Server Quality Checklist

Tool Scores

• delegate_to_providerB
  3.2/5.0
  Behavior2/5

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

  No annotations are present, so the description must disclose behavioral traits. It only states 'generic version' and the act of dispatching, but does not explain error handling, authentication requirements (beyond api_key), response format, or whether the call is synchronous/streaming.

  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 very short and front-loaded: one sentence defining function, one for usage. No fluff or repetition. Every sentence 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?

  Given the tool's complexity (9 parameters, 5 required) and generic nature, the description is too sparse. It lacks details on constructing provider_url, task format, and what the output schema contains aside from its mere existence. An agent would struggle to invoke correctly without additional manual or external knowledge.

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

  Parameters2/5

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

  Schema coverage is low (44%), and the description adds no parameter-level information. It does not explain the format of provider_url, task, agent_name, or other critical fields beyond what the schema already provides, failing to compensate for gaps.

  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 that the tool dispatches an agent to any OpenAI/Anthropic-compatible endpoint, and contrasts with default providers by naming alternatives (DeepSeek, MiniMax, etc.). It is specific and hints at differentiation from siblings like delegate_to_local_agent.

  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 explicitly instructs to use this for non-default providers, providing concrete examples. It gives clear usage context but does not explain when not to use (e.g., when default provider is sufficient) or alternatives.

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

• delegate_batchA
  4.5/5.0
  Behavior4/5

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

  Discloses parallelism, batch size cap, KV cache benefits, and the sub-agent limitation. However, lacks details on error handling or behavior on partial failures.

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

  Conciseness4/5

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

  Front-loaded main purpose, but some sections (limitation, alternatives) are lengthy. Still efficient overall.

  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?

  Covers purpose, usage, parameters, and limitations well. With output schema present, return format is not needed. Minor gaps like error behavior do not detract significantly.

  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?

  Only parameter 'tasks' is described beyond schema: explains it is a list of dicts with keys matching delegate_to_local_agent and a hard cap, adding value over 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 it dispatches up to N agents in parallel using asyncio.gather, contrasting with the sibling delegate_to_local_agent which handles single agents.

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

  Usage Guidelines5/5

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

  Explicitly tells when to use (multiple independent sub-tasks with parallel slots) and when not to use (cannot be called from sub-agent), with clear alternative suggestions.

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

• list_local_agentsA
  4.5/5.0
  Behavior4/5

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

  No annotations provided, so description carries full burden. It clearly states it is a listing operation with no side effects, and specifies return values. Sufficiently transparent.

  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?

  Single sentence conveying all necessary information without redundancy. Highly concise and front-loaded.

  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?

  Given no parameters and a clear output schema (described), the description fully covers what the tool does and returns. Complete for its simplicity.

  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?

  No parameters exist, so the description adds no value beyond schema. Baseline score of 4 is appropriate as schema coverage is 100% and no extra parameter info is needed.

  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 lists available agents from a specific directory, mentions the sibling function for delegation, and specifies the returned fields (name, description, model). It is specific and distinguishes from siblings.

  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 use when needing to know available local agents for delegation, but does not explicitly state when not to use or compare to alternatives. Sibling context helps, but explicit guidance is missing.

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

• local_backend_statusA
  4.5/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the full burden. It discloses that the tool is a read-only health check returning status, models, and latency, which is sufficient 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.

  Conciseness5/5

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

  Two sentences, front-loaded with purpose and specific outputs. No wasted words.

  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?

  Given no parameters and a clear output schema, the description adequately covers the tool's purpose and return values. Completes the context for its role as a pre-delegation check.

  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?

  Zero parameters, so no additional info needed. Schema coverage is 100% vacuously. Baseline for 0 params is 4.

  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 it performs a health check on the backend, returning status, models, and latency. It distinguishes from sibling tools like delegation and listing agents.

  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?

  Explicitly mentions it is useful before delegating to validate backend reachability. No explicit when-not-to or alternatives, but the context is clear.

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

• delegate_to_local_agentA
  4.7/5.0
  Behavior5/5

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

  No annotations were provided, so the description carries full burden. It discloses that the agent is loaded from a .md file with frontmatter, that tool calling includes read_file/write_file/run_bash, that the backend must be OpenAI/Anthropic-compatible, and that the orchestrator remains intact. This sufficiently informs the agent of behavioral traits.

  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 concise and front-loaded with the core action. Each sentence serves a purpose: stating the action, clarifying when to use, and pointing to an alternative. No unnecessary words or repetition.

  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?

  Given the tool's complexity (6 parameters, output schema exists), the description covers the agent source, backend compatibility, alternative tool, and basic behavior. The presence of an output schema means return values do not need explanation. The description is complete for the agent to select and invoke 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?

  Schema description coverage is 100%, so baseline is 3. The main description does not add additional meaning beyond what is already in the input schema parameter descriptions, which are already detailed. Therefore, no extra value is provided by the description for parameters.

  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 purpose: 'Despacha un agente (cargado desde un .md con frontmatter) a un backend OpenAI/Anthropic-compatible con tool calling completo (read_file / write_file / run_bash).' It distinguishes from the sibling tool delegate_batch by specifying 'Para despachar VARIOS agentes en paralelo en una sola llamada, ver delegate_batch.'

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

  Usage Guidelines5/5

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

  The description explicitly states when to use the tool: 'USAR cuando el usuario quiera ejecutar un agente específico en un backend alternativo (local, cloud, etc.) en vez del default del orquestador.' It also provides an exclusion by pointing to delegate_batch for multiple agents in parallel.

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