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Found 42 Skills
Detect patterns, anomalies, and trends in code and data. Use when identifying code smells, finding security vulnerabilities, or discovering recurring patterns. Handles regex patterns, AST analysis, and statistical anomaly detection.
Early rug-risk triage for token launches and small DeFi deployments from public data—liquidity lock and pool events, dev and sniper wallet clustering, contract authority and transfer-risk checks, coordinated exits, and evidence-backed risk scores. Use when the user asks for rug pull detection, pump-and-dump signals, launch red flags, LP removal forensics, or cross-chain profit exit tracing—not for front-running trades, harassing teams, or certifying scams without on-chain proof.
Structured UX evaluation that produces quantitative assessments, identifies specific issues, and routes to the right Intent skill for resolution. Part of the Intent design strategy system. Runs heuristic evaluations, cognitive walkthroughs, anti-pattern detection, and task success analysis. Scores, categorizes, and prioritizes findings — then maps every issue to the skill that fixes it. Trigger on: UX review, design audit, heuristic evaluation, usability assessment, "review this design", "what's wrong with this", "evaluate the experience", "is this accessible", "check for dark patterns", "how good is this UX", "rate this design", "find the problems", or any request to systematically assess the quality of a user experience. This is the diagnostic entry point of the Intent system — the UX doctor that diagnoses issues and refers to specialists.
Advanced error analysis and pattern detection specialist for identifying, analyzing, and preventing software errors
Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.
This skill should be used when the user asks to "rewrite my resume", "fix my resume", "humanize my resume", "make my resume sound human", "clean up my resume bullets", "reword my resume", or wants AI-sounding text in their resume rewritten with annotations explaining each change. Works for all resume and CV types: standard US, federal, academic, legal, medical, consulting, tech, executive, military transition, education, nonprofit, trades, creative, investment banking, and EU/Europass formats. Entry-level through executive.
Perform systematic self-review of code changes before commits using structured checklist. Validates architecture boundaries, code quality, test coverage, documentation, and project-specific anti-patterns. Use before committing, creating PRs, or when user says "review my changes", "self-review", "check my code". Adapts to Python, JavaScript, TypeScript, Go, Rust projects.
This skill should be used when the user asks to "roast my code", "review code brutally", "find code sins", "what's wrong with my code", "shame my code", "critique this code", "find antipatterns", "code quality roast", or wants entertaining but actionable code criticism with severity-ranked fixes. Delivers brutally honest roasts with file:line citations and redemption paths.
Command: sync-testing-skill
Detects anti-patterns and code smells in .NET test suites. Use when the user asks to review test quality, find test smells, identify flaky test indicators, or audit tests for common mistakes. Covers assertion quality, test isolation, naming, flakiness indicators, over-mocking, and structural problems. Works with MSTest, xUnit, NUnit, and TUnit.
Reviews React Flow code for anti-patterns, performance issues, and best practices. Use when reviewing code that uses @xyflow/react, checking for common mistakes, or optimizing node-based UI implementations.
Detect and remove AI-generated markers from Finnish text, making it sound like a native Finnish speaker wrote it. Use when asked to "humanize", "naturalize", or "remove AI feel" from Finnish text, or when editing .md/.txt files containing Finnish content. Identifies 26 patterns (12 Finnish-specific + 14 universal) and 4 style markers.