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Found 400 Skills
Trigger: Invoked when the target is long-term, the task is complex, resources are temporarily at a disadvantage, or a quick win cannot be achieved in the short term but the task cannot be abandoned; common signals include long-term effort, phased plan, endurance, strategic patience, and the need for phased advancement. English: Trigger when the work is long-horizon, difficult, and unlikely to be won quickly. Use this skill to divide the effort into stages, keep strategic confidence, and accumulate small wins into overall victory.
Join the Degenerate Claw perpetuals trading competition for ACP agents. Trade perps, join the leaderboard, post trading signals, subscribe to agent forums, and interact with the Degenerate Claw platform.
Monitor buyer intent signals across the web including job postings, tech changes, funding rounds, and leadership changes. Alerts when prospects show buying signals and prioritizes "hot" accounts. Use for timing-based prospecting.
Invoke this when users react disproportionately intensely to losing (or about to lose) something, or feel an urgent need to "break even" and fail to cut losses after a loss. Typical trigger signals: sunk cost trap, gambler's doubling down, irrational bidding in auctions, inability to abandon failed projects with heavy resource investment. Not applicable to general investment valuation (use value-assessment) or herd behavior (use misjudgment-checklist).
pytest-django integration testing specialist. Covers all fixtures (db, transactional_db, client, rf, settings, mailoutbox, django_user_model), @pytest.mark.django_db options, DRF APIClient, factory_boy integration, async views, signals, management commands, and multi-database testing. USE WHEN: user mentions "pytest-django", "django test", "@pytest.mark.django_db", asks about "django client fixture", "DRF APIClient", "django signals test", "management command test", "django async view test". DO NOT USE FOR: Non-Django Python tests - use `pytest` or `python-integration`; FastAPI - use `fastapi-testing`; Pure container setup - use `testcontainers-python`
Detecting whether agent iterations are converging toward a stable solution or hitting a ceiling. Covers convergence signals, ceiling detection, non-convergence diagnosis, test pass rate as a convergence metric, and forward progress tracking for large projects. Trigger phrases: "convergence", "is the agent converging", "ceiling detection", "when to stop iterating", "diminishing returns"
Triage mixed game demo and playtest feedback into a prioritized fix brief, weighted evidence summary, and next artifact recommendation. Use when a team has playtest notes, Steam Playtest responses, creator or streamer demo reactions, survey comments, wishlist/context signals, bug lists, or performance findings and needs to decide what to fix first before the next build, festival, or launch beat, even if they only say "sort our playtest feedback", "what should we fix before Next Fest", "players are confused", "streamers bounced off the demo", or "turn these demo notes into priorities".
12-Factor App patterns for deployable applications. Use when configuring environment variables, connecting to backing services, structuring application startup/shutdown, or handling graceful shutdown and process signals. Applies to any deployed application (services, APIs, frontends, workers). Server-specific factors (port binding, concurrency, disposability) apply only to backend services.
Momentum platform help — AI revenue orchestration with automated CRM updates, Slack Deal Rooms, MEDDIC Autopilot, AI coaching, churn signals, and executive briefs. Use when Salesforce fields never get updated after calls, deal rooms in Slack are noisy or disorganized, MEDDIC tracking is inconsistent across reps, post-call action items aren't making it into the CRM, you need churn risk signals from customer conversations, or AI coaching scores don't match what you see on calls. Do NOT use for building outbound sequences (use /sales-cadence) or picking an AI note-taker (use /sales-note-taker).
Single-page SEO audit: deep content quality evaluation using Google's E-E-A-T framework, Helpful Content guidelines, on-page SEO factors, search intent alignment, technical signals, and readability analysis. Fetches GSC performance data for that specific page, crawls the live HTML, evaluates metadata, schema markup, internal linking, content depth, and produces a scored report with actionable fixes. Use this skill whenever the user wants to analyze a specific page or URL — not the whole site. Trigger on: "analyze this page", "audit this URL", "how is this page doing", "evaluate my blog post", "check this landing page", "page SEO", "content quality check", "is this page good enough", "review this page's SEO", "what's wrong with this page", "how can I improve this page", "page analysis", "single page audit", "content audit for [URL]", or any request that names a specific URL/page for SEO evaluation. If the user provides a specific URL (not just a domain), this is likely the right skill — use /seo-analysis for full-site audits instead.
Smart Money analytics on OKX: leaderboard traders, position tracking, trade records, aggregated consensus signals, and signal history. Use this skill when the user asks about 聪明钱, smart money, 牛人榜, leaderboard, top traders, 带单员, lead traders, 交易员排行, trader ranking, trader positions, trader PnL, 交易员持仓, 交易员收益, smart money signal, 聪明钱信号, long/short ratio, 多空比, capital flow, 资金流向, position conviction, 仓位强度, entry price distribution, smart money overview, 聪明钱总览, signal history, 信号历史, trader search, 搜索交易员, who is trading BTC, 谁在交易BTC, recommend traders, 推荐交易员, best traders, top performers.
Analyst consensus snapshot for listed companies via Longbridge — current revenue / EPS / target-price consensus estimates and analyst rating distribution. For revision direction, beat/miss tracking, and PEAD signals use longbridge-earnings-revision. Triggers: "一致预期", "分析师预期", "EPS预测", "目标价", "分析师评级分布", "买入评级", "卖出评级", "一致預期", "分析師預期", "EPS預測", "目標價", "分析師評級分佈", "買入評級", "賣出評級", "analyst consensus", "EPS forecast", "target price", "analyst rating distribution", "buy sell hold", "price target consensus", "TSLA.US consensus", "700.HK analyst estimates".