Skip to main content
Glama
fegone
by fegone

delegate_to_provider

Route a sub-agent to any OpenAI/Anthropic-compatible provider by specifying the endpoint, API key, and model, enabling delegation to non-default backends like DeepSeek or local models.

Instructions

Versión genérica: despacha un agente a CUALQUIER endpoint OpenAI/Anthropic-compatible. Usar para rutear explícitamente a providers no configurados como default (DeepSeek, MiniMax, Alibaba, OpenRouter, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
modelYesIdentificador del modelo (depende del provider)
api_keyYesAPI key del provider
workdirNo.
mode_tagNoTag a prepender en system prompt (default MODE:LOCAL — puede ser MODE:DEEPSEEK etc.)MODE:LOCAL
max_turnsNo
agent_nameYes
max_tokensNo
provider_urlYesURL completa al endpoint /v1/messages (o equivalente)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/fegone/claude-code-delegate-local'

If you have feedback or need assistance with the MCP directory API, please join our Discord server