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Found 896 Skills
Use when writing ANY test, debugging flaky tests, making tests faster, or choosing Swift Testing vs XCTest. Covers unit tests, UI tests, async testing, test architecture.
Unbounce platform help — landing page builder, Smart Traffic AI optimization, Smart Copy AI copywriting, A/B testing, popups, sticky bars, Dynamic Text Replacement, AMP pages, REST API. Use when landing page built in Unbounce isn't converting, Smart Traffic not improving conversions, A/B test setup in Unbounce, popup or sticky bar not triggering, Unbounce page loads too slowly, choosing between Build vs Experiment vs Optimize plan, connecting Unbounce to CRM or email tool, or Dynamic Text Replacement not working. Do NOT use for general funnel strategy (use /sales-funnel) or general CRO methodology (use /sales-vwo).
Write Prisma Next queries — pick a lane (`db.orm.<Model>` for CRUD and includes, `db.sql.<table>` SQL builder for set-builder shapes the ORM doesn't express), filter / project / sort / paginate, eager-load relations with `.include(...)`, transactions via `db.transaction(...)`, aggregates via `.aggregate(...)`. Use for query, where, select, orderBy, take, skip, include, eager load, first, all, count, aggregate, create, update, delete, upsert, returning, transaction, db.transaction, drizzle-style, kysely-style, prisma client, db.close, script, script won't exit, hangs, close connection, db.end, pool.end, await using. Also covers result consumption (`.all()` is a Thenable — just `await` it; no `collect()` / `toArray()` helper needed), single-consumption semantics (`RUNTIME.ITERATOR_CONSUMED`), aggregate nullability (`count` returns `number`, `sum/avg/min/max` return `number | null` per SQL semantics), and range conditions (chain `.where()` clauses or use `and(...)` — there is no `.between(...)`).
Builds and debugs Letta Code channels, including first-party channel adapters and dynamic user channel plugins under ~/.letta/channels. Use when adding Telegram, WhatsApp, Bluesky, Slack, Discord, or custom channel support; testing channel routing, pairing, MessageChannel, runtime dependencies, or channel plugin manifests.
Scroll-based animations using GSAP ScrollTrigger plugin including pinning, scrubbing, snap points, and parallax effects. Use when creating scroll-driven animations, sticky sections, progress indicators, or parallax scrolling experiences.
Use this skill when you need to test or evaluate LangGraph/LangChain agents: writing unit or integration tests, generating test scaffolds, mocking LLM/tool behavior, running trajectory evaluation (match or LLM-as-judge), running LangSmith dataset evaluations, and comparing two agent versions with A/B-style offline analysis. Use it for Python and JavaScript/TypeScript workflows, evaluator design, experiment setup, regression gates, and debugging flaky/incorrect evaluation results.
Use when implementing end-to-end tests, using Playwright or Cypress, testing user journeys, debugging flaky tests, or asking about "E2E testing", "Playwright", "Cypress", "browser testing", "visual regression", "test automation"
When the user wants to add, optimize, or audit a top announcement bar or sticky banner. Also use when the user mentions "announcement bar," "top banner," "sticky bar," "promo banner," "header banner," "announcement bar design," "sticky header," "promo bar," "urgency banner," or "lead capture bar."
Supports publishing, scheduling, querying, managing, and analyzing posts across 13 social platforms via StoryClaw. Use when the user wants to post to TikTok, Instagram, Facebook, X/Twitter, YouTube, LinkedIn, Threads, Pinterest, Reddit, Bluesky, Telegram, Snapchat, or Google Business Profile. Use cases: (1) Publish or schedule a post with optional media, (2) Query post history or view post details, (3) View post or account analytics (likes, views, followers, reach), (4) Delete a post. Triggers: 帮我发帖, 自动发帖, 定时发帖, 查看帖子, 帖子数据, 观看量, 粉丝数, 账号分析, post to social media, schedule post, social media analytics.
Buy, sell, or redeem YES/NO outcome tokens on Kalshi prediction markets via DFlow. Use when the user wants to bet on an event, place a Kalshi order, take a YES or NO position, exit a Kalshi position, redeem winning outcome tokens after a market resolves, tune priority fees on a PM trade, or build a gasless / sponsored PM flow where the app pays tx / ATA / market-init costs. Covers both the `dflow` CLI and the DFlow Trading API. Do NOT use to discover markets, view positions, stream prices, complete Proof KYC, or for non-Kalshi spot swaps.
Eight-axis judgment code review for the current diff — Correctness, Simplification, Tests, Documentation, Style, Intent, Design/API, Performance (+ Coherence on metadata changes). Five-phase pipeline scope → deterministic tool battery (npx/uvx-preferred, zero-install for the JS + Python majority) → 8 parallel LLM axis reviewers → Haiku validators on sub-80 findings (verbatim rubric, ≥80 threshold) → synthesis with no-silent-drop + Conventional Comments JSONL. Every report closes with "What I did NOT check" (security → /security-review, runtime perf, flaky detection). Opt-in flags `--verify-build`, `--mutation-test`, `--reconcile`, `--apply-safe`. Public-skill posture — zero auto-install, graceful skip on missing native tools.
Audits AI-implemented work for honest completion. Runs independent-evaluator checks against task artifacts, transcripts, tests, CI evidence, requirement-to-test mapping, status front matter, and quality gates; flags skipped tests, weakened assertions, mock-only confidence, snapshot drift, happy-path-only coverage, flaky retries, and status/evidence mismatches. Use when validating completed Compozy tasks, AI-authored PRs, or codex-loop iterations. Do not use for real-user QA, persona/journey testing, exploratory charters, or product usability sessions; use qa-execution for those.