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…entation

  • Add aenvironment-deploy skill for deploying instances and services
  • Add Chinese instance deployment API documentation for AI agents
  • Fix markdownlint issues in all markdown files
  • Include Python implementation reference and parameter quick reference table

…entation

- Add aenvironment-deploy skill for deploying instances and services
- Add Chinese instance deployment API documentation for AI agents
- Fix markdownlint issues in all markdown files
- Include Python implementation reference and parameter quick reference table

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Summary of Changes

Hello @JacksonMei, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the AEnvironment platform by introducing a new Claude Code skill designed to simplify and automate the deployment of sandboxed environments. It provides flexible workflows for deploying both temporary agent instances and persistent application services, backed by detailed documentation and a robust Python library for managing these operations.

Highlights

  • New AEnvironment Deploy Skill: Introduced a new Claude Code skill (aenvironment-deploy) to automate the deployment of sandboxed environment instances and services.
  • Multiple Deployment Workflows: The skill supports three distinct deployment workflows: building images locally, deploying existing images, and deploying already registered environments.
  • Instance and Service Deployment: Facilitates the deployment of both temporary, IP-based "instances" for agents and persistent, domain-based "services" for applications, including optional storage.
  • Comprehensive Documentation: Added extensive documentation covering the new skill's usage, AEnvironment CLI commands, config.json schema, and a troubleshooting guide.
  • Python Operations Library: Included a Python library (aenv_operations.py) providing core functionalities for programmatic interaction with the AEnvironment CLI.

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Changelog
  • .claude/aenvironment-deploy/SKILL.md
    • New documentation for the aenvironment-deploy skill, detailing its purpose, workflows (local build, existing image, registered env), instance vs. service types, parameters, configuration, access, management, examples, error handling, and best practices.
  • .claude/aenvironment-deploy/references/CLI_COMMANDS.md
    • New reference guide for AEnvironment CLI commands, covering configuration, environment management, instance operations, and service operations.
  • .claude/aenvironment-deploy/references/CONFIG_SCHEMA.md
    • New documentation outlining the config.json schema for AEnvironment environments, including basic structure, key fields, resource requirements, deployment configurations, and versioning guidelines.
  • .claude/aenvironment-deploy/references/TROUBLESHOOTING.md
    • New troubleshooting guide addressing common issues related to installation, configuration, build, environment registration, and deployment within AEnvironment.
  • .claude/aenvironment-deploy/scripts/aenv_operations.py
    • New Python module providing a class AEnvOperations to encapsulate AEnvironment CLI interactions, including methods for configuration, environment lifecycle management (init, build, register), and instance/service deployment and management.
  • .claude/aenvironment-deploy/scripts/deploy_existing_env.py
    • New Python script implementing the "Deploy Existing Environment" workflow (Workflow C) for AEnvironment.
  • .claude/aenvironment-deploy/scripts/deploy_with_existing_image.py
    • New Python script implementing the "Deploy with Existing Image" workflow (Workflow B) for AEnvironment.
  • .claude/aenvironment-deploy/scripts/deploy_with_local_build.py
    • New Python script implementing the "Deploy with Local Image Build" workflow (Workflow A) for AEnvironment.
  • README.md
    • Updated to announce the new "Deploy Skill" and provide a quick guide on its installation and usage within Claude Code.
Activity
  • The pull request introduces a new feature and associated documentation.
  • No specific review comments or progress updates are available in the provided context.
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lgtm

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Code Review

This pull request introduces a new aenvironment-deploy skill, a valuable addition for automating deployments. A critical security vulnerability was identified where the AEnvOperations library leaks sensitive data, including passwords and secrets, to stderr in verbose logs; implementing argument masking for sensitive fields is strongly recommended. Furthermore, the aenv_operations.py script's reliance on parsing human-readable CLI output is fragile, and improvements for more reliable, machine-readable parsing are suggested. Minor issues include a documentation discrepancy and an unused variable.

Comment on lines +282 to +296
# Extract instance info from output
instance_id = "unknown"
ip_address = "unknown"

for line in stdout.split("\n"):
if "id" in line.lower():
parts = line.split()
if len(parts) >= 2:
instance_id = parts[-1]
elif "ip" in line.lower() or "address" in line.lower():
parts = line.split()
for part in parts:
if self._is_valid_ip(part):
ip_address = part

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high

Extracting instance_id and ip_address by parsing the command's standard output is highly unreliable. This approach is sensitive to any changes in the output text, including wording, capitalization, or formatting. A much more robust solution would be for the aenv instance create command to return structured data, like JSON, which can be parsed reliably. This would prevent potential failures where the script might not be able to retrieve critical deployment information.

Comment on lines +335 to +353
# Extract service info from log output and table
service_id = "unknown"
access_url = "unknown"

for line in stdout.split("\n"):
# Look for service ID in log line or table
if "service created:" in line.lower():
parts = line.split(":")
if len(parts) >= 2:
service_id = parts[-1].strip().rstrip('[0m')
elif "│ service id" in line.lower():
parts = [p.strip() for p in line.split("│") if p.strip()]
if len(parts) >= 2:
service_id = parts[1]
elif "│ service url" in line.lower():
parts = [p.strip() for p in line.split("│") if p.strip()]
if len(parts) >= 2:
access_url = parts[1]

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high

Similar to create_instance, this function parses human-readable output to get the service_id and access_url. This is very fragile and can easily break if the CLI output changes. The aenv service create command should ideally provide a machine-readable output format (e.g., JSON) to allow for robust parsing of the results.

for attempt in range(retry + 1):
try:
if self.verbose:
print(f"Running: {' '.join(cmd)}", file=sys.stderr)
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security-medium medium

The _run_command method prints the full command being executed to sys.stderr when the verbose flag is enabled. This command can contain sensitive information such as registry passwords (passed via configure_cli) or environment variables (passed via create_instance, create_service, or update_service). If a user runs any of the deployment scripts with the --verbose flag, their credentials and secrets will be logged to the terminal's error stream, which may be captured in CI/CD logs or shared terminal sessions.

To remediate this, implement a masking mechanism to redact sensitive values before logging. For example, you can identify arguments that follow sensitive flags like -e or are part of configuration commands and replace their values with placeholders.

Comment on lines +183 to +186
python -c "from scripts.aenv_operations import AEnvOperations; \
ops = AEnvOperations(); \
ops.configure_cli('owner', 'api-url', 'hub-url'); \
print(ops.list_instances())"
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medium

The placeholders owner, api-url, and hub-url in the example command are a bit vague. For better clarity and consistency with other parts of the documentation, consider using more descriptive placeholders like <owner-name>, <api-service-url>, and <envhub-url>. This will make it easier for users to understand what values they need to provide. A similar issue exists on lines 200-203.

Suggested change
python -c "from scripts.aenv_operations import AEnvOperations; \
ops = AEnvOperations(); \
ops.configure_cli('owner', 'api-url', 'hub-url'); \
print(ops.list_instances())"
python -c "from scripts.aenv_operations import AEnvOperations; \
ops = AEnvOperations(); \
ops.configure_cli('<owner-name>', '<api-service-url>', '<hub-url>'); \
print(ops.list_instances())"

Comment on lines +228 to +244
# Parse environment names from rich table output
envs = []
in_table = False
for line in stdout.split("\n"):
line = line.strip()
# Skip empty lines, headers, and table decorations
if not line or line.startswith("Available") or line.startswith("┏") or \
line.startswith("┃") or line.startswith("┡") or line.startswith("└"):
continue
# Data rows start with │
if line.startswith("│"):
parts = [p.strip() for p in line.split("│") if p.strip()]
if len(parts) >= 2: # name and version
env_name = parts[0]
version = parts[1]
envs.append(f"{env_name}@{version}")

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medium

Parsing the human-readable table output from the aenv list command is very brittle. Any change in the CLI's output formatting, including changes to the box-drawing characters or column spacing, will break this parsing logic. To make this more robust, the aenv CLI should be updated to provide a machine-readable output format, such as JSON (e.g., aenv list --output json). This would allow for reliable parsing and eliminate the need for this complex and fragile string manipulation.


# Parse environment names from rich table output
envs = []
in_table = False
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medium

The variable in_table is initialized to False but is never used anywhere in the list_environments method. It should be removed to improve code clarity and remove dead code.

if "service created:" in line.lower():
parts = line.split(":")
if len(parts) >= 2:
service_id = parts[-1].strip().rstrip('[0m')
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medium

Using rstrip('[0m') to remove ANSI escape codes is not a robust solution, as it only handles one specific escape sequence at the end of the string. Other color codes or text formatting sequences will not be removed. A more reliable approach is to use a regular expression to strip all ANSI escape codes from the string. For example:

import re

clean_text = re.sub(r'\x1B\[[0-?]*[ -/]*[@-~]', '', text_with_ansi)

This would require importing the re module at the top of the file.

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