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Interview the user relentlessly about a plan or design. Use when the user wants to stress-test a plan before building, or uses any 'grill' trigger phrases.

日本語の概要は準備中です。原文の説明を表示しています。

GitHub Actions security review for workflow exploitation vulnerabilities. Use when asked to "review GitHub Actions", "audit workflows", "check CI security", "GHA security", "workflow security review", or review .github/workflows/ for pwn requests, expression injection, credential theft, and supply chain attacks. Exploitation-focused with concrete PoC scenarios.

日本語の概要は準備中です。原文の説明を表示しています。

Migrate test files from `as` type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace `as` in tests, or needs partial test data.

日本語の概要は準備中です。原文の説明を表示しています。

After navigating and interacting in Cursor's built-in browser, use browser_network_requests to audit every fetch/XHR for failures, slowness, duplicate calls, and suspicious payloads. Use for API-heavy pages and after backend or client networking changes.

日本語の概要は準備中です。原文の説明を表示しています。

Keep iterating on code changes until the tests pass, the build succeeds, or linting is clean. Runs in a tight loop of fix → run → check → repeat. Use when you want the agent to autonomously grind through test failures or build errors.

日本語の概要は準備中です。原文の説明を表示しています。

Diagnoses bias, anomalies, and strange-looking results on a specific PostHog experiment. Covers empty / 0-exposure experiments, sample ratio mismatch, identity fragmentation, multi-variant exposure, uneven-split exclusion bias, significance traps (peeking, A/A, Bayesian vs Frequentist), PostHog-vs-SQL discrepancies, and surprises after mid-run edits. Symptom-driven dispatch to the right diagnostic. TRIGGER when: user asks 'is my experiment biased?' or 'why 0 exposures?', references the bias banner, says a variant looks strange / wrong / off, sees significance flipping, notices PostHog numbers disagreeing with their SQL, sees an A/A test showing significance, or reports surprises after mid-run edits. DO NOT TRIGGER when: creating a new experiment (use creating-experiments), only configuring rollout (use configuring-experiment-rollout) or metrics (use configuring-experiment-analytics), or only asking lifecycle questions (use managing-experiment-lifecycle).

日本語の概要は準備中です。原文の説明を表示しています。

Explore and diagnose a PostHog endpoint's execution logs — error messages, failed runs, cache misses, slow runs, or unexpected row counts during endpoint invocations. Use when the user says "my endpoint is failing", "show me the logs for endpoint X", "what error did endpoint Y produce", "why did endpoint Z return no rows", "is this endpoint hitting cache", or "check the last N runs". Focused on a single named endpoint's runtime log entries, not project-wide auditing or query performance profiling.

日本語の概要は準備中です。原文の説明を表示しています。

Guides agents through the 3-step experiment creation flow: defining the hypothesis, configuring rollout, and setting up analytics. Delegates rollout decisions to configuring-experiment-rollout and metric setup to configuring-experiment-analytics. TRIGGER when: user asks to create a new experiment or A/B test, OR when you are about to call experiment-create. DO NOT TRIGGER when: user is updating an existing experiment, managing lifecycle, or only browsing experiments.

日本語の概要は準備中です。原文の説明を表示しています。

Toggle between light and dark mode in Cursor's browser, screenshot both states, and flag missing token mappings or contrast issues.

日本語の概要は準備中です。原文の説明を表示しています。

Diagnose why a PostHog endpoint is slow or expensive and propose a concrete fix — bump the cache TTL, enable materialisation, restructure variables, or rewrite the query. Use when the user says "this endpoint is slow", "my endpoint times out", "we're hitting the cost cap on this one", or asks "should I materialise this?". Focuses on a single named endpoint, not a project-wide audit.

日本語の概要は準備中です。原文の説明を表示しています。

Django access control and IDOR security review. Use when reviewing Django views, DRF viewsets, ORM queries, or any Python/Django code handling user authorization. Trigger keywords: "IDOR", "access control", "authorization", "Django permissions", "object permissions", "tenant isolation", "broken access".

日本語の概要は準備中です。原文の説明を表示しています。

Use Cursor's browser to fill and submit every form in the app with valid and invalid data, verifying validation, error states, and success flows.

日本語の概要は準備中です。原文の説明を表示しています。

Django performance code review. Use when asked to "review Django performance", "find N+1 queries", "optimize Django", "check queryset performance", "database performance", "Django ORM issues", or audit Django code for performance problems.

日本語の概要は準備中です。原文の説明を表示しています。

Resolves a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment ("split test demo", "the File engagement boost experiment", "onboarding retention test", "landing page hero experiment", "pricing experiment"), describes it loosely ("the signup experiment", "my pricing test", "the one with the new checkout"), uses a relative reference ("latest", "most recent", "the one I created yesterday"), filters by status (running, draft, stopped, archived), or otherwise refers to an experiment by anything other than its concrete ID.

日本語の概要は準備中です。原文の説明を表示しています。

Crawl all links in a file or project, test each for a valid HTTP response, report broken ones, and fix or remove them.

日本語の概要は準備中です。原文の説明を表示しています。

Find bugs, security vulnerabilities, and code quality issues in local branch changes. Use when asked to review changes, find bugs, security review, or audit code on the current branch.

日本語の概要は準備中です。原文の説明を表示しています。

Find feature flags that were soft-deleted in the active project within a recent time window. Use when the user asks "what flags were deleted in the last N days", "show me recently deleted feature flags", "who deleted flag X", "audit recent flag deletions", or anything similar. Handles the non-obvious gotcha that system.feature_flags exposes the deleted boolean but does not expose a deletion timestamp — the actual deleted-at time lives in the per-flag activity log and must be cross-referenced.

日本語の概要は準備中です。原文の説明を表示しています。

Set up Playwright end-to-end testing in a project, including test configuration, example tests, and CI integration.

日本語の概要は準備中です。原文の説明を表示しています。

Audit and optimize application performance, including bundle size, rendering, database queries, and Core Web Vitals.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze a repository to generate recommended Claude Code settings.json permissions. Use when setting up a new project, auditing existing settings, or determining which read-only bash commands to allow. Detects tech stack, build tools, and monorepo structure.

日本語の概要は準備中です。原文の説明を表示しています。

Configures the rollout shape of a PostHog experiment — the variant split (50/50, 80/20, A/B/C ratios), the overall rollout percentage that gates how many users enter the experiment, and the disambiguation when a percentage like "roll out to 25%" could mean either. Use when the user mentions a rollout percentage, variant split, or traffic distribution; gives a ratio like 60/40, 70/30, or 80/20; asks "who sees the test variant?"; wants to increase, decrease, or change the rollout or split on a draft or running experiment; weighs equal vs uneven splits; or proposes a mid-experiment split change (often an anti-pattern that needs reset or end-and-restart).

日本語の概要は準備中です。原文の説明を表示しています。

Add feature flags to an application for gradual rollouts, A/B testing, and kill switches using PostHog, LaunchDarkly, or a simple local implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Start the dev server, discover API routes from the codebase, hit every endpoint, and report which ones return errors.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze session replay patterns across experiment variants to understand user behavior differences. Use when the user wants to see how users interact with different experiment variants, identify usability issues, compare behavior patterns between control and test groups, or get qualitative insights to complement quantitative experiment results.

日本語の概要は準備中です。原文の説明を表示しています。