Testing and debugging

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Use when implementing any feature or bugfix, before writing implementation code

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.

Use when determining what test coverage ALREADY exists for a specific change (a PR, Jira key, Tech Breakdown doc, Testmo CSV, changed paths, or named component). Triggers on "what's already tested", "does this PR have tests", "what coverage exists for", "is this component covered", or "which behaviors have no test today". This is a backward-looking inventory of existing coverage for a concrete change. Do NOT use it to recommend or decide which new tests to add ("should I add integration tests here", "are unit tests enough"), to design a test strategy or plan, to run or fix existing tests, or to explain testing concepts like the test pyramid or which layers a repo uses — those are all out of scope.

Confirms what a third-party library, remote API, build backend, or scraped document actually does before writing code that depends on it — throwaway probes that run in seconds, permissive clients that forward wrong arguments instead of rejecting them, per-endpoint docs that don't generalize, response shapes that make a "fast path" always-false, fakes that encode your assumption rather than the service's behavior, dry-runs that skip the step that fails, and large inputs that were silently read only in part. Use when integrating a new dependency or endpoint, writing a tolerated-status or error branch, choosing a client argument name, testing against a fake, or reviewing code that asserts an upstream contract.

The protocol behind every investigation skill. Use when AI research must proceed without you: search-plan gate, Fact/Inference/Assumption labels, confidence stacking, diffable outputs.

Compatibility pointer for the canonical postmortem skill.

Use when you need to run all compiler checks (tests, lint, format) before committing. Detects whether TS or Rust code changed and runs the appropriate checks.

Use when adding new error messages to React, or seeing "unknown error code" warnings.

Use when feature flag tests fail, flags need updating, understanding @gate pragmas, debugging channel-specific test failures, or adding new flags to React.

Authors and calibrates Instance AI evaluations that build standalone n8n Agents through Agent Builder. Use when a change under packages/cli/src/modules/agents affects build-agent routing, Agent setup, model or credential selection, tools, MCP servers, integrations, skills, tasks, testing, or user-facing build responses. Requires LangTracer access before authoring so each finished case can be published.

Authors a new Instance AI workflow or Agent eval case — written locally as JSON, calibrated against a real build, then pushed to the LangTracer suite CI runs — build cases, behaviour/process cases, credential cases, and seeded (mid-conversation) cases — with intent-driven expectations. Use when adding or changing an Instance AI eval, or debugging why one is flaky.

Debug failed or wrong-output workflow executions using executions tools. Load when the user reports execution failures, unexpected node output, empty parameter values after a successful run, or a node showing a red or failed expression error.

How to use the `@gate` / `@force-gate` test directives instead of `it.skip` or fake-green skip patterns. Use when a test is known-failing under some test-matrix dimension (dev mode, a bundler, an experimental flag like cacheComponents), when converting `if (isNextDev) return` guards or env-var `describe.skip` branches, when adding a condition to test/lib/gate/conditions.ts, or when keying a fixture's experimental flag on a __NEXT_TEST_AXIS letter. Covers directive choice, condition tiers, the test-axis fixture pattern, pitfalls, and verification commands.

Verify Next.js runtime behavior after editing app code. Use this skill to confirm a change actually works in a running app — not just that it compiles or type-checks. Combines /_next/mcp (Next.js's view) with agent-browser (the browser's view). Requires a running `next dev`.

How to write end-to-end tests using createRouterAct and LinkAccordion. Use when writing or modifying tests that need to control the timing of internal Next.js requests (like prefetches) or assert on their responses. Covers the act API, fixture patterns, prefetch control via LinkAccordion, fake clocks, and avoiding flaky testing patterns.

Cross-model benchmark for gstack skills. (gstack)

Clean fixture tool skill with no forced reads and no mode table.

Use when asked to debug, fix a bug, investigate an error, or do root cause analysis, and when users report errors, stack traces, unexpected behavior, or say something stopped working.

QA-test a website or web app and return a 1-5 quality score (5 = flawless, 1 = broken) with evidence. Use when the user wants to test, QA, evaluate, score, or "check how good" a site, page, flow, or app — including a local dev server (e.g. "qa test localhost:5173", "does the checkout work?", "rate this landing page"). Drives a real Browser Use cloud browser, tunneling localhost automatically.

Query PyTorch CI, GitHub Actions, HUD, Grafana, and infrastructure metrics. Use when users ask about CI duration, job failures, queue times, workflow trends, runner health, dashboard data, or PyTorch infrastructure metrics.

Fetch, analyze, reproduce, and minimize GitHub issue reproductions. Use only when the user asks to check whether a GitHub issue reproduces, minimize a GitHub issue's repro, analyze a GitHub bug report, or scrub/triage a GitHub issue for reproducibility. Do not use for standalone reproduction requests without a GitHub issue.