Borrowing it
Nothing to install: this file belongs to cacr92/WeReply. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cacr92/WeReply/main/.trae/skills/codeagent/SKILL.mdgit clone --depth 1 https://github.com/cacr92/WeReplyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cacr92/wereply/codeagent)<a href="https://agentmods.dev/skills/cacr92/wereply/codeagent"><img src="https://agentmods.dev/badge/skills/cacr92/wereply/codeagent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cacr92/wereply/codeagent"><img src="https://agentmods.dev/badge/skills/cacr92/wereply/codeagent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.01391 |
| Opus 5.5 | $0.00014 | $0.00556 |
| Sonnet 5.5 | $0.00007 | $0.00278 |
| Haiku 4.5 | $0.00003 | $0.00139 |
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 1mo ago.
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.
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"
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.
- 1mo ago First seen · 206 lines · 35 tokens per session scan A 5e74542e6a42
codeagent is a skill published in the GitHub repository cacr92/WeReply (9 stars, last pushed 9mo ago), licensed MIT. It adds 35 tokens to every session and 1,391 once invoked, about $0.0001 per session on Opus 5.5. 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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