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etheaven
by etheaven

ask-codex

Analyze, review, edit, or generate code using OpenAI models. Supports file references, model selection, reasoning effort, and structured edits for efficient code tasks.

Instructions

Use OpenAI Codex to analyze, review, edit, or generate code. Call this tool whenever the user mentions "codex", "use codex", or wants to leverage OpenAI models (GPT-5.4, GPT-5.3-codex, etc.) for code tasks. Supports file references with @ syntax (e.g. @src/), model selection, reasoning effort control, and structured edits via changeMode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesTask or question. Use @ to include files (e.g., '@largefile.ts explain').
modelNoModel ID to use. IMPORTANT: Use exact IDs listed below, do NOT invent or modify model names. Recommended (use in this order): gpt-5.4 (default, best), gpt-5.3-codex (best coding), gpt-5.3-codex-spark (instant, Pro only), gpt-5.2-codex, gpt-5.2, gpt-5.1-codex-max, gpt-5.1-codex, gpt-5.1, gpt-5, gpt-5-mini, gpt-5-nano. Large context (1M): gpt-4.1, gpt-4.1-mini, gpt-4.1-nano.
reasoningEffortNoReasoning effort level. Controls depth of internal reasoning. Values: none, minimal, low, medium (default), high, xhigh. Higher = deeper analysis but slower and more expensive. Not all models support all levels. gpt-5.4 supports: none/low/medium/high/xhigh. gpt-5.3-codex supports: low/medium/high/xhigh. o3/o4-mini support: low/medium/high.
sandboxNoQuick automation mode: enables workspace-write + on-failure approval. Alias for fullAuto.
fullAutoNoFull automation mode
approvalPolicyNoApproval: never, on-request, on-failure, untrusted
approvalNoApproval policy: untrusted, on-failure, on-request, never
sandboxModeNoAccess: read-only, workspace-write, danger-full-access
yoloNo⚠️ Bypass all safety (dangerous)
cdNoWorking directory
workingDirNoWorking directory for execution
changeModeNoReturn structured OLD/NEW edits for refactoring
chunkIndexNoChunk index (1-based)
chunkCacheKeyNoCache key for continuation
imageNoOptional image file path(s) to include with the prompt
configNoConfiguration overrides as 'key=value' string or object
profileNoConfiguration profile to use from ~/.codex/config.toml
timeoutNoMaximum execution time in milliseconds (optional)
includeThinkingNoInclude reasoning/thinking section in response
includeMetadataNoInclude configuration metadata in response
searchNoEnable web search by activating web_search_request feature flag. Requires network access - automatically sets sandbox to workspace-write if not specified.
ossNoUse local Ollama server (convenience for -c model_provider=oss). Requires Ollama running locally. Automatically sets sandbox to workspace-write if not specified.
enableFeaturesNoEnable feature flags (repeatable). Equivalent to -c features.<name>=true
disableFeaturesNoDisable feature flags (repeatable). Equivalent to -c features.<name>=false
Behavior2/5

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

No annotations provided, so description must carry the full burden. It mentions file references, model selection, and changeMode, but omits critical behaviors like destructive actions (yolo), automation modes, and safety implications. Lacks depth for a complex tool.

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?

Two sentences covering purpose, trigger, and key features. No redundancy, well front-loaded with essential information.

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?

No output schema, yet the description does not mention what the tool returns. Despite 100% schema coverage, the lack of return value description and incomplete coverage of automation features makes it inadequate for a tool with 24 parameters.

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 adds high-level context (e.g., @ syntax, changeMode) but does not significantly enhance understanding beyond the schema's parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool uses OpenAI Codex for code tasks (analyze, review, edit, generate). It specifies when to call it (when user mentions 'codex' or wants OpenAI models), distinguishing it from sibling tools like batch-codex or brainstorm.

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?

Explicitly states to call when user mentions 'codex' or wants OpenAI models for code tasks. Does not provide explicit when-not-to-use scenarios, but the trigger conditions are clear.

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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