homeassistant-ops
Operate a Home Assistant instance via the official REST/WebSocket APIs and backups, with safe plan/apply workflows for bulk, reviewable changes.
Discover Databases skills, compare source repositories and read the instructions for each workflow.
Operate a Home Assistant instance via the official REST/WebSocket APIs and backups, with safe plan/apply workflows for bulk, reviewable changes.
Get a second opinion by bundling a prompt + a curated file set, then asking another powerful LLM for debugging, refactor advice, design checks, or cross-validation.
Use when there are 2+ consecutive failures, repeated errors, or the work feels stuck - pauses implementation, switches to root-cause investigation, gathers evidence, and resumes only after a verified plan and o...
Use when providing exact commands, flags, config keys, file paths, API details, standards, or version-specific behavior - enforces verification via official docs (Context7/web fetch), explicit citations, and ba...
Use when considering switching libraries/tools, changing architecture, or replacing automation with manual workarounds - explains root cause, offers 2-3 options with trade-offs, and requests explicit user choic...
Use when editing an existing codebase and the goal is minimal, standard, and non-invasive changes - prioritizes simplest solution, standard libraries first, and surgical modification without unsolicited refacto...
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source o...
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.
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.