agent-run-orchestrator
Run section orchestrators to coordinate multi-component workflows. Use when starting work on a section.
Browse published AI skills maintained by mvillmow. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
85Repository stars across indexed skills
1,105Repository forks
340Average repository stars per indexed skill
13Repository stars may repeat across skills from the same repository.
Run section orchestrators to coordinate multi-component workflows. Use when starting work on a section.
Identify and document model hyperparameters from papers. Use when setting up training configurations.
Analyze SIMD usage opportunities in Mojo code. Use to find performance optimization opportunities.
Verify a PR is ready for merge (CI passing, approvals, no conflicts). Use before merging to ensure all requirements met.
Analyze ML model architecture from papers and code. Use when understanding model structure for implementation.
Create API reference documentation from docstrings. Use when documenting public module interfaces.
Measure function performance and compare implementations. Use when optimizing critical code paths.
Process and validate datasets for training. Use when setting up data pipelines.
Validate Mojo syntax against current v0.26.1+ standards. Use to catch syntax errors before compilation.
Identify performance optimization opportunities. Use when improving code efficiency.
Coordinate implementation phase by delegating tasks and ensuring code quality. Use during implementation phase to manage engineer tasks.
Examine code organization and identify structural patterns. Use when reviewing module design or understanding architecture.
Diagnose and fix CI/CD failures by analyzing logs, reproducing locally, and applying fixes. Use when CI checks fail on pull requests.
Retrieve all review comments from a pull request using the GitHub API. Use when you need to see what feedback has been provided on a PR.
Generate fix suggestions based on error patterns and best practices. Use when analyzing failures to get actionable remediation steps.
Measure test coverage and identify untested code. Use when assessing test completeness.
Execute model training with optimization algorithms. Use when running training loops on datasets.
Check Mojo code for memory safety issues (ownership violations, use-after-free, etc.). Use to catch memory bugs.
Identify code quality issues and anti-patterns. Use when reviewing code for maintainability problems.
Scan code for security vulnerabilities and unsafe patterns. Use before committing sensitive code or in security reviews.
Validate and verify dependencies are available and compatible. Use when setting up environments.
Measure model performance on test datasets. Use when assessing accuracy, precision, recall, and other metrics.
Validate GitHub Actions workflow files for syntax, best practices, and correctness. Use before committing workflow changes or when workflows fail.
Create isolated git worktrees for parallel development. Use when working on multiple issues simultaneously.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.