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Ai Coding Agent Guardrails

Community
FrancoStino
ai-coding-agent-guardrails

Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.

Overview

PublisherFrancoStino
Repositoryopencode-skills-collection
Skill nameai-coding-agent-guardrails
Stars
90
Forks
12
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by FrancoStino on GitHub. Read the source before you install it.

Installation

Install the Ai Coding Agent Guardrails AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/FrancoStino/opencode-skills-collection/tree/main/bundled-skills/ai-coding-agent-guardrails
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/FrancoStino/opencode-skills-collection.git /tmp/opencode-skills-collection
mkdir -p .claude/skills
cp -r /tmp/opencode-skills-collection/bundled-skills/ai-coding-agent-guardrails .claude/skills/ai-coding-agent-guardrails
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ai Coding Agent Guardrails in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ai Coding Agent Guardrails on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ai Coding Agent Guardrails is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AI Coding Agent Guardrails

Secure the use of AI coding agents across engineering teams. This skill covers permission boundaries, secret protection, sandbox isolation, code review gates, and audit trails for Claude Code, Cursor, Copilot, and Codex.


Permission Boundaries

CLAUDE.md Configuration

Create a CLAUDE.md at the repository root to restrict Claude Code behavior:

markdown
# CLAUDE.md

## Restrictions

- NEVER read or output contents of .env, .env.*, secrets.yaml, or any file matching *.pem, *.key
- NEVER execute `rm -rf`, `DROP TABLE`, `kubectl delete`, or `terraform destroy` commands
- NEVER push directly to main or master branches
- NEVER modify files in the infrastructure/, terraform/, or .github/workflows/ directories without explicit user approval
- NEVER install new dependencies without listing them first for review
- NEVER access or display API keys, tokens, passwords, or connection strings

## Allowed Operations

- Read and modify application source code in src/, lib/, and tests/
- Run test suites with `npm test`, `pytest`, `go test`
- Run linters with `eslint`, `ruff`, `golangci-lint`
- Create new branches with prefix `ai/` or `agent/`
- Create and modify files in docs/ directory

## Code Standards

- All new functions must include docstrings or JSDoc comments
- All new code must have corresponding unit tests
- Follow existing code style and patterns in the repository
- Maximum file length: 500 lines. Suggest splitting if exceeded.

Command Allowlists

For agents that execute shell commands, define an explicit allowlist:

yaml
# .agent-permissions.yaml
agent_permissions:
  allowed_commands:
    - "npm test"
    - "npm run lint"
    - "npm run build"
    - "pytest"
    - "ruff check"
    - "go test ./..."
    - "git status"
    - "git diff"
    - "git log"
    - "git checkout -b"
    - "git add"
    - "git commit"
    - "ls"
    - "cat"
    - "head"
    - "tail"

  blocked_commands:
    - "rm -rf"
    - "curl"
    - "wget"
    - "ssh"
    - "scp"
    - "kubectl"
    - "terraform"
    - "aws"
    - "gcloud"
    - "az"
    - "docker push"
    - "npm publish"

  blocked_paths:
    - ".env*"
    - "**/*.pem"
    - "**/*.key"
    - "**/secrets/**"
    - "infrastructure/**"
    - ".github/workflows/**"

  allowed_paths:
    - "src/**"
    - "lib/**"
    - "tests/**"
    - "docs/**"
    - "package.json"
    - "pyproject.toml"

File System Access Controls

Use filesystem permissions to enforce boundaries at the OS level:

bash
#!/bin/bash
# setup-agent-workspace.sh
# Create a restricted workspace for agent execution

AGENT_USER="ai-agent"
REPO_DIR="/workspace/repo"

# Create agent user with limited permissions
useradd --system --shell /bin/bash --no-create-home "$AGENT_USER"

# Set ownership: developers own everything, agent gets read on most
chown -R root:developers "$REPO_DIR"
chmod -R 750 "$REPO_DIR"

# Grant agent write access only to safe directories
setfacl -R -m u:${AGENT_USER}:rwx "${REPO_DIR}/src"
setfacl -R -m u:${AGENT_USER}:rwx "${REPO_DIR}/tests"
setfacl -R -m u:${AGENT_USER}:rwx "${REPO_DIR}/docs"

# Deny agent access to sensitive files
setfacl -m u:${AGENT_USER}:--- "${REPO_DIR}/.env"
setfacl -R -m u:${AGENT_USER}:--- "${REPO_DIR}/infrastructure"
setfacl -R -m u:${AGENT_USER}:--- "${REPO_DIR}/.github/workflows"

echo "Agent workspace permissions configured."

Secret Protection

Pre-commit Hooks with git-secrets

bash
#!/bin/bash
# install-secret-scanning.sh

# Install git-secrets
git clone https://github.com/awslabs/git-secrets.git /tmp/git-secrets
cd /tmp/git-secrets && make install

# Initialize in repository
cd /path/to/repo
git secrets --install

# Register common secret patterns
git secrets --register-aws

# Add custom patterns for common credential formats
git secrets --add '-----BEGIN (RSA |EC |DSA )?PRIVATE KEY-----'
git secrets --add 'AKIA[0-9A-Z]{16}'
git secrets --add 'ghp_[a-zA-Z0-9]{36}'
git secrets --add 'sk-[a-zA-Z0-9]{48}'
git secrets --add 'xox[baprs]-[0-9a-zA-Z-]{10,}'
git secrets --add 'password\s*[:=]\s*["\x27][^\s]{8,}'
git secrets --add 'api[_-]?key\s*[:=]\s*["\x27][^\s]{8,}'

# Add allowed patterns (false positive exclusions)
git secrets --add --allowed 'EXAMPLE_KEY'
git secrets --add --allowed 'your-api-key-here'

Agent Output Scanning

Scan agent-generated output before it reaches version control:

python
#!/usr/bin/env python3
"""scan_agent_output.py - Scan AI agent output for leaked secrets."""

import re
import sys
from pathlib import Path

SECRET_PATTERNS = [
    (r'AKIA[0-9A-Z]{16}', 'AWS Access Key'),
    (r'(?i)aws_secret_access_key\s*[:=]\s*\S+', 'AWS Secret Key'),
    (r'ghp_[a-zA-Z0-9]{36}', 'GitHub Personal Access Token'),
    (r'gho_[a-zA-Z0-9]{36}', 'GitHub OAuth Token'),
    (r'sk-[a-zA-Z0-9]{48,}', 'OpenAI/Anthropic API Key'),
    (r'xox[baprs]-[0-9a-zA-Z\-]{10,}', 'Slack Token'),
    (r'-----BEGIN (RSA |EC |DSA )?PRIVATE KEY-----', 'Private Key'),
    (r'(?i)(password|passwd|pwd)\s*[:=]\s*["\x27][^\s]{4,}', 'Hardcoded Password'),
    (r'(?i)(api[_-]?key|apikey)\s*[:=]\s*["\x27][^\s]{8,}', 'API Key'),
    (r'eyJ[a-zA-Z0-9_-]{10,}\.[a-zA-Z0-9_-]{10,}', 'JWT Token'),
    (r'(?i)database_url\s*[:=]\s*\S+', 'Database Connection String'),
]


def scan_file(filepath: str) -> list[dict]:
    findings = []
    content = Path(filepath).read_text(errors="ignore")
    for line_num, line in enumerate(content.splitlines(), 1):
        for pattern, label in SECRET_PATTERNS:
            if re.search(pattern, line):
                findings.append({
                    "file": filepath,
                    "line": line_num,
                    "type": label,
                    "content": line.strip()[:120],
                })
    return findings


def main():
    files = sys.argv[1:]
    if not files:
        print("Usage: scan_agent_output.py <file1> [file2] ...")
        sys.exit(1)

    all_findings = []
    for f in files:
        all_findings.extend(scan_file(f))

    if all_findings:
        print(f"BLOCKED: {len(all_findings)} potential secret(s) detected:\n")
        for finding in all_findings:
            print(f"  [{finding['type']}] {finding['file']}:{finding['line']}")
            print(f"    {finding['content']}\n")
        sys.exit(1)

    print("OK: No secrets detected in agent output.")
    sys.exit(0)


if __name__ == "__main__":
    main()

Git Pre-commit Hook Integration

bash
#!/bin/bash
# .git/hooks/pre-commit
# Block commits containing secrets from AI agents

STAGED_FILES=$(git diff --cached --name-only --diff-filter=ACM)

if [ -z "$STAGED_FILES" ]; then
  exit 0
fi

echo "Scanning staged files for secrets..."

# Run git-secrets
git secrets --pre_commit_hook -- "$@"
GIT_SECRETS_EXIT=$?

# Run custom scanner on staged files
python3 .tools/scan_agent_output.py $STAGED_FILES
SCANNER_EXIT=$?

if [ $GIT_SECRETS_EXIT -ne 0 ] || [ $SCANNER_EXIT -ne 0 ]; then
  echo ""
  echo "COMMIT BLOCKED: Secrets detected in staged files."
  echo "If this is a false positive, use: git commit"
  exit 1
fi

Sandbox Configuration

Docker Sandbox for Agent Execution

dockerfile
# Dockerfile.agent-sandbox
FROM ubuntu:24.04

RUN apt-get update && apt-get install -y \
    git \
    nodejs \
    npm \
    python3 \
    python3-pip \
    && rm -rf /var/lib/apt/lists/*

# Create non-root agent user
RUN useradd -m -s /bin/bash agent && \
    mkdir -p /workspace && \
    chown agent:agent /workspace

# Drop capabilities
USER agent
WORKDIR /workspace

# No network by default - override at runtime if needed
# No access to Docker socket
# No access to host filesystem beyond mounted volume
bash
#!/bin/bash
# run-agent-sandbox.sh
# Launch an AI coding agent inside a locked-down container

REPO_DIR="$(pwd)"
CONTAINER_NAME="agent-sandbox-$$"

docker run \
  --name "$CONTAINER_NAME" \
  --rm \
  --network none \
  --read-only \
  --tmpfs /tmp:size=512m \
  --tmpfs /home/agent:size=256m \
  --memory 4g \
  --cpus 2 \
  --pids-limit 256 \
  --security-opt no-new-privileges:true \
  --security-opt seccomp=seccomp-agent.json \
  --cap-drop ALL \
  --cap-add DAC_OVERRIDE \
  -v "${REPO_DIR}/src:/workspace/src" \
  -v "${REPO_DIR}/tests:/workspace/tests:rw" \
  -v "${REPO_DIR}/docs:/workspace/docs:rw" \
  -v "${REPO_DIR}/package.json:/workspace/package.json:ro" \
  -e "NO_COLOR=1" \
  agent-sandbox:latest \
  "$@"

Seccomp Profile for Agent Containers

json
{
  "defaultAction": "SCMP_ACT_ERRNO",
  "comment": "seccomp-agent.json - Restrictive profile for AI coding agents",
  "syscalls": [
    {
      "names": [
        "read", "write", "open", "close", "stat", "fstat", "lstat",
        "poll", "lseek", "mmap", "mprotect", "munmap", "brk",
        "access", "pipe", "select", "sched_yield", "mremap",
        "dup", "dup2", "nanosleep", "getpid", "getuid", "getgid",
        "geteuid", "getegid", "getppid", "getpgrp", "setsid",
        "getgroups", "uname", "fcntl", "flock", "fsync",
        "getcwd", "chdir", "readlink", "chmod", "mkdir",
        "rmdir", "unlink", "rename", "symlink", "readlinkat",
        "openat", "mkdirat", "newfstatat", "unlinkat", "renameat",
        "faccessat", "pselect6", "ppoll", "set_robust_list",
        "get_robust_list", "epoll_create1", "epoll_ctl", "epoll_wait",
        "eventfd2", "pipe2", "dup3", "pread64", "pwrite64",
        "futex", "clock_gettime", "clock_getres", "exit_group",
        "wait4", "clone", "execve", "arch_prctl", "set_tid_address",
        "exit", "getdents64", "rt_sigaction", "rt_sigprocmask",
        "rt_sigreturn", "ioctl", "writev", "madvise", "getrandom"
      ],
      "action": "SCMP_ACT_ALLOW"
    },
    {
      "names": [
        "socket", "connect", "bind", "listen", "accept",
        "sendto", "recvfrom", "sendmsg", "recvmsg"
      ],
      "action": "SCMP_ACT_ERRNO",
      "comment": "Block all network syscalls"
    },
    {
      "names": ["ptrace", "process_vm_readv", "process_vm_writev"],
      "action": "SCMP_ACT_ERRNO",
      "comment": "Block debugging and process inspection"
    }
  ]
}

Contents

When to Use

Apply these guardrails when:

  • Onboarding AI coding agents into an engineering team for the first time
  • Developers are using Claude Code, Cursor, Copilot, or Codex to generate production code
  • Agents have access to repositories containing secrets, infrastructure configs, or sensitive business logic
  • Your compliance framework (SOC 2, ISO 27001, FedRAMP) requires controls around automated code generation
  • Autonomous or semi-autonomous agents are creating pull requests without direct human typing
  • You need to enforce consistent security policies across multiple agents and team members

Signs you need tighter guardrails:

  • Agents have committed secrets or credentials to version control
  • Agent-generated code has introduced vulnerabilities caught late in the pipeline
  • No clear audit trail distinguishes human-written from AI-generated code
  • Developers are bypassing code review for "simple" agent changes
  • Agents are executing arbitrary shell commands in production-connected environments

Limitations

  • Apply guidance only within authorized scope; test destructive steps in non-production first.
  • Docs-only import: upstream scripts and templates not bundled.

Example

bash
# Read-only first: inventory before any active step.
which <tool> && <tool> --help | head -n 20

Adapted from BagelHole/DevOps-Security-Agent-Skills (MIT); frontmatter, When to Use/Limitations, and safety boundaries added for upstream compliance. Docs-only import: helper scripts and templates not bundled.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ai Coding Agent Guardrails AI skill do?

Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.

Why use Ai Coding Agent Guardrails on TypingMind?

Because you install it once and use it with any model. Ai Coding Agent Guardrails is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ai Coding Agent Guardrails in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/FrancoStino/opencode-skills-collection/tree/main/bundled-skills/ai-coding-agent-guardrails. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ai Coding Agent Guardrails?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ai Coding Agent Guardrails?

As many as you like. As long as a model supports skills, you can use Ai Coding Agent Guardrails with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ai Coding Agent Guardrails AI skill free?

Yes. It is published on GitHub by FrancoStino under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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