What does the Implementation Runner skill actually do?

It performs the actual coding tasks defined in a chain and records which files were changed and whether the task was completed successfully in the system's analysis context.

Which files does this skill track?

It tracks all files modified during the implementation phase and lists their paths in the 'repo.changedFiles' output signal.

Can this skill call other sub-agents?

No, the Implementation Runner is restricted from calling other skills or sub-agents to ensure it focuses strictly on executing the current implementation task.

How does it handle failed implementation attempts?

If an implementation fails or is deferred, the skill records the specific reason in the 'notes' field, allowing for easier debugging and workflow adjustment.

Implementation Runner

Name: Implementation Runner
Author: munlucky

bymunlucky

Productivity & Workflow

Executes code modifications within a skill chain while systematically tracking implementation status and file changes.

About

The Implementation Runner skill serves as the engine for executing planned code changes within a structured AI workflow. It bridges the gap between analysis and execution by defining change scopes, applying modifications, and maintaining a detailed audit trail of changed files and completion states in the analysis context. This skill is particularly useful for complex development tasks where maintaining state and ensuring task completion visibility are critical for subsequent steps in an automated coding pipeline.

Key Features

Automated tracking of file modifications and change summaries
Comprehensive logging of implementation status including completion and deferral reasons
Structured scope definition based on user requirements and repository context
0 GitHub stars
Real-time state recording in analysisContext for workflow continuity
Isolated execution logic that prevents recursive skill calls for cleaner workflows

Use Cases

Recording audit trails for AI-generated code changes in large-scale repositories
Tracking implementation progress in long-running CI/CD automation scripts
Managing multi-file refactoring tasks within an autonomous coding agent

About

Key Features

Automated tracking of file modifications and change summaries
Comprehensive logging of implementation status including completion and deferral reasons
Structured scope definition based on user requirements and repository context
0 GitHub stars
Real-time state recording in analysisContext for workflow continuity
Isolated execution logic that prevents recursive skill calls for cleaner workflows

Use Cases

Recording audit trails for AI-generated code changes in large-scale repositories
Tracking implementation progress in long-running CI/CD automation scripts
Managing multi-file refactoring tasks within an autonomous coding agent