Results for “auto-fix”

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Full-cycle AI coding skill: plans, builds, tests, lints, fixes bugs, and writes production-grade docs. Auto-detects project state and adapts its 8-phase pipeline.

Full-cycle AI coding skill: plans, builds, tests, lints, fixes bugs, and writes production-grade docs. Auto-detects project state and adapts its 8-phase pipeline.

Full-cycle AI coding skill: plans, builds, tests, lints, fixes bugs, and writes production-grade docs. Auto-detects project state and adapts its 8-phase pipeline.

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.

Diagnoses and fixes build, type, and runtime errors with minimal changes, covering TypeScript, PyTorch, and other build systems.

Production-grade accessibility skill for WCAG 2.2 AA compliance. Covers auditing, remediation, component authoring, and validation workflows. Auto-invoked for UI implementation, a11y fixes, and accessibility testing.

Production-grade Playwright testing toolkit. Use when the user mentions Playwright tests, end-to-end testing, browser automation, fixing flaky tests, test migration, CI/CD testing, or test suites. Generate tests, fix flaky failures, migrate from Cypress/Selenium, sync with TestRail, run on BrowserStack. 55 templates, 3 agents, smart reporting.

Production-grade Playwright testing toolkit. Use when the user mentions Playwright tests, end-to-end testing, browser automation, fixing flaky tests, test migration, CI/CD testing, or test suites. Generate tests, fix flaky failures, migrate from Cypress/Selenium, sync with TestRail, run on BrowserStack. 55 templates, 3 agents, smart reporting.

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

Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.

Diagnose and fix automatic batching regressions in React 18 class components with a decision tree for setState behavior changes.

Audits an Obsidian wiki for structural issues like orphaned pages, broken wikilinks, stale content, and provenance drift, with optional automated fixes.

Autonomously runs iterative experiment loops to optimize code against a measurable metric. Use when the user wants to improve execution time, memory usage, test pass rate, or any numeric performance goal across repeated experiments — NOT for one-shot bug fixes or simple code review.

Automates app maintenance by assessing health, prioritizing by staleness and debt, and running targeted fix pipelines that commit directly to main.

Scans a codebase for broken links and references, auto-fixes what it can, and flags what needs human review.

Verifies data structures, files, YAML blocks, or agent output against their defined schema, producing a pass/fail report with actionable fix instructions.

Generate, review, fix, and migrate Playwright end-to-end tests with templates, CI integration, and optional TestRail/BrowserStack sync.

Automates the cycle of fixing CI failures, addressing PR review feedback, and pushing changes until all checks pass.

Validate n8n expression syntax and fix common errors when writing {{}} expressions, accessing $json/$node variables, and mapping data between nodes.

Meta-skill codifying the no-wakeup-polling pattern. Describes the ScheduleWakeup anti-pattern, the fix (--auto merge + detached watcher), and when to still use wakeups. Reduces handoff spam by 80%.

Refactors code by removing unused imports, variables, methods, redundant comments, and fixing formatting, with automatic test runs and commits after each step.

Runs a disciplined diagnosis loop for hard bugs and performance regressions, from reproduction through hypothesis testing, instrumentation, fixing, and regression testing.

Generates, reviews, fixes, and migrates Playwright end-to-end tests, with templates, agents, and integrations for TestRail and BrowserStack.

Full pull request lifecycle — create branches, commit changes, open PRs, monitor CI status, auto-fix failures, and merge. Works with gh CLI or falls back to git + GitHub REST API via curl.

Direct TMDL file authoring and BIM-to-TMDL conversion for semantic models in PBIP projects. Automatically invoke when the user asks to "edit TMDL", "add a measure in TMDL", "TMDL syntax", "fix formatString", "fix summarizeBy", "TMDL indentation", "convert BIM to TMDL", "add a column description", "create a calculated column in TMDL", or mentions .tmdl file editing or BIM-to-TMDL migration.

Run the full autonomous engineering pipeline end-to-end (plan, work, code review, test, commit, push, open PR, watch CI, fix CI failures until green). Use only when the user explicitly requests hands-off execution of a software task and provides a feature description; do not auto-route casual conversation here.

Lints agent configuration files for Skills, Hooks, MCP, Memory, and Plugins across 10+ AI tools, flagging issues against 231 validation rules and optionally auto-fixing them.

Proactive self-monitoring of infrastructure, services, and health. Tracks disk/memory/load, service health, cron job status, recent errors. Auto-fixes safe issues. Triggers on: health check, heartbeat, monitor status, service status, infrastructure check.

Behavior-driven development: Discovery → Formulation → Automation. Use when the user wants to build features or fix bugs via Gherkin scenarios and the BDD lifecycle, or mentions BDD/Gherkin/Executable Specifications. Delegates test implementation to /mattpocock:tdd.

Fully autonomous QA testing agent for Modular RAG MCP Server. Reads test cases from QA_TEST_PLAN.md, executes ALL test types automatically without human intervention — CLI commands, Dashboard UI via Streamlit AppTest headless rendering, MCP protocol via subprocess JSON-RPC, provider switches, and data lifecycle checks. Diagnoses failures, applies fixes with up to 3 retry rounds, and records results in QA_TEST_PROGRESS.md. Use when user says 'run QA', 'QA test', 'QA 测试', '执行测试', '跑测试', 'test and fix', or wants to execute QA test plan.

Fully autonomous QA testing agent for Modular RAG MCP Server. Reads test cases from QA_TEST_PLAN.md, executes ALL test types automatically without human intervention — CLI commands, Dashboard UI via Streamlit AppTest headless rendering, MCP protocol via subprocess JSON-RPC, provider switches, and data lifecycle checks. Diagnoses failures, applies fixes with up to 3 retry rounds, and records results in QA_TEST_PROGRESS.md. Use when user says 'run QA', 'QA test', 'QA 测试', '执行测试', '跑测试', 'test and fix', or wants to execute QA test plan.

Audits deployment readiness across CI/CD, containers, monitoring, IaC, secrets, CDN, and DNS, scoring each area and identifying critical gaps, with optional auto-fix via chained sub-skills.

Fully autonomous QA testing agent for Modular RAG MCP Server. Reads test cases from QA_TEST_PLAN.md, executes ALL test types automatically without human intervention — CLI commands, Dashboard UI via Streamlit AppTest headless rendering, MCP protocol via subprocess JSON-RPC, provider switches, and data lifecycle checks. Diagnoses failures, applies fixes with up to 3 retry rounds, and records results in QA_TEST_PROGRESS.md. Use when user says 'run QA', 'QA test', 'QA 测试', '执行测试', '跑测试', 'test and fix', or wants to execute QA test plan.

Trains, evaluates, exports, quantizes, and runs inference for a Grounding DINO model that detects objects described by text prompts without a fixed class vocabulary.