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Code Remediation with Gomboc.ai Community Edition

作者 Gomboc AI · GitHub ↗ · v0.2.5 · MIT-0
cross-platform ⚠ suspicious
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当前安装
4
版本数
在 OpenClaw 中安装
/install gomboc-security-community
功能描述
Automatically scans and generates deterministic, merge-ready code fixes for infrastructure, app code, and configs using Gomboc.ai's Open Remediation Language.
使用说明 (SKILL.md)

Gomboc Code Remediation Skill

Deterministic, merge-ready code fixes powered by ORL (Open Remediation Language).


Provenance & External Dependencies

Source: This skill wraps the official Gomboc.ai Community Edition code remediation engine.

Official Documentation: https://docs.gomboc.ai
Community Discussions: https://github.com/Gomboc-AI/gomboc-ai-feedback/discussions
GitHub App: https://github.com/apps/gomboc-ai-community

External API Dependency:

Token Scope & Security (Least Privilege):

  • Scope: Read-only API access (minimal required permissions)
  • Capabilities: Query account, scans, runs, and fix events only
  • Restrictions: Cannot modify, delete, or alter Gomboc configurations
  • Safe for CI/CD: No destructive capabilities, suitable for GitHub Actions and workflow secrets
  • Best Practice: Generate a dedicated token per environment/workflow; never commit to code
  • Storage: Use GitHub Secrets (Actions) or CI provider's secure secret management
  • Verification: Check token scope in Gomboc settings before use in production

Shipped Files:

  • SKILL.md — This documentation
  • README.md — Quick start guide
  • SECURITY.md — Security audit
  • scripts/cli-wrapper.py — Python CLI wrapper
  • scripts/docker-compose.yml — MCP server configuration
  • examples/vulnerable.tf — Example vulnerable code
  • references/ — Integration guides

License: MIT (see LICENSE.md)


Gomboc.ai Community Edition automatically scans and fixes code issues across your entire codebase — infrastructure, applications, configurations, and more — using a deterministic remediation engine (no hallucinations). Unlike traditional scanners that generate alerts, Gomboc delivers merge-ready pull requests that clear your code issues backlogs. This skill wraps Gomboc's power into agent workflows, CLI tools, and CI/CD pipelines, making it the perfect complement to agentic coding.

How Gomboc Works

Gomboc's Open Remediation Language (ORL) engine operates through a multi-stage deterministic process:

Policy Definition → Code Analysis → Deterministic Fix Generation → PR Delivery
  1. Understands your environment and code context
  2. Turns policies into executable rules using ORL
  3. Analyzes your code with full syntax-tree precision (via Tree-sitter)
  4. Generates deterministic fixes (same input = same output, always)
  5. Delivers merge-ready pull requests ready to review and ship

Key difference: While generative AI is probabilistic (helpful for reasoning but unpredictable), Gomboc's ORL provides deterministic remediation — predictable, repeatable, and auditable.

What It Does

  • Scan any codebase for issues (infrastructure, application code, configs)
  • Generate deterministic, merge-ready pull requests with fixes
  • Remediate continuously via GitHub Actions or interactive CLI/MCP
  • Trust 94%+ fix acceptance rate with zero hallucinations (ORL Engine)
  • Pair with agents — deterministic remediation that works perfectly alongside agentic coding systems

Supported Languages & Frameworks

ORL supports remediation across multiple languages and code types via syntax-tree matching (Tree-sitter):

  • Infrastructure as Code

    • Terraform (HCL)
    • CloudFormation (YAML/JSON)
    • Kubernetes manifests (YAML)
    • Helm charts
  • Configuration Files

    • JSON, YAML, HCL
    • Shell scripts
    • Docker files
  • Code Languages

    • Python
    • JavaScript/TypeScript
    • Go, Java, C#, Rust, and 20+ more
  • Cloud Providers

    • AWS, Azure, GCP, OCI
    • Kubernetes, Helm
  • Policy Coverage

    • CIS benchmarks
    • AWS best practices
    • Security hardening
    • Custom org policies

Full language list: docker run --rm gombocai/orl language

Quick Start

1. Get a Token

# Sign up at https://app.gomboc.ai (free, Community Edition)
# Generate Personal Access Token in Settings
export GOMBOC_PAT="gpt_your_token"

2. Scan Code

python scripts/cli-wrapper.py scan --path ./src

3. Generate Fixes

python scripts/cli-wrapper.py fix --path ./src

4. Apply Fixes (Optional)

python scripts/cli-wrapper.py remediate --path ./src --commit

Key Features

Deterministic AI — Same fix every time, no hallucinations ✅ 94%+ Accuracy — Merge-ready fixes users actually accept ✅ Free Forever — Community Edition of Gomboc.ai ✅ Production-Ready — Battle-tested implementation ✅ Secure by Design — No token leaking, proper error handling ✅ Agent-Friendly — Perfect for autonomous code improvement loops

CLI Commands

scan

Detect issues in your codebase

gomboc scan path:./terraform
gomboc scan path:./src policy:aws-cis format:markdown

fix

Generate merge-ready fixes

gomboc fix path:./terraform format:pull_request
gomboc fix path:./src format:json

remediate

Apply fixes directly to code

gomboc remediate path:./src commit:true
gomboc remediate path:./terraform commit:true push:true

config

Manage authentication

gomboc config --show-token

Why This Matters for Agents

Gomboc solves the determinism problem in AI-driven code improvement:

  • Deterministic Fixes — ORL ensures same code always produces same fix (no randomness)
  • Repeatable — Policies execute consistently across runs, repos, and teams
  • Trustworthy — 94%+ merge rate because fixes are syntax-aware, not brittle regex patterns
  • Safe for Agents — Agents can autonomously scan → generate → apply without human fear
  • Continuous Improvement — Perfect for agentic loops: code generation → scanning → remediation → iterate

The Agent Workflow:

  1. Agent generates code
  2. Gomboc scans and identifies issues
  3. ORL generates deterministic fixes
  4. Agent reviews and applies fixes
  5. Repeat with next feature/iteration

This creates a feedback loop where agents learn and improve continuously.

Integration Methods

Gomboc integrates into your workflow through multiple paths:

1. VS Code / Cursor IDE (Developers)

Fastest way to try Gomboc interactively:

# Install: Gomboc VS Code Extension
# Set: GOMBOC_PAT in extension settings
# Run: Gomboc: Scan current file
# Review: Problems panel → Apply Fix

2. MCP Server (Agents)

Run the MCP server for agent integration:

docker-compose -f scripts/docker-compose.yml up
# Server runs on http://localhost:3100

# Or: docker run -p 3100:3100 -e GOMBOC_PAT='your_token' gombocai/mcp:latest

Agents interact with Gomboc via MCP protocol:

@gomboc scan path:./src
@gomboc fix path:./src format:pull_request
@gomboc remediate path:./code commit:true

See references/mcp-integration.md for details.

3. CLI Tool (Developers & Scripts)

Use the Python CLI for local scanning:

export GOMBOC_PAT="your_token"
python scripts/cli-wrapper.py scan --path ./src --format markdown
python scripts/cli-wrapper.py fix --path ./src --format pull_request
python scripts/cli-wrapper.py remediate --path ./src --commit

See references/setup.md for detailed instructions.

4. GitHub App (Automated)

Install Gomboc GitHub App for automatic PRs:

5. GitHub Actions (CI/CD)

Automate continuous remediation in pipelines:

- uses: gomboc-action@v1
  with:
    path: ./terraform
    auto-fix: true
    policy: default

See references/github-action.md for configuration.

Configuration

All configuration is via environment variables:

Variable Purpose Required Example
GOMBOC_PAT Personal Access Token Yes gpt_abc123...
GOMBOC_MCP_URL MCP server URL No http://localhost:3100
GOMBOC_POLICY Remediation policy No default or aws-cis

Security & Audit

This skill has been:

  • ✅ Security-audited for token handling
  • ✅ Verified against live Gomboc API
  • ✅ Tested with real vulnerabilities
  • ✅ Confirmed production-ready

See SECURITY.md for complete audit details.

Open Remediation Language (ORL)

ORL is the deterministic execution engine that powers Gomboc fixes:

Deterministic Remediation

  • Same input = same output, always (no probabilistic AI)
  • Syntax-tree aware (via Tree-sitter) instead of brittle regex
  • Safe for bulk remediation across large codebases
  • Results are auditable and reviewable

How ORL Works

  1. Detects policy violations by analyzing syntax trees
  2. Evaluates context and code structure
  3. Applies precise transformations (insert, modify, delete)
  4. Validates fixes are safe and complete

Policy-Driven Fixes

  • Policies define what should be fixed (CIS, AWS best practices, custom rules)
  • ORL rules execute those policies to generate code changes
  • Policy Sets let you customize enforcement by environment/team

See: https://docs.gomboc.ai/orl

Support & Documentation

License

MIT License — See LICENSE file


Ready to remediate? Start with the Quick Start section above, then explore integration methods that fit your workflow.

安全使用建议
This skill appears to be a legitimate wrapper around the Gomboc.ai remediation API and requires a personal access token (GOMBOC_PAT). Before installing: (1) verify the skill's origin/repository and that the package you received actually comes from the official Gomboc project; (2) confirm the .clawhub.yml requirement for GOMBOC_PAT (the registry metadata in the bundle is inconsistent); (3) only provide a dedicated, least-privilege token (do not reuse org-wide or cloud credentials) and store it in your CI secrets manager; (4) inspect and vet the Docker image gombocai/mcp:latest before running docker-compose; (5) run the CLI and any setup scripts in a sandbox or isolated test repo first to confirm behavior; (6) require human review of auto-generated fixes / PRs before merging or enabling auto-commit/push in CI. These checks will reduce risk from misconfiguration or a malicious/compromised upstream image.
能力评估
Purpose & Capability
The SKILL.md, README, and CLI wrapper consistently describe a remediation tool that calls https://api.app.gomboc.ai/graphql using a GOMBOC_PAT token — this is coherent with the stated purpose. However, the top-level registry metadata in the provided bundle listed 'Required env vars: none' and 'Primary credential: none', while .clawhub.yml and the code require GOMBOC_PAT. That metadata mismatch is unexpected and should be resolved (the runtime clearly needs a token).
Instruction Scope
Runtime instructions and the CLI wrapper focus on scanning, requesting fixes, and (optionally) remediating code via the Gomboc API. The scripts read repository files under the provided path and make HTTPS requests to the documented Gomboc GraphQL endpoint. There are no instructions to read unrelated system files or to exfiltrate arbitrary data beyond what the Gomboc API calls would transmit (account and scan/fix info).
Install Mechanism
This is an instruction-only skill (no install spec). It includes code files and a docker-compose that references the Docker image gombocai/mcp:latest. There is no automatic installer, but running the docker-compose will pull a container image from a public registry — validate that image and its provenance before running. No other unusual download URLs or obfuscated installers were found.
Credentials
The actual runtime requires a single sensitive env var (GOMBOC_PAT) used for Bearer authentication to the remote API — appropriate and proportionate for this service. However, the provided registry metadata incorrectly indicates no required env vars; this inconsistency could mislead users and policy engines. Ensure you only provide a dedicated, least-privilege token and do not reuse broader credentials.
Persistence & Privilege
The skill does not request 'always: true' and does not modify other skills or global agent config. It can be invoked by agents (normal default). The code does not contain autonomous installation or privilege-escalation behavior.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install gomboc-security-community
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /gomboc-security-community 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.2.5
- Added a new "Token Scope & Security (Least Privilege)" section detailing API token permissions and usage best practices. - Clarified that tokens grant read-only API access and cannot modify or delete Gomboc configurations. - Provided guidance for secure token management in CI/CD environments (e.g., GitHub Secrets). - No code or functional changes; documentation enhancement only.
v0.2.4
- Version bump to 0.2.4 with no changes to files or functionality. - No updates or modifications were made in this release.
v0.2.3
- Added a new Provenance & External Dependencies section detailing official sources, API endpoints, authentication, and shipped files - Clarified that the skill wraps the official Gomboc.ai Community Edition and pointed to official documentation and discussion links - Improved transparency about external API dependencies and licensing - No functional or code changes; documentation clarified and expanded
v0.2.2
**Expanded integration and documentation, now highlighting ORL deterministic remediation.** - Added .clawhub/origin.json and _meta.json for improved metadata and integration support. - SKILL.md significantly expanded with detailed documentation on Open Remediation Language (ORL) and Gomboc's deterministic remediation approach. - New sections covering supported languages, policy coverage, and supported cloud providers. - Integration methods now include VS Code extension, GitHub App, MCP server, CLI tool, and GitHub Actions. - More examples and clarification for agent workflows and continuous remediation. - Emphasizes ORL’s role in providing safe, repeatable, and auditable code fixes.
元数据
Slug gomboc-security-community
版本 0.2.5
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 4
常见问题

Code Remediation with Gomboc.ai Community Edition 是什么?

Automatically scans and generates deterministic, merge-ready code fixes for infrastructure, app code, and configs using Gomboc.ai's Open Remediation Language. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 100 次。

如何安装 Code Remediation with Gomboc.ai Community Edition?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install gomboc-security-community」即可一键安装,无需额外配置。

Code Remediation with Gomboc.ai Community Edition 是免费的吗?

是的,Code Remediation with Gomboc.ai Community Edition 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Code Remediation with Gomboc.ai Community Edition 支持哪些平台?

Code Remediation with Gomboc.ai Community Edition 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Code Remediation with Gomboc.ai Community Edition?

由 Gomboc AI(@gomboc-ai)开发并维护,当前版本 v0.2.5。

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