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ask-ai

Analyze code or ask questions using AI agents like Gemini, Codex, and Claude Code, with options for sandbox testing and structured edits.

Instructions

Provider selection [--provider], model selection [-m], sandbox [-s], and changeMode:boolean for providing edits. Supports Gemini, Codex, and Claude Code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesAnalysis request. Use @ syntax to include files (e.g., '@largefile.js explain what this does') or ask general questions
providerNoProvider to use (e.g., 'gemini', 'codex', 'claude'). Defaults to server config ('gemini').gemini
modelNoOptional model to use (e.g., 'gemini-2.5-flash', 'gpt-5.3-codex'). If not specified, uses the server default (provider default).
sandboxNoUse sandbox mode (-s flag, Gemini only) to safely test code changes, execute scripts, or run potentially risky operations in an isolated environment
changeModeNoEnable structured change mode (Gemini only) - formats prompts to prevent tool errors and returns structured edit suggestions that Claude can apply directly
chunkIndexNoWhich chunk to return (1-based)
chunkCacheKeyNoOptional cache key for continuation
Behavior2/5

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

No annotations are provided, so the description should disclose behavioral traits. It does not mention that sandbox and changeMode are Gemini-only (hidden in schema), nor does it discuss authentication, rate limits, or error handling.

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

Conciseness3/5

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

The description is a single sentence listing options, which is concise but lacks structure and is not front-loaded with a clear purpose statement.

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 7 parameters, no output schema, and no annotations, the description is incomplete. It does not explain return values, continuation mechanics (chunkIndex, chunkCacheKey), or practical usage scenarios.

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 coverage is 100%, so baseline is 3. The description briefly restates a few parameters (provider, model, sandbox, changeMode) but adds little beyond the schema descriptions, which are already detailed.

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 implies the tool is for querying an AI and mentions provider/model selection, sandbox, and changeMode. It distinguishes itself from siblings like 'brainstorm' or 'coordinate-review' by focusing on AI querying, but lacks an explicit verb+resource phrase.

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 other tools or when not to use it. It only lists optional flags, leaving the agent to infer usage context.

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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