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Found 384 Skills
Patterns for Ralph loop tasks. Auto-loaded to provide guidance on completion signals, progress tracking, and iteration patterns. Ralph = autonomous issue-to-merged-PR loop.
Detects Follow-Through Day (FTD) signals for market bottom confirmation using William O'Neil's methodology. Dual-index tracking (S&P 500 + NASDAQ) with state machine for rally attempt, FTD qualification, and post-FTD health monitoring. Use when user asks about market bottom signals, follow-through days, rally attempts, re-entry timing after corrections, or whether it's safe to increase equity exposure. Complementary to market-top-detector (defensive) - this skill is offensive (bottom confirmation).
6 buying signals ranked by purchase correlation - Former Customers, New Leadership, High-Intent Website, Tech Stack Change, Expansion, and Hiring/Downsizing. Use when prioritizing outreach, building signal-based campaigns, or setting up intent tracking.
Documentation and commit specialist. Runs after ralph subagents complete a Priority group. Reviews RALPH_DONE signals, updates progress.md and PRD task checkboxes, and makes one atomic git commit per completed user story. Also writes an implementation summary when the full PRD is done. Use after ralph subagents finish implementing — never during active development.
This skill should be used when the user asks for 'TRX price', 'TRON token price', 'price chart on TRON', 'K-line data for USDT/TRX', 'TRON trade history', 'TRON whale activity', 'large transfers on TRON', 'smart money on TRON', 'TRON DEX volume', or mentions checking real-time prices, candlestick data, trading volume, whale monitoring, or smart money signals on the TRON network. For token search and metadata, use tron-token. For swap execution, use tron-swap.
Crypto Twitter intelligence and alpha research. Search X/Twitter for real-time crypto narratives, trending tokens, yield strategies, smart money signals, and protocol research. Features TweetRank (PageRank-inspired credibility scoring), multi-signal token detection, coordinated raid detection, and dynamic tool discovery for execution suggestions. Solana-first but covers all major chains.
Full-story verification — infers what the user is building, then verifies the complete flow end-to-end: browser → API → data → response. Triggers on dev server start and 'why isn't this working' signals.
Activate this when users need to understand extreme events (bubbles, crashes, mass hysteria, cults, mob behavior), diagnose systemic organizational failures, or assess the risk of multiple psychological/market/institutional forces aligning in the same direction. Typical trigger signals: the phenomenon described by the user "far exceeds what any single factor can explain"; the user attempts to explain an extreme outcome with a single cause; the user is concerned about "multiple adverse factors erupting simultaneously". Not applicable to conventional single-factor decision analysis or assessment of mild incremental changes.
Tracks how competitors position themselves online — scrapes homepages, features, pricing, and blogs to extract messaging, value props, CTAs, and pricing models. Compares against previous snapshots to surface positioning shifts with before/after tracking. Produces messaging matrices, content gap analysis, white space maps, and battlecard inputs. Use when anyone asks about competitor messaging, positioning, website copy, content strategy, or how competitors present themselves. Triggers: "competitor positioning", "messaging comparison", "content gap", "what changed on their site", "competitor homepage", "landing page teardown", "marketing battlecard", "how do they describe their product", "share of voice", "counter-messaging". Do NOT use for business signals like funding/hiring (use competitor-intel), single-company deep dives (use company-deep-dive), or meeting prep (use meeting-prep).
Adapts experiences across cultures and languages — not just translation, but cultural reconception. Part of the Intent design strategy system. When a product enters a new market, everything is in play: information density, navigation patterns, color meaning, icon comprehension, date formats, trust signals, payment flows, and the fundamental assumptions about how people make decisions. Trigger when: planning international expansion, auditing i18n readiness, adapting designs for RTL languages, reviewing cultural assumptions in a design, preparing localization test plans, or when someone says "we need to launch in [country]" and the plan is "just translate it." Also trigger for compliance reviews across markets (GDPR, PIPL, accessibility laws).
Investigate transcription factor binding, cis-regulatory elements, chromatin accessibility, and regulatory variant annotation. Use when asked about TF binding sites, enhancers, promoters, ChIP-seq data, ATAC-seq signals, candidate cis-regulatory elements (cCREs), or the regulatory impact of genomic variants.
Assess chemical and drug toxicity via adverse outcome pathways, real-world adverse event signals, and toxicogenomic evidence. Integrates AOPWiki (AOPWiki_list_aops, AOPWiki_get_aop) for mechanism- level pathway tracing, FAERS for post-market adverse event quantification, OpenFDA for label mining, and CTD for chemical-gene-disease evidence. Produces structured toxicity reports with evidence grading (T1-T4). Use when asked about toxicity mechanisms, adverse outcome pathways, AOP mapping, FAERS signal detection, or chemical-disease relationships for drugs or environmental chemicals.