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gemini_prompt

Send prompts to Google's Gemini models via CLI to generate text responses. Supports contextual prompts and optional model selection for AI interactions.

Instructions

Invoke the headless Gemini CLI with a single prompt. Stateless — each call is an independent turn. Runs in the MCP server's current working directory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesPrompt text sent to the Gemini CLI.
modelNoOptional model identifier (e.g., gemini-2.5-pro).
Behavior3/5

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 key behavioral traits: statelessness, independence of calls, and execution directory. However, it lacks details on permissions, rate limits, error handling, or output format. For a tool with no annotations, this is adequate but leaves gaps in 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?

The description is highly concise and front-loaded: three short sentences with zero waste. Each sentence adds value—stating the purpose, behavioral trait (statelessness), and execution context—earning its place efficiently.

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?

Given no annotations, no output schema, and 2 parameters with full schema coverage, the description is minimally complete. It covers purpose and basic behavior but lacks details on output, errors, or advanced usage. For a stateless CLI tool, this is adequate but not comprehensive.

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 both parameters ('prompt' and 'model') fully. The description doesn't add any parameter-specific meaning beyond what the schema provides, such as examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

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 the tool's purpose: 'Invoke the headless Gemini CLI with a single prompt.' It specifies the verb ('invoke') and resource ('Gemini CLI'), and distinguishes it from the sibling tool by noting it's 'stateless — each call is an independent turn.' However, it doesn't explicitly name the sibling tool for full differentiation.

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 provides clear context for usage: 'Stateless — each call is an independent turn' and 'Runs in the MCP server's current working directory.' This implies when to use it (for independent prompts) and hints at an alternative (the sibling tool likely handles context). However, it doesn't explicitly name the sibling or state when-not-to-use scenarios.

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

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