Skip to main content
Glama

nexus_ask

Send a prompt to any AI provider, including ChatGPT, Gemini, Claude, and Ollama. Use active provider/model by default or specify a different one.

Instructions

Send a prompt to any AI provider (ChatGPT, Gemini, Claude, Ollama, etc.). Uses the active provider/model by default, or specify a different one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel ID to use (e.g. "gpt-4o", "gemini-2.0-flash"). Defaults to active model.
promptYesThe prompt to send to the AI provider
providerNoProvider ID to use (e.g. "openai", "gemini", "ollama"). Defaults to active provider.
maxTokensNoMaximum tokens in the response
temperatureNoSampling temperature (0.0 to 2.0)
systemPromptNoOptional system prompt to set context

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It only repeats the defaulting behavior already present in the schema and says nothing about response format, errors, authentication failures, rate limits, or side effects, which is a significant gap for a tool that calls external providers.

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

Conciseness5/5

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

The description is two concise sentences with no filler. The core action is front-loaded in the first sentence, and the second sentence adds a useful usage detail about defaults without redundancy.

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

Completeness3/5

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

The description provides enough to start using the tool with just a prompt, but it omits what the tool returns, which matters because there is no output schema. It also lacks guidance on provider configuration requirements or how this compares to agent-related sibling tools, leaving moderate gaps.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all six parameters. The description adds no parameter-level meaning beyond the schema, such as examples, constraints, or relationships between provider and model, so the baseline score of 3 is appropriate.

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?

Description states a specific verb and resource: 'Send a prompt to any AI provider', with concrete provider examples. It clearly conveys the tool's function, though it does not explicitly differentiate it from sibling tools like nexus_agent_run or nexus_subagent_run.

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

Usage Guidelines3/5

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

The description gives useful context about default provider/model behavior and the option to override it. However, it does not state when to prefer this tool over alternatives such as agent_run, subagent_run, or plan_execute, leaving the choice partly implied.

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