codeagent

A command-line wrapper that sends coding tasks to Codex, Claude, or Gemini, which are different AI systems. It supports file references, parallel tasks, and choosing which system handles each task.

In plain words
What is it for?
Use it for code analysis, large refactors, code generation, documentation tasks, and interface prototypes across one or more repositories.
Why use it?
It gives one way to delegate code work while selecting a backend suited to the task, instead of learning separate command formats.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/cacr92/wereply/codeagent
Any agent
npx skills add cacr92/WeReply --skill codeagent
Clone the repo
git clone --depth 1 https://github.com/cacr92/WeReply

Made for: Claude Code, Codex.

Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,391 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00035 $0.01391
Opus 5 $0.00017 $0.00696
Sonnet 5 $0.00007 $0.00278
Haiku 4.5 $0.00003 $0.00139

Measured yesterday against content hash 5e74542e6a42, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codeagent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.trae/skills/codeagent/SKILL.md · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codeagent Wrapper Integration

Overview

Execute codeagent-wrapper commands with pluggable AI backends (Codex, Claude, Gemini). Supports file references via @ syntax, parallel task execution with backend selection, and configurable security controls.

When to Use

  • Complex code analysis requiring deep understanding
  • Large-scale refactoring across multiple files
  • Automated code generation with backend selection

Usage

HEREDOC syntax (recommended):

codeagent-wrapper - [working_dir] <<'EOF'
<task content here>
EOF

With backend selection:

codeagent-wrapper --backend claude - <<'EOF'
<task content here>
EOF

Simple tasks:

codeagent-wrapper "simple task" [working_dir]
codeagent-wrapper --backend gemini "simple task"

Backends

Backend Command Description Best For
codex --backend codex OpenAI Codex (default) Code analysis, complex development
claude --backend claude Anthropic Claude Simple tasks, documentation, prompts
gemini --backend gemini Google Gemini UI/UX prototyping

Backend Selection Guide

Codex (default):

  • Deep code understanding and complex logic implementation
  • Large-scale refactoring with precise dependency tracking
  • Algorithm optimization and performance tuning
  • Example: "Analyze the call graph of @src/core and refactor the module dependency structure"

Claude:

  • Quick feature implementation with clear requirements
  • Technical documentation, API specs, README generation
  • Professional prompt engineering (e.g., product requirements, design specs)
  • Example: "Generate a comprehensive README for @package.json with installation, usage, and API docs"

Gemini:

  • UI component scaffolding and layout prototyping
  • Design system implementation with style consistency
  • Interactive element generation with accessibility support
  • Example: "Create a responsive dashboard layout with sidebar navigation and data visualization cards"

Read the full file on GitHub · 206 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 206 lines · 35 tokens per session scan A 5e74542e6a42

Subscribe to this mod's changes

codeagent is a skill published in the GitHub repository cacr92/WeReply (5 stars, last pushed 7mo ago), licensed MIT. It adds 35 tokens to every session and 1,391 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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