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.
npx agentmods add instructions/rachittshah/cc-codex/claude-mdgit clone --depth 1 https://github.com/rachittshah/cc-codexWrote 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/instructions/rachittshah/cc-codex/claude-md)<a href="https://agentmods.dev/instructions/rachittshah/cc-codex/claude-md"><img src="https://agentmods.dev/badge/instructions/rachittshah/cc-codex/claude-md.svg" alt="Measured on agentmods" 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 | $0.03552 | $0.03552 |
| Opus 5 | $0.01776 | $0.01776 |
| Sonnet 5 | $0.00710 | $0.00710 |
| Haiku 4.5 | $0.00355 | $0.00355 |
Grade D, and why
cc-codex CLAUDE.md scanned grade D with 2 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 5d 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.
Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
printenv OPENAI_API_KEY Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
**Note**: The high reasoning effort is automatically enabled via `model_reasoning_effort = "high"` in `~/.codex/config.toml` How it starts
The opening of the file, as written. The whole thing — 547 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Code + Codex Integration
Role: Claude Code delegates reasoning, planning, and specification tasks to Codex CLI using
gpt-5model with high reasoning effort
Core Directive
When Claude Code needs to:
- Reason through complex problems
- Plan multi-step implementations
- Create detailed specifications
- Analyze architectural decisions
→ Delegate to Codex CLI using gpt-5 model
Note: The high reasoning effort is automatically enabled via model_reasoning_effort = "high" in ~/.codex/config.toml
Usage Pattern
When to Call Codex
Call Codex for:
- Deep reasoning - Complex logic, trade-offs, decision trees
- Planning - Breaking down features into actionable steps
- Specification - Creating detailed technical specs
- Analysis - Code architecture, performance, security reviews
- Design decisions - Comparing multiple approaches
When NOT to Call Codex
Do NOT call Codex for:
- Simple code edits or file operations
- Direct execution of known tasks
- Quick lookups or simple questions
- File reading/writing operations
Required Command Format
Always use this exact format:
codex exec -m gpt-5 --full-auto "YOUR_REASONING_TASK_HERE"
Command Breakdown
codex exec- Non-interactive execution-m gpt-5- REQUIRED: Use GPT-5 reasoning model--full-auto- Automatic execution with workspace write access"TASK"- Clear, specific reasoning/planning task
Note: High reasoning effort is automatically applied based on your ~/.codex/config.toml setting
Integration Rules
1. Model Requirement
# ✅ CORRECT - Always use gpt-5
codex exec -m gpt-5 --full-auto "reason through this problem"
# ❌ WRONG - Never omit model flag
codex exec --full-auto "reason through this problem"
2. Task Clarity
# ✅ CORRECT - Specific reasoning task
codex exec -m gpt-5 --full-auto "analyze three approaches for implementing user authentication: JWT, session-based, and OAuth2. Compare security, scalability, and complexity."
# ❌ WRONG - Vague request
codex exec -m gpt-5 --full-auto "help with auth"
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.
- 5d ago First seen · 547 lines · 3,552 tokens per session scan D 9610f66e581e
cc-codex CLAUDE.md is an instructions file published in the GitHub repository rachittshah/cc-codex (11 stars, last pushed 10mo ago), licensed Apache-2.0. It adds 3,552 tokens to every session, about $0.0178 per session on Opus 5. A static security scan graded it D with 2 findings (harvests environment variables, reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
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Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.