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consult_gemini

Send a query to Gemini AI via its command-line interface, specifying a working directory and optional model for flexible AI assistance.

Instructions

Send a query directly to the Gemini CLI.

Args: query: Prompt text forwarded verbatim to the CLI. directory: Working directory used for command execution. model: Optional model alias (flash, pro) or full Gemini model id. timeout_seconds: Optional per-call timeout override in seconds.

Returns: Gemini's response text or an explanatory error string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
directoryYes
modelNo
timeout_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions forwarding the query verbatim and returning response/error, but does not clarify read-only nature, authentication needs, rate limits, or potential 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.

Conciseness5/5

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

The description is concise and well-structured with an initial purpose sentence and a clear Args/Returns format. Every sentence is informative with no fluff.

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?

While the description covers invocation details and parameter semantics, it lacks contextual completeness for an AI agent: no guidance on when to use this tool vs siblings, no output schema details, and no behavioral context beyond the immediate invocation.

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?

The description includes detailed parameter explanations (query, directory, model, timeout_seconds) and return value, adding meaning beyond the input schema. Schema description coverage is 0% in JSON, but the docstring compensates well.

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 states 'Send a query directly to the Gemini CLI', clearly indicating the action and resource. However, it does not explicitly distinguish from sibling tools like 'consult_gemini_with_files' or 'web_search', which would be helpful for an AI agent.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description lacks explicit context such as prerequisites, when-not-to-use, or comparisons with siblings.

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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