Results for “auto-fix”

When reviewing code, generate the complete corrected version — not just the issues, but the exact fixed code ready to copy-paste.

Iterate on a PR until CI passes. Use when you need to fix CI failures, address review feedback, or continuously push fixes until all checks are green. Automates the feedback-fix-push-wait cycle.

Incrementally fixes Gradle build and compilation errors for Android and Kotlin Multiplatform projects.

Iterate on a PR until CI passes. Use when you need to fix CI failures, address review feedback, or continuously push fixes until all checks are green. Automates the feedback-fix-push-wait cycle.

Iterate on a PR until CI passes. Use when you need to fix CI failures, address review feedback, or continuously push fixes until all checks are green. Automates the feedback-fix-push-wait cycle.

Iterate on a PR until CI passes. Use when you need to fix CI failures, address review feedback, or continuously push fixes until all checks are green. Automates the feedback-fix-push-wait cycle.

Creates custom ESLint rules using the ESLint RuleTester API and AST Explorer patterns, generating rule implementations with auto-fix suggestions based on estree node types and scope analysis.

Autonomous error recovery — detect failures, diagnose root cause, apply fixes, and resume without stopping

Session-end auto-extraction of lessons, errors, fixes, and user feedback into structured memory. Fires at session end. Requires consent on first run.

Runs a deep cross-layer consistency audit across a codebase, tracing features from UI to database to find broken wiring, missing handlers, model mismatches, and security gaps, then auto-fixes critical and warning issues.

Interpret n8n validation errors and warnings, guide iterative fixes, and explain validation profiles, error types, and auto-sanitization.

Automates end-to-end QA: starts the app, exercises screens and API endpoints, verifies functionality and design quality, runs domain analysis, and fixes issues found.

Systematically repair a broken feature or module by scoping, tracing dependencies, diagnosing all issues, fixing them in order, and verifying end-to-end.

Executes trivial coding tasks inline without subagent overhead, committing changes atomically.

Automates repeated rounds of Copilot code review on GitHub pull requests: triggers review, triages threads, dispatches parallel fix agents, commits, replies, and loops until convergence.

Autonomously repairs failed task verification by choosing retry, decompose, prune, or escalate strategies before surfacing to the user.

Repairs failed task verification by choosing a strategy: retry with adjustments, decompose into sub-tasks, prune infeasible tasks, or escalate to the user.

Processes a PR's review comments (Copilot or human), classifies them, applies the fixes that belong, replies to each thread, and pushes. Use whenever the user says "address the review", "fix what Copilot said", "handle the comments", mentions Copilot already reviewed a PR, or passes a PR number/URL with pending reviews — or in Spanish "revisá los comentarios", "arreglá lo que dijo Copilot", "atendé el review".

Use when the user asks to fix, debug, or make a specific feature/module/area work end-to-end. Triggers: 'make X work', 'fix the Y feature', 'the Z module is broken', 'focus on [area]'. Not for quick single-bug fixes — this is for systematic deep-dive repair across all files and dependencies.

Reviews and repairs risky or unclear code with minimal validated changes, running a fixed-point loop until the diff is clean across two consecutive review cycles.

Iteratively improves a compiled LaTeX paper through two rounds of external LLM review, fix implementation, and recompilation.

Runs a structured bug-fix pipeline: scouts evidence, diagnoses root cause, applies minimal fixes, and reviews before committing.

Investigate and fix bugs, crashes, null references, and runtime errors in QuizVerse.

This skill should be used when the user wants to "improve a skill", "update skill based on feedback", "optimize skill after use", or says "自更新", "/自更新". Collects user feedback after using a skill and automatically updates that skill with improvements.

Enforce code quality with Ruff in a controlled, iterative workflow: run checks with optional scope and rule overrides, apply safe and unsafe autofixes, review diffs, and resolve remaining findings.

Continuously improves Makepad development skills by capturing reusable patterns, fixing errors, and validating content during development.

Urgent issue classification, root cause analysis, and fast-path routing for production hotfixes

[OMX] Strict autonomous loop: $deep-interview -> $ralplan -> $ultragoal (+ $team if needed) -> $code-review -> $ultraqa

Use when paired-end reads need to be reordered so mates appear consecutively, or when preparing BAM files for featureCounts by adding dummy reads for singletons.

Autopsy a stuck project, extract salvageable artifacts, and route to a fresh start via $bootstrap-repo reset or new-repo bootstrap