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Create and improve GitHub Actions workflows that automate building, testing, and deployment. The skill covers testing across multiple environments, dependency caching, build output management, and security settings such as limited permissions and protected deployment environments.
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Run three static audits covering architecture alignment, threats, and MCP server policies, permissions, and dependencies. Store timestamped results, track changes across runs, and fail scheduled CI jobs when findings reach a chosen severity.
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Run four cost checks in parallel to assess budget limits, accelerating daily spending, unusual sessions, and projected budget exhaustion. Combine their results into one health status and exit code for automated CI workflows.
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Review custom tabs, menus, lists, and similar controls for required ARIA child roles, which describe interface elements to assistive technology. Identify missing roles and structural wrappers that prevent screen readers from recognizing the items.
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Fix white flashes and blending problems between scenes in HyperFrames videos. This skill explains background setup, overlapping scene containers, final-frame holds, and timeline templates so transitions render with the intended appearance.
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Plan subtitles as layers over a video, deciding which spoken phrases to omit, show normally, or emphasize behind the subject. The guidance preserves full-frame composition and limits large embedded words to occasional key moments.
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Use hosted DNA models to predict gene structures, expression levels, and regions that regulate gene activity. Start from a gene symbol, genomic coordinates, or a DNA sequence, without installing model weights or running a local GPU.
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Analyze price and volume data using trend indicators, overbought and oversold measures, and volume changes. Combine these three perspectives into a single long, short, or stand-aside signal, with adjustable calculation periods and thresholds.
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Analyze public blockchain records to assess crypto market conditions. Combine network activity, large-holder transfers, decentralized finance liquidity, and valuation measures into a report with indicator comparisons, a composite score, and an interpretation of market signals.
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Evaluate investment factors across multiple securities using statistical measures and grouped backtests. Compare how well each factor predicts future returns, examine its consistency over time, and combine useful factors with equal or performance-based weights.
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Recognize classic candlestick patterns using pandas, a Python library for tabular data. Combine bullish and bearish pattern scores into long, short, or stand-aside signals, with adjustable thresholds for candle bodies and shadows.
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Audit a website for visibility in AI search, including how easily its content can be quoted, technical access, content quality, and structured data. Receive a weighted score out of 100 and a prioritized improvement plan.
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Assess security weaknesses in CI/CD systems that automate software builds and delivery. Covering GitHub Actions, Jenkins, GitLab CI, and Azure DevOps, the skill examines unsafe inputs, excessive permissions, exposed credentials, and tampered build outputs, alongside detection and defensive controls.
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Choose, create, and review software diagrams that explain structure, interactions, workflows, states, or data relationships. Select suitable notation and rendering tools, then plan static exports or interactive views with readable layouts, accessible controls, and validation.
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Implement a WebGL transition where a ragged ember edge burns away the old page and reveals the next scene in motion. The skill covers glowing embers, porous char, rendering optimizations, transition timing, and reduced-motion behavior.
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Build falling leaves or petals with visible front-and-back tumbling and sideways motion tied to rotation. Covers 2D canvas and 3D implementations, depth layers, particle density, rendering costs, and reduced-motion support.
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Create a multi-panel research figure from a clear claim and fixed data references, or start from an existing figure. Plan the layout, coordinate panel creation, inspect the composite, and revise affected panels through independent review.
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Analyzes market breadth using Monty's Uptrend Ratio Dashboard data to diagnose the current market environment. Generates a 0-100 composite score from 5 components (breadth, sector participation, rotation, momentum, historical context). Use when asking about market breadth, uptrend ratios, or whether the market environment supports equity exposure. No API key required.
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Quantifies crypto market regime health using free, keyless public data (CoinGecko + Binance funding). Generates a 0-100 composite score across 6 components (100 = risk-on) with a posture recommendation. No API key required. Use when user asks about crypto market conditions, whether it's alt season, BTC dominance, crypto risk-on vs risk-off, funding rates, or whether crypto exposure should be increased or reduced.
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Assesses heuristic market top risk using O'Neil Distribution Days, Minervini Leading Stock Deterioration, and Monty Defensive Sector Rotation. Generates a 0-100 composite score with risk zone classification. Use when user asks about market top risk, distribution days, defensive rotation, leadership breakdown, or whether to reduce equity exposure. Focuses on 2-8 week tactical timing signals for 10-20% corrections.
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Quantifies market breadth health using TraderMonty's public CSV data. Generates a 0-100 composite score across 6 components (100 = healthy). No API key required. Use when user asks about market breadth, participation rate, advance-decline health, whether the rally is broad-based, or general market health assessment.
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Use when the user asks to "audit our brand narrative" or "is this message on-canon"; runs separate typed TALE truth, system, or effectiveness profiles and never averages them into one composite. Checks differentiation, canon, landing consistency, and evidence integrity. Not for launch readiness — use launch-readiness-auditor; not for social operations — use social-quality-auditor. 品牌叙事分层审计/发布前一致性放行
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Build a Says, Thinks, Does, Feels map for one user or segment. Use when sharing user understanding quickly. For a composite archetype with goals and behaviours use `user-persona`; for cross-session themes use `affinity-diagram`.
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Builds, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging or threat detection.
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