测试与 QA
测试、调试、验证和质量工作流
Skills 列表
om-apply-upgrade-notes
Apply the skills collection's UPGRADE_NOTES.md after an upgrade. Re-syncs installed tracker and browser-provider descriptors while preserving local edits, reports custom-provider gaps, checks pipeline config and installed artifacts, and summarizes exactly what changed.
open-mercatoom-auto-continue-pr-loop
Advanced om-auto-continue-pr for PRs started by om-auto-create-pr-loop — claims the PR, resumes from the first non-done PLAN.md Tasks row in an isolated worktree, keeps the per-step commit and checkpoint discipline (integration tests + screenshots for UI), runs the full gate at completion, keeps spec-only design PRs design-only (implementation ships on its own PR via om-auto-implement-spec), and preserves the run-folder and label contract. Use plain om-auto-continue-pr for simple runs.
open-mercatoom-auto-create-pr-loop
Advanced om-auto-create-pr for long, multi-step spec implementations needing resumability and strict step tracking — run folder (PLAN/HANDOFF/NOTIFY), one lean commit per Step, checkpoint verification every ~5 Steps with integration tests and UI screenshots, full gate at completion, ready labeled PR. Resumable via om-auto-continue-pr-loop. Use plain om-auto-create-pr for small fixes.
open-mercatoom-auto-fix-issue
Fix or implement a tracker issue end to end from a single command — takes an issue id or a plain problem description (filed first via om-prepare-issue), classifies, then drives the bug autofix chain (om-verify-in-repo, om-root-cause, om-fix, om-open-pr, om-auto-review-pr, om-auto-qa-pr for UI fixes) or the feature route (spec via om-auto-write-spec, built via om-auto-implement-spec). Isolated worktree, claim protocol, clean stops. Use for "fix issue 123" or a pasted problem description.
open-mercato
speckit-checklist
Generate a custom checklist for the current feature based on user requirements.
dceoy
pydantic
Pydantic is a Python data validation and serialization library, based on type hints. Use this skill whenever you need to do relatively complex data modeling using Pydantic, e.g. when adding constraints, defining a model hierarchy with subclasses, etc.
pydanticspeckit-implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md
dceoyspeckit-clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
dceoyspeckit-specify
Create or update the feature specification from a natural language feature description.
dceoy
technical-analysis
Master of price action, chart patterns, and technical indicators - combining classical Wyckoff/Dow theory with modern quantitative validation for edge identificationUse when "technical analysis, chart pattern, indicator, RSI, MACD, support resistance, trend, candlestick, price action, fibonacci, trading, technical-analysis, charts, indicators, price-action, patterns, support-resistance, trend-following" mentioned.
omer-metin
review-pr
Review a pull request diff and write structured feedback to review.json for the workflow to publish. Use when reviewing a checked-out PR from local artifacts like pr_diff.txt and pr_description.txt and producing machine-readable review output instead of posting directly to GitHub.
warpdotdevfix-errors
Fix compilation errors, linting issues, and test failures in the warp Rust codebase. Covers presubmit checks, WASM-specific errors, and running specific tests. Use when the user hits build errors, clippy or fmt failures, test failures, or needs to run or interpret presubmit before a PR.
warpdotdevimplement-specs
Implement an approved feature from PRODUCT.md and TECH.md, keeping specs and code aligned in the same PR as implementation evolves. Use after the product and tech specs are approved and the next step is building the feature.
warpdotdevcreate-pr
Create a pull request in the warp repository for the current branch. Use when the user mentions opening a PR, creating a pull request, submitting changes for review, or preparing code for merge.
warpdotdevdiagnose-ci-failures
Diagnose CI failures for a PR using the GitHub CLI, extract error logs, and generate a plan to fix them. Use when the user asks to check CI status, pull CI issues, triage test failures, or investigate PR build failures.
warpdotdevpydantic-ai-harness
Extend Pydantic AI agents with batteries-included capabilities from pydantic-ai-harness -- Code Mode (collapse many tool calls into one sandboxed Python execution), a filesystem and shell, sub-agents, planning, context compaction, and more. Use when the user mentions pydantic-ai-harness, CodeMode, Monty, code mode, or tool sandboxing, when they want first-party filesystem/shell/sub-agent/planning/compaction capabilities for a Pydantic AI agent, when they want an agent to run agent-written Python, or when a Pydantic AI agent would benefit from orchestrating multiple tool calls in a single sandboxed script.
pydantic
playwright-automation
Write production-grade Playwright tests in TypeScript: Page Object Model, fixtures, auto-waiting, user-facing locators, parallel execution, CI integration, sharding, and 2025-2026 feature awareness. Includes an explicit "do not" list for AI agents. Use when: "Playwright," "write E2E test," "page object," "new Playwright suite," "Playwright config." Not for: fixing one flaky test at runtime — use test-reliability. Not for: bulk regenerating selectors after a UI refactor — use selector-drift-recovery. Not for: visual baseline creation/management — use visual-testing. Not for: deep WCAG/axe audits — use accessibility-testing. Related: visual-testing, ci-cd-integration, api-testing, test-reliability, selector-drift-recovery, accessibility-testing.
petrkindlmannquantitative-research
World-class systematic trading research - backtesting, alpha generation, factor models, statistical arbitrage. Transform hypotheses into edges. Use when "backtest, alpha, factor model, statistical arbitrage, quant research, systematic trading, mean reversion, momentum strategy, regime detection, walk forward, " mentioned.
omer-metinbuilding-pydantic-ai-agents
Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add tools/capabilities, defer capability loading, stream output, define agents from YAML, or test agent behavior.
pydantic
r3f-materials
Choose and configure React Three Fiber surface materials, PBR, transparency, and transmission. Use for mesh appearance and material cost; use shader guidance for custom GLSL or TSL code.
enzedr3f-physics
Add Rapier rigid bodies, colliders, forces, sensors, and joints to React Three Fiber. Use for collision-driven movement and simulation; use animation guidance for purely visual motion.
enzedr3f-textures
Configure textures in React Three Fiber, including color spaces, UV channels, sampling, video, and render targets. Use for texture appearance or memory issues; use loader guidance for model-loading workflows.
enzed
django-expert
Expert Django backend development guidance. Use when creating Django models, views, serializers, or APIs; debugging ORM queries or migrations; optimizing database performance; implementing authentication; writing tests; or working with Django REST Framework. Follows Django best practices and modern patterns.
vintasoftware
apollo-router-plugin-creator
Guide for writing Apollo Router native Rust plugins. Use this skill when: (1) users want to create a new router plugin, (2) users want to add service hooks (router_service, supergraph_service, execution_service, subgraph_service), (3) users want to modify an existing router plugin, (4) users need to understand router plugin patterns or the request lifecycle. (5) triggers on requests like "create a new plugin", "add a router plugin", "modify the X plugin", or "add subgraph_service hook".
apollographql