onewave-ai-claude-skills
claudeComprehensive code review skill that identifies bugs, performance issues, and suggests improvements. Integrates with development workflows for quality assurance.
200 skills
Advanced code review system that spawns three independent agents to review PRs with randomized file order, severity classification, consensus voting, and automatic deduplication.
Plugin dyad-sh-dyad from marketplace cascade-code-testing-code-review in joshuarweaver/cascade-code-testing-code-review. Commands read from the repo's manifest — 1 month ago.
dyad:add-modelsAdd one or more AI models to the language model constants file, researching specs from official docs.
dyad:check-workflowsCheck GitHub Actions workflow runs from the past day, identify severe or consistent failures, and file an issue if actionable problems are found.
dyad:debug-minified-errorMap a minified error stack trace from a production Dyad build back to original source locations using source maps.
dyad:debug-with-playwrightDebug E2E tests by taking screenshots at key points to visually inspect application state.
deep-reviewDeep multi-agent code review run locally — a fleet of parallel finder agents reviews the diff from independent angles, then adversarial verifier agents reproduce each finding before it is reported. Local equivalent of /code-review ultra. Use when the user asks for a deep, thorough, or multi-agent re
dyad:deflake-e2e-from-runRoot-cause flaky or failing E2E tests from a specific CI run by downloading and analyzing the Playwright HTML report (traces, screenshots, errors). Use this when given a GitHub Actions run URL and asked to investigate failures. Diagnose from report artifacts first, then rebuild and rerun the affecte
dyad:deflake-e2e-recent-commitsAutomatically gather flaky E2E tests from recent CI runs on the main branch and from recent PRs by wwwillchen/keppo-bot/dyad-assistant, then deflake them.
dyad:deflake-e2eIdentify and fix flaky E2E tests by running them repeatedly and investigating failures.
dyad:e2e-rebaseRebase E2E test snapshots based on failed tests from the PR comments.
dyad:feedback-to-issuesTurn customer feedback (usually an email) into discrete GitHub issues. Checks for duplicates, proposes new issues for approval, creates them, and drafts a reply email.
dyad:fix-issueCreate a plan to fix a GitHub issue, then implement it locally.
dyad:multi-pr-reviewMulti-agent code review system that spawns three independent Claude sub-agents to review PR diffs. Each agent receives files in different randomized order to reduce ordering bias. One agent focuses specifically on code health and maintainability. Issues are validated using reasoned analysis rather t
dyad:plan-to-issueCreate a plan collaboratively with the user, then convert the approved plan into a GitHub issue.
dyad:pr-fix:ciDiagnose and fix failing CI checks on a pull request from its latest GitHub Actions CI run. Use when PR CI has E2E/Playwright failures, macOS or Windows unit-test failures, or presubmit/type/build failures; analyzes the exact run logs and artifacts, invokes dyad:deflake-e2e-from-run for E2E failures
dyad:pr-fix:commentsRead all unresolved GitHub PR comments from trusted authors and address or resolve them appropriately.
dyad:pr-fixAddress all outstanding issues on a GitHub Pull Request by handling both review comments and failing CI checks.
dyad:pr-pushPublish local work by committing changes, running checks, pushing the branch, and creating or refreshing a GitHub PR with a reviewer-useful description.
dyad:pr-rebaseRebase the current branch on the latest upstream changes, resolve conflicts, and push.
dyad:pr-screencastRecord a visual demonstration of the key feature of this PR using screenshots and add it as a new comment to the PR.
dyad:promote-beta-to-stablePromote the latest pre-release to a stable release by creating a release branch, bumping the version, and pushing.
remember-learningsReview the current session for errors, issues, snags, and hard-won knowledge, then update the rules/ files (or AGENTS.md if no suitable rule file exists) with actionable learnings.
dyad:run-benchmarkRun the app-builder benchmark (benchmarks/app-builder) for one or more models — build the three apps through headless Dyad against neon-sim and the recording proxy, score them (Playwright CUJs + security probes + LLM judge), verify the wire ledger, and regenerate RESULTS.md and the scores page. Use
dyad:swarm-pr-reviewTeam-based PR review using Claude Code swarm. Spawns three specialized teammates (correctness expert, code health expert, UX wizard) who review the PR diff, discuss findings with each other, and reach consensus on real issues. Posts a summary with merge verdict and inline comments for HIGH/MEDIUM is
dyad:swarm-to-planSwarm planning session with PM, UX, and Engineering agents who debate an idea, ask clarifying questions, and produce a detailed spec written to plans/$plan-name.md.
Comprehensive code review skill that identifies bugs, performance issues, and suggests improvements. Integrates with development workflows for quality assurance.
200 skills
AI-powered code review tool providing feedback on code quality, best practices, and potential issues.
20 skills · 1 command · 3 agents · hooks
Claude Code plugin for code review focusing on inclusive design, accessibility, and ethical considerations.
18 skills · 1 agent
Claude Code plugins marketplace focused on code style review and specification-driven development workflows.
18 skills
Skills and tools for comprehensive code review analysis and feedback generation.
16 skills
Automated pull request code review with quality, security, performance, and architecture assessment. Activates on PR review requests or 'review pr' keywords.
12 skills
Matt Pocock's agent skills for real engineering (grilling, spec/ticket flows, TDD, code review, domain modelling and more).
39 skills
Harness-native ECC operator layer - 71 agents, 314 skills, 98 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
200 skills · 98 commands · 71 agents · 1 MCP server · hooks
Comprehensive PR review agents specializing in comments, tests, error handling, type design, code quality, and code simplification
1 command · 6 agents
Tenant-isolated AI teams that plan work, coordinate tasks, recall approved context, and return evidence-backed results
6 skills · 6 commands · 4 agents · 1 MCP server
Perform AI code review on Git diffs — supports workspace changes, branch ranges, and single commits with concurrent per-file analysis, codebase search, and deep context-aware review.
2 commands
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams
6 skills · 7 commands · 4 agents
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