front-loaded with core purpose. 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 tool's complexity (autonomy levels, risk mechanisms, structured output) and no output schema, the description gives a reasonable overview. It mentions output returns a 'structured evaluation brief', but lacks details on the brief's content or structure. Still sufficient for agent selection.

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 baseline is 3. The tool description adds minimal parameter semantics beyond 'receives agent definition' and 'returns structured brief'. It does not elaborate on parameter usage or behavior beyond 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 tool's function: determining appropriate autonomy level (copiloto/ejecutor supervisado/autónomo con guardrails) and verifying risk reduction mechanisms. It also specifies input (agent definition) and output (structured evaluation brief), distinguishing it from sibling tools like evaluar_necesidad or evaluar_sistema.

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 implies usage for autonomy evaluation but provides no explicit guidance on when to use this tool versus alternatives (e.g., evaluar_necesidad, evaluar_sistema). No 'when not to use' or comparison to siblings is 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 must carry behavioral transparency. It explains it evaluates and detects antipatterns, which is non-destructive. It could explicitly state read-only, but the evaluation nature is clear enough for safe usage.

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 two sentences, highly concise, and front-loaded with the core purpose. Every sentence adds value with no wasted words.

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 two parameters and no output schema, the description sufficiently covers purpose and usage. It lacks details about return format or output, but for an evaluation tool, the context is adequate.

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

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

Schema coverage is 100%, so baseline is 3. The description does not add extra information about the parameters beyond what the schema already provides.

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: evaluating whether a problem justifies using an agent or can be solved with simpler approaches. It specifies detecting antipatterns, making the goal unambiguous.

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 explicitly says to use the tool before building or to question an existing agent, but it does not mention when not to use it or suggest alternative tools from the sibling list. However, the guidance is clear enough for an agent to decide when to invoke.

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

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

No annotations are provided, so the description must carry the burden of behavioral disclosure. The description only states what topics it evaluates (purpose) but does not disclose what the tool does with the input, whether it modifies state, requires authentication, has rate limits, or what the output format is. This is inadequate for an evaluation tool that likely returns a structured assessment.

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 moderate-length sentence that starts with the verb 'Evalúa', making the action clear. It concisely lists the evaluation dimensions without redundancy. However, a bit more structure (e.g., separating purpose from scope) could improve readability.

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 output schema, the description should explain the evaluation outcome, return format, or methodology. It only lists topics covered. For an evaluation tool with 3 parameters, the lack of information about what the agent receives back (e.g., a report, score, recommendations) makes it incomplete.

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

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

Schema coverage is 100% and all parameters have descriptions. The tool description adds context about the evaluation topics but does not provide additional meaning beyond the schema. Baseline 3 is appropriate as the description neither harms nor significantly enhances parameter understanding.

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 evaluates how an agent fits into a larger system, listing specific aspects (catalog of skills, reuse vs specialization, orchestration, automation vs supervision, memories). This is a specific verb+resource combination that distinguishes it from siblings like 'evaluar_autonomia' and 'evaluar_necesidad'.

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. The description implies it is for system-level integration evaluation, but does not provide any when-to-use or when-not-to-use conditions. Sibling tools exist, but no differentiation criteria are offered.

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. It only discloses that missing fields are marked as pending, but does not mention side effects, permissions, idempotency, or any other behavioral traits beyond the bare minimum.

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?

Two sentences with no wasted words. The purpose is front-loaded, and the description is efficiently structured for quick reading.

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?

Despite 10 parameters and no output schema, the description is minimal. It does not explain the generation process, output format, prerequisites, or how to handle optional fields. This leaves agents without sufficient context to use the tool confidently.

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

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

Schema coverage is 100%, so baseline is 3. The description adds no additional meaning beyond that the fields are 'provistos' (provided), which does not enhance understanding of individual parameters.

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 title and description clearly state the tool generates a formal contract for an agent using provided fields, and specifically marks missing fields as [PENDIENTE]. This distinguishes it from siblings, none of which mention contract generation.

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 implies usage when generating a contract, but provides no explicit guidance on when to use this tool versus alternatives, nor any when-not-to-use conditions. The context is implied but not stated.

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 discloses that the tool returns a Markdown guide. There are no side effects or hidden behaviors; the description is straightforward and honest. However, it could mention that it is a read-only operation with no side effects, but given the simplicity, a score of 4 is appropriate.

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?

Two sentences that are front-loaded with the main purpose and include usage guidance. No extraneous content.

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 simple, zero-parameter, no-output-schema tool, the description is complete. It states what is returned, the format, and when to use it. No additional information 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?

The tool has zero parameters, so baseline is 4. The description does not need to add parameter information. Schema coverage is 100% trivially.

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?

Description clearly states the tool returns 'la guía completa El Buen Agente (v2) en Markdown', specifying the verb, resource, and format. It distinguishes from sibling tools by explicitly mentioning that for specific agent operations, one should use evaluar_*/revisar_*/auditar_* tools.

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?

Explicitly advises using this tool for general context and provides clear alternatives by naming the evaluar_*/revisar_*/auditar_* tools for concrete agent operations. This tells the agent when to use and when not to use this tool.

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 does not disclose side effects, authentication requirements, or what happens if verification fails. The tool appears to generate a plan, but it's unclear if it modifies state or is read-only.

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 two sentences, front-loaded with the main action, and contains no fluff. Every part is relevant.

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

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

With 3 parameters, no output schema, and no annotations, the description covers the purpose and usage criteria adequately but lacks details on output format, error handling, or prerequisites. Not terribly incomplete, but could be better.

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

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

Schema coverage is 100%, so baseline is 3. The description does not add significant meaning beyond the schema; it merely restates that 'problema' is the candidate task. No extra parameter-level guidance is provided.

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 explicitly states it generates a startup plan for a new agent, with specific conditions (one agent, concrete problem, human reviewer) and verification criteria. This clearly distinguishes it from sibling tools like 'auditar_contexto' or 'construir_agente'.

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 implies usage for new agent startup and provides criteria for the problem (recurring, time-consuming, accessible data). However, it does not explicitly state when not to use this tool or suggest alternatives.

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 provided, so description bears full responsibility. It states the evaluation purpose but omits behavioral traits like whether the tool is read-only, modifies state, requires specific permissions, or produces a report.

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?

Single sentence, efficient, and front-loaded with the core purpose. However, it could benefit from breaking into multiple sentences for readability, but as is, it is concise and adequately sized.

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?

Lacks details about return value, output format, or outcomes. For a planning tool with no output schema, the description should explain what the agent receives after invocation. The current description is too minimal for an unfamiliar 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 100%: both parameters (language and agent_definition) are described in the schema. The description does not add extra meaning beyond the schema, so baseline score of 3 applies.

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

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

The description clearly states it evaluates which parts of an agent to expose as tool, resource, or prompt, and whether UI or API/MCP is appropriate. This distinguishes it from siblings like 'evaluar_sistema' or 'evaluar_autonomia' by focusing on exposure strategy.

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

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

No guidance on when to use this tool versus alternatives. No mention of prerequisites, when not to use, or which sibling might be more appropriate for specific tasks.

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 the tool returns 'el flujo recomendado de tools', but does not specify the output format (e.g., ordered list, text, or structured data). For a simple recommendation tool, this is acceptable but could be more 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?

Two concise sentences that front-load the purpose and usage guidance. No unnecessary words. Every sentence 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?

The description covers the core purpose, usage context, and parameter semantics. However, it omits the return value structure, which would help an agent process the output. Given the tool's simplicity and lack of output schema, this is a minor gap.

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 single parameter 'situacion' has a clear enum with values 'nuevo' and 'existente', fully described in the schema. The tool description adds valuable context by explaining when to choose each value, going beyond the schema's built-in 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 title and description clearly state the tool recommends an order of tools based on the situation (new vs. existing agent). It also explicitly says to call it first when unsure where to start, differentiating it from sibling tools that focus on specific tasks like auditing or designing.

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 strong when-to-use guidance by stating 'Llamala PRIMERO si no sabés por dónde empezar.' It also distinguishes the two situations: 'nuevo' vs. 'existente'. However, it does not explicitly state when not to use the tool or name specific alternatives beyond the sibling list.

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 present, so the description must carry the full burden. It describes the tool as a verification step ('verifica') but does not explicitly state it is read-only, nor does it mention any side effects, prerequisites, or error handling. The behavioral traits (e.g., idempotency, auth requirements) are not disclosed.

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

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

The description is two sentences, front-loaded with the core purpose. Every sentence is informative and necessary, with no redundant language or filler.

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 (2 parameters, no output schema), the description covers the main purpose, input, and output but lacks detail on the output structure ('brief de evaluación estructurado'). Additionally, the 'language' parameter is omitted from the description. Without an output schema, the description should better specify what the structured brief contains.

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

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

Schema coverage is 100%, providing baseline 3. The description adds meaning for 'agent_definition' (calls it 'la definición del agente') and implies an output brief, but does not mention the 'language' parameter or its enum values. Overall, the description provides moderate added value beyond the 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 specifies the tool's purpose: verifying that the boundary between recommendation and execution is defined in code (status + gates), not discovered in production. It lists concrete items (what executes directly, pending approval, rejected) and states the input (agent definition) and output (structured evaluation brief). This distinguishes it from siblings like 'revisar_rol_y_frontera' which likely focus on role boundaries.

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 implies usage during design time ('no descubierta en producción') but does not explicitly state when to use this tool versus alternatives like 'revisar_rol_y_frontera' or 'auditar_contexto'. No when-not-to-use guidance is provided, and the context signals show many sibling tools with overlapping themes.

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 provided, so description carries full burden. It describes the tool's function but fails to disclose behavioral traits like whether it modifies data, errors on invalid input, or rate limits. The read-only nature is implied but not explicit.

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?

Three sentences cover purpose, inputs, and output. Front-loaded with key action. No waste, but could be more structured (e.g., bullet points).

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?

No output schema or annotations; description mentions returns 'brief de evaluación estructurado' but lacks detail on structure. For a tool with 2 params and no nested objects, completeness is adequate but not thorough.

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

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

Schema coverage is 100%, so schema already documents both parameters. Description adds minor value (e.g., 'Cuanto más completa, mejor la evaluación') but doesn't provide critical format or syntax details beyond schema. Baseline 3 is appropriate.

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

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

Description clearly states the tool verifies outputs are actionable, with specific criteria (strict schema, readable summary, gate exposure). Distinguishes from siblings like 'evaluar_sistema' by focusing on output actionability rather than system-level evaluation.

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?

Description implies usage for checking output actionability but lacks explicit guidance on when not to use or how it differs from similar tools. No alternatives 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?

With no annotations, the description carries the full burden. It clearly indicates a read-only verification action ('Verifica', 'devuelve un brief'), which is sufficient for a non-destructive tool. No contradictions.

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?

Single sentence that front-loads the core purpose and defines input/output. No redundant words or tangential content.

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?

The description states it returns a 'brief de evaluación estructurado' but does not detail the structure or evaluation criteria. For a complex verification tool without an output schema, this is a notable gap.

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

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

Schema coverage is 100%, and the description adds no new semantics beyond the schema. It restates 'Recibe la definición del agente' but does not clarify format or provide usage examples.

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 uses specific verbs ('Verifica', 'Recibe', 'devuelve') and clearly states the resource: agent role clarity and boundary. It distinguishes from siblings like 'revisar_frontera_ejecucion' by focusing on role and identity layer.

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 implies usage when verifying role clarity and boundaries (e.g., during agent design), but provides no explicit exclusions or comparisons to sibling tools like 'auditar_contexto' or 'revisar_frontera_ejecucion'.

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 discloses that it closes the cycle with a contract and returns structured content with counts and a normalized verdict (apto only if faltas === 0). However, it does not clarify if the tool has side effects (e.g., writing state) beyond the cycle closure, nor does it mention authentication or rate limits. The disclosure is adequate but lacks depth.

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 three sentences long, covering purpose, input, output, and use case without any fluff. Each sentence serves a distinct and necessary function, making it highly efficient.

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 (one parameter with 19 sub-items) and the presence of an output schema, the description explains the input requirements, the output structure (counts and normalized verdict), and the verdict condition. It does not cover error handling or edge cases, but for a CI gate tool, the current level is sufficient. Minor gap prevents a perfect score.

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

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

Schema coverage is 100%, with the 'puntos' parameter described in the schema as 'Los 19 puntos del checklist con su estado evaluado.' The description repeats that the points must be 19 with states (ok|parcial|falta), adding no new semantic meaning beyond what the schema already provides. Therefore, the description adds minimal value over the 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 name, title, and description clearly state this tool validates the checklist verdict for CI. It specifies it closes the checklist cycle, takes 19 points with states, and returns structured validation output. It distinguishes itself from siblings like checklist_nacimiento by being for programmatic consumption and gates.

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 indicates this tool should be used after checklist_nacimiento to close the cycle, and explicitly states it's intended for CI/gates where text parsing is not needed. However, it does not explicitly state when not to use it or mention alternatives, though the context of sibling tools makes the use case clear.

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