A robust validation framework that enforces successful tests, builds, and type checks before an AI agent can declare a task complete.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install verification-checkpoint
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install verification-checkpoint using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Verification Checkpoint AI Agent Skill?
The Verification Checkpoint is a mandatory quality control layer for AI developers utilizing Openclaw Skills. It functions as an automated gatekeeper that intercepts completion claims—triggered by keywords like done, finished, or complete—to perform a rigorous technical audit. This skill ensures that code is not just written, but verified through actual execution and static analysis, preventing the delivery of broken or non-compiling implementations in production-grade environments. By integrating this into your workflow, you ensure that every agent action meets the highest standards of reliability and technical integrity.
Verification Checkpoint AI Agent Skill Use Cases
- Validating bug fixes and feature implementations before the agent submits work.
- Enforcing strict type-checking and linting rules in TypeScript and Python projects.
- Automating local build verification to prevent unnecessary CI/CD failures.
- Ensuring architectural stability during complex refactoring tasks using Openclaw Skills.
How Verification Checkpoint AI Agent Skill Works
- Completion Trigger: The skill monitors for intent signals and keywords like finished, complete, or implementation done.
- Automated Testing: It executes the project's primary test runner, such as npm test or pytest, to ensure no regressions.
- Static Analysis: The skill runs language-specific type-checkers like tsc or mypy to catch logical and type-level inconsistencies.
- Build Validation: It attempts a production-ready build to ensure that all dependencies and configurations are healthy.
- Verified Reporting: It generates a structured report, granting a final verdict only if every validation stage passes successfully.
Verification Checkpoint AI Agent Skill Setup
To deploy this verification logic within Openclaw Skills, ensure your local environment is configured with the necessary toolchains.
# Install verification dependencies for JS/TS
npm install --save-dev typescript eslint
# Install verification dependencies for Python
pip install pytest mypy ruff
Enable the auto_trigger functionality in your skill configuration to allow the agent to automatically start the checkpoint whenever completion keywords are detected.
Verification Checkpoint AI Agent Skill Data Schema & Taxonomy
The Verification Checkpoint skill organizes its output into a standardized report format to ensure clarity for both the developer and the agent.
| Attribute | Description |
|---|---|
| timestamp | The ISO 8601 formatted time of the verification run |
| level | The rigor level applied (1: Minimal, 2: Standard, 3: Full) |
| results | A detailed list of executed commands, their pass/fail status, and duration |
| verdict | The final status (PASS/FAIL) determining if the task is truly complete |
Verification Checkpoint AI Agent Skill Advanced Features
- Scalable Verification Levels: Offers three distinct tiers of validation ranging from L1 for minor typos to L3 for breaking changes and security reviews.
- Seamless Skill Orchestration: Works in tandem with systematic-debug and auto-fix within the Openclaw Skills ecosystem to automatically resolve failures detected during checking.
- Language-Agnostic Command Mapping: Support for custom validation commands across diverse stacks, including TypeScript, Python, and Go.
- Pre-Deployment Quality Gates: Automatically blocks pull request generation or deployment steps if the verification verdict is not a pass.
SKILL.md
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