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ask_gemini

Generates context from files and queries Gemini for a response.

Instructions

Generates context from files and sends it to Gemini for a response.

This tool combines context generation with a direct call to the Gemini API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_instructionsNoThe primary query or instructions for Gemini.
file_selectionsNoOptional list of files/line ranges to include in the context.
project_pathNoOptional project root for relative paths.
include_claude_memoryNoInclude CLAUDE.md files in context.
include_cursor_rulesNoInclude Cursor rules files in context.
auto_meta_promptNoIf no user_instructions, generate a meta-prompt.
temperatureNoAI temperature for generation.
modelNoSpecific Gemini model to use.
thinking_budgetNoOptional token budget for thinking mode.
text_outputNoIf True, return the response as a string. If False, save it to a file.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, so description carries full burden. It mentions combining context generation with an API call but fails to disclose behavioral traits like file reading, potential mutations (none), or authentication needs. Insufficient transparency for a tool with 10 parameters.

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?

Two sentences, both informative. First sentence states primary function, second adds context. No fluff, front-loaded. Could include a brief usage hint, but overall efficient.

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?

Despite 10 parameters and output schema, description is minimal. Missing explanation of tool's workflow (context generation then API call), order of operations, or how parameters interact. Incomplete for a complex tool.

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. Description adds minimal extra meaning beyond schema—just 'context from files' which aligns with file_selections. No additional parameter semantics or examples provided.

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 it generates context from files and sends to Gemini, specifying a verb ('generates context') and resource ('Gemini'). It differentiates from sibling tools (code review, PR review) by focusing on general AI query with file context.

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 on when to use this tool versus alternatives. The description lacks explicit context for appropriate usage, such as when to choose this over direct Gemini calls or other context-generation tools.

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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