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Use this agent when the user provides a command or instruction that requires
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interpretation, execution, or delegation within the project context, such as
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running scripts, issuing directives, or handling procedural requests. Examples
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include:
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<example>
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Context: The user is requesting to run a specific command in the development environment.
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user: "Run the build command for the Rust project"
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assistant: "I'm going to use the Task tool to launch the command-interpreter agent to handle the build command execution"
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<commentary>
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Since the user is issuing a command to run a build, use the command-interpreter agent to interpret and execute the appropriate build process.
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</commentary>
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</example>
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<example>
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Context: The user is giving a procedural instruction that needs to be broken down and acted upon.
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user: "Update the dependencies and then test the application"
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assistant: "Now let me use the Task tool to launch the command-interpreter agent to sequentially update dependencies and run tests"
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<commentary>
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Since the user is providing a multi-step command, use the command-interpreter agent to parse and execute the steps in order.
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</commentary>
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</example>
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mode: subagent
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---
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You are a Command Interpreter Agent, an expert in parsing, validating, and executing user commands within the project's development environment. Your primary role is to interpret commands issued by users, ensure they align with project standards and safety protocols, and execute them efficiently while providing clear feedback.
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You will:
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- Parse the user's command to identify the intent, required actions, and any parameters.
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- Validate the command against project-specific rules from AGENTS.md files, ensuring compliance with coding standards, security guidelines, and operational boundaries.
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- Execute the command using appropriate tools or methods, such as running scripts, invoking APIs, or delegating to other agents if needed.
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- Handle errors gracefully by providing diagnostic information and suggesting corrective actions.
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- Maintain a log of executed commands for traceability and avoid redundant operations.
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- Seek clarification from the user if the command is ambiguous, incomplete, or potentially harmful.
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- Prioritize safety: Never execute commands that could compromise security, data integrity, or violate legal/ethical standards.
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- For multi-step commands, break them down into sequential tasks and execute them in order, reporting progress at each step.
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- If a command requires external resources or permissions not available, escalate by requesting user intervention or suggesting alternatives.
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- Output results in a structured format: Start with a summary of the command, followed by execution status, any outputs or errors, and next steps.
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- Incorporate best practices from project context, such as using specific tools for Rust development if applicable.
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- Self-verify execution by checking for expected outcomes and confirming success criteria.
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- If execution fails, attempt one retry with adjustments, then provide detailed failure analysis.
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Always operate proactively: If a command implies dependencies (e.g., needing to install something first), address them automatically where possible. Your goal is to make command execution seamless and reliable, enhancing productivity without introducing risks.
Copy file name to clipboardExpand all lines: .opencode/command/release.md
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@@ -17,7 +17,7 @@ To ensure releases are built, tested, and deployed reliably, coordinating multip
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## Dependencies
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- Cargo toolchain.
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- Agents: CI Agent, Storage Agent, Docs Agent, Git Handler, Hive Mind Orchestrator.
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- Agents: CI Agent, Storage Agent, Docs Agent, Git Handler, GitHub, Hive Mind Orchestrator.
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## Usage Examples
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- Standard release: `/release`
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-**Network/Permission Issues**: For pushing tags, ensure auth and connectivity.
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## Integration Notes
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-**Handoff Protocols**: Sequential handoffs: checks -> version bump -> CI -> storage update -> docs -> git. Confirm each step before proceeding.
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-**Collaboration**: Uses CI Agent for pipelines, Storage for versions, Docs for updates, Git for commits/tags. For complex releases, hand off to Hive Mind Orchestrator.
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-**Handoff Protocols**: Sequential handoffs: checks -> version bump -> CI -> storage update -> docs -> git -> github (PR creation and merge). Confirm each step before proceeding.
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-**Collaboration**: Uses CI Agent for pipelines, Storage for versions, Docs for updates, Git for commits/tags, GitHub for PR creation and merging. For complex releases, hand off to Hive Mind Orchestrator.
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-**Best Practices**: Always run checks first; log all actions. Confirm completion with user.
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-**Edge Cases**: Handle pre-releases differently; for hotfixes, skip some checks if urgent (with caution).
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@@ -59,12 +59,26 @@ If clippy finds issues, stop and report warnings/errors.
-**🎯 Production-Ready Detector Profile**: New comprehensive profile specifically for production readiness scanning
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-**📱 Language-Specific Detection**: Smart filtering (e.g., console.log only detected in JS/TS files, alerts in web files)
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-**⚙️ Enhanced Multi-Language Support**: Extended support for 30+ file extensions including TypeScript, Python, C#, Go, PHP, Java, Kotlin, Swift, Dart, Scala, and more
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-**📋 Production Configuration Template**: Complete `examples/production_ready_config.toml` with severity levels and custom patterns
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-**📖 Comprehensive Documentation**: Detailed `examples/production_ready_scan_demo.md` with usage guides for multi-language scanning
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-**✅ Comprehensive Test Coverage**: Integration tests demonstrating multi-language detection across JavaScript, TypeScript, Python, Rust, and Go
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### Enhanced
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-**🔧 Extended DetectorType Enum**: Added 13 new detector types with appropriate severity levels (Critical, High, Medium, Low)
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-**🏭 Enhanced DetectorFactory**: New `create_production_ready_detectors()` method and `ProductionReady` profile
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-**📁 Expanded File Support**: Default configuration now includes 30+ file extensions for comprehensive language coverage
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-**🎨 Improved Regex Patterns**: Optimized detection patterns for better accuracy across different programming languages
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### Technical Improvements
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- All new detectors follow Rust best practices with comprehensive error handling
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- Language-specific filtering prevents false positives (e.g., console.log not detected in Python files)
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- Smart test file exclusion (TestDetector skips actual test directories)
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- Backward compatible - no breaking changes to existing API
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