Results for “fix”

Debug running Docker containers and Compose services. Use when inspecting container logs, exec-ing into running containers, diagnosing networking issues, checking resource usage, debugging multi-stage builds, troubleshooting health checks, or fixing Compose service dependencies.

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.

Use this skill for reproduction-first debugging, root cause isolation, minimal fixes, regression tests. Trigger when the task involves agent profile work related to Staff Debugger Agent, implementation, audits, debugging, strategy, or validation.

Generate changelog entries and GitHub releases from git history. Categorizes commits into features, fixes, breaking changes, and docs. Supports conventional commits, PR-based grouping, and semantic versioning. Creates formatted CHANGELOG.md entries and GitHub releases.

Generate user-facing release notes from tickets, PRDs, or changelogs. Creates clear, engaging summaries organized by category (new features, improvements, fixes). Use when writing release notes, creating changelogs, announcing product updates, or summarizing what shipped.

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 components and pages for WCAG 2.2 AA accessibility issues and applies practical fixes for touch targets, focus states, contrast, labels, and reduced motion.

Score a UI file's design quality 0-100 against StyleSeed's design language with per-category breakdown, worst offenders, and prioritized fix list.

Diagnose and fix slow MSBuild incremental builds by identifying why targets re-execute unnecessarily, covering common causes like missing Inputs/Outputs, volatile properties, and FileWrites registration.

Audits test code in any language using the academic testsmells.org 19-smell catalog, producing a severity-ranked report with specific locations and actionable fixes.

Detects and fixes common MSBuild anti-patterns in .csproj, .vbproj, .fsproj, .props, .targets, and .proj files, covering Exec misuse, unquoted conditions, hardcoded paths, and more.

Detect and fix code-quality and correctness issues in AEM as a Cloud Service projects locally, without external services or network calls.

Ranks any list of impediments and their countermeasures using a value-stream scoring model (ROI, Cost to Implement, Ease of Deployment, Risk Factor) and a fixed prioritization formula.

Tests authentication and authorization mechanisms in mobile application APIs to identify broken authentication, insecure token management, session fixation, privilege escalation, and IDOR vulnerabilities.

Diagnose SaaS business health across growth, retention, unit economics, and capital efficiency. Use when preparing a business review or prioritizing urgent fixes.

Analyze a screen's visual hierarchy by evaluating entry point, eye flow, weight distribution, and emphasis, then provide actionable fixes.

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.

Scans Python and JavaScript codebases for bugs, security vulnerabilities, code smells, and anti-patterns, producing a prioritized fix list with line numbers, severity ratings, and suggested corrections.

Applies Kelvin Garr's fixed AICA brand identity—black glass, gold circuits, Space Grotesk—and Next.js 14 implementation guide for his personal sites and AICA-branded projects.

Optimize CircleCI configuration for speed, reliability, and maintainability. Use when users ask to improve `.circleci/config.yml`, reduce CI runtime, tune caching/workspaces/parallelism, remove pipeline waste, or fix flaky pipeline behavior caused by configuration choices.

Diagnose Sentry issues without copy-pasting stack traces. Uses the Composio CLI to pull issue details, events, breadcrumbs, and suspect commits, then maps the frames to local source so the agent can propose a fix directly.

Diagnose Sentry issues without copy-pasting stack traces. Uses the Composio CLI to pull issue details, events, breadcrumbs, and suspect commits, then maps the frames to local source so the agent can propose a fix directly.

Use this skill for CI log analysis, local reproduction, root cause isolation, targeted fixes, rerun strategy. Trigger when the task involves programming work related to CI Failure Triage, implementation, audits, debugging, strategy, or validation.

Evidence-first repo execution workflow for ECC. Use when the user wants a command run, a repo checked, a CI failure debugged, or a narrow fix pushed with exact proof of what was executed and verified.

SEO — on-page, technical, structured data, Core Web Vitals, and mobile-first indexing. Use when optimizing a website for search engines, adding meta tags or structured data, fixing Core Web Vitals, or auditing technical SEO.

Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.

Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.

Drive a Genie change test-first through the genie MCP tools, working entirely from the live image (no files). Use when adding behavior or fixing a bug in the image — anything where a test should lead.

Review the current git diff for correctness, security, and performance risks before you commit. Produces severity-ranked findings with the exact file:line and a suggested fix. Pure Claude Code — no MCP, no signup.

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.

Write, create, modernize, or fix comprehensive MSTest unit tests with MSTest 3.x/4.x APIs, covering assertions, data-driven tests, lifecycle, and async patterns.

Investigates bugs, regressions, and crashes by dispatching four parallel read-only sub-agents, then ranks hypotheses and recommends the fastest proof or fix path.

Scan open-source dependencies for known vulnerabilities using Snyk, including CI/CD integration, automated fix PRs, license compliance, and continuous monitoring.