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Retrieve study, mutation, clinical, and sample data from cBioPortal and turn the results into concise summaries. Use it to browse studies, inspect molecular profiles, or look up mutations for specified genes.
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Build and update Convex backend code, including schemas, queries, authentication, storage, and scheduled jobs. Apply input and output validation, indexed data access, and deployment checks to verify the implementation.
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Detects somatic mutations in circulating tumor DNA using variant callers optimized for low allele fractions with UMI-based error suppression. Reliably detects mutations at VAF above 0.5 percent using consensus-based approaches. Use when identifying tumor mutations from plasma DNA or tracking specific variants.
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Detects somatic mutations in circulating tumor DNA using variant callers optimized for low allele fractions with UMI-based error suppression. Reliably detects mutations at VAF above 0.5 percent using consensus-based approaches. Use when identifying tumor mutations from plasma DNA or tracking specific variants.
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TanStack Query (React Query) v5 best practices for data fetching, caching, mutations, and server state management. Use when building data-driven React applications, setting up query configurations, implementing mutations/optimistic updates, configuring caching strategies, integrating with SSR, or fixing v4→v5 migration errors.
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TanStack Query (React Query) v5 best practices for data fetching, caching, mutations, and server state management. Use when building data-driven React applications, setting up query configurations, implementing mutations/optimistic updates, configuring caching strategies, integrating with SSR, or fixing v4→v5 migration errors.
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Implement React Server Actions in Next.js 14+ for secure, progressively enhanced form handling and server mutations without API routes. Use when handling form submissions, performing server-side mutations, implementing progressive enhancement, creating actions that work without JavaScript, validating data on the server, revalidating cached data after mutations, handling file uploads server-side, implementing optimistic UI updates, or building forms that gracefully degrade without client-side JavaScript.
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Implement and review browser API requests in OpenBot using shared patterns for reading and changing data. Covers cache keys, refreshing stored results after changes, error handling, and how components display request states.
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Hunt fintech-specific GraphQL vulnerabilities: money-movement mutations (transfers, redemptions, withdrawals, card top-ups), ledger/balance/portfolio query IDOR, decimal-precision and rounding abuse, idempotency-key bypass enabling double-spend, KYC/PII field-level authorization gaps, and admin-override mutations reachable via mass assignment. Distinct from hunt-graphql, which owns generic GraphQL discovery and IDOR/mutation methodology — this skill owns the delta introduced when a GraphQL layer sits in front of a ledger, wallet, payments, banking, brokerage, or lending backend, where a resolver bug moves real money instead of just leaking data. Use when hunting a fintech, banking, payments, wallet, neobank, brokerage, or lending target that exposes a GraphQL API, or when a schema/response includes balance, transfer, ledger, redeem, quote, KYC, or account-linking fields.
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Detects somatic mutations in circulating tumor DNA, treating low-VAF detection as a signal-versus-noise problem set by error suppression and molecules sampled, not by the choice of caller. Distinguishes de novo CALLING (scanning a panel for unknown variants, bounded by per-locus error and multiple testing) from tumor-informed DETECTION (tracking a pre-specified variant set, where panel integration reaches single-ppm). Covers VarDict and Mutect2 for de novo calling, UMI-aware callers, and a pysam-based known-variant VAF tracker, with matched-WBC subtraction as the mandatory defense against clonal hematopoiesis (the dominant false positive). Use when calling or tracking tumor mutations from plasma cfDNA, setting a VAF threshold, or deciding whether a low-VAF call is tumor versus CHIP.
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Detects somatic mutations in circulating tumor DNA, treating low-VAF detection as a signal-versus-noise problem set by error suppression and molecules sampled, not by the choice of caller. Distinguishes de novo CALLING (scanning a panel for unknown variants, bounded by per-locus error and multiple testing) from tumor-informed DETECTION (tracking a pre-specified variant set, where panel integration reaches single-ppm). Covers VarDict and Mutect2 for de novo calling, UMI-aware callers, and a pysam-based known-variant VAF tracker, with matched-WBC subtraction as the mandatory defense against clonal hematopoiesis (the dominant false positive). Use when calling or tracking tumor mutations from plasma cfDNA, setting a VAF threshold, or deciding whether a low-VAF call is tumor versus CHIP.
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Expert-level genetics covering Mendelian inheritance, molecular genetics, mutations, linkage analysis, population genetics, epigenetics, and GWAS. Covers classical and modern approaches from Mendel to CRISPR.
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Performs GraphQL introspection attacks to Şunu çıkar: full API schema including types, queries, mutations, subscriptions, and field definitions from GraphQL endpoints. The tester uses introspection queries to map the attack surface, identifies sensitive fields and mutations, tests for query depth and complexity limits, and exploits GraphQL-specific vulnerabilities including batching attacks, alias-based brute force, and nested query DoS. Activates for requests involving GraphQL security testi...
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Build real-time, reactive backend applications with Convex using TypeScript queries, mutations, and actions with automatic reactivity and optimistic updates. Use when building real-time collaborative applications, implementing reactive data synchronization, writing serverless backend functions, creating queries that auto-update, implementing mutations with transactional guarantees, handling file uploads with Convex storage, implementing authentication with Convex Auth, designing reactive database schemas, or building applications requiring instant data synchronization.
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Evaluate whether tests catch defects in business logic, calculations, or state machines. Using Stryker, the skill introduces small code changes, reviews which changes escape detection, and helps strengthen tests where important behavior is insufficiently checked.
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Analyze candidate sites where sugars may attach to proteins, review experimental evidence, and prepare prediction or structural shielding workflows. Supports mutation planning, antibody glycan comparisons, and interpretation of site-specific measurements while distinguishing candidates from confirmed modifications.
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Ask plain-language questions about AWS resources, settings, and costs, and receive readable tables using read-only AWS CLI commands. Inspect services and filter results by region, state, or tags without creating, changing, or deleting resources.
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Find lookalike domains with dnstwist and prioritize suspicious results using DNS records, registration age, and website similarity. The skill also covers monitoring for new findings and producing blocklists and reports to support domain takedown requests.
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Trace application behavior and explain data structures using compact text tree diagrams. The diagrams connect user actions to real functions, data types, state changes, and the components that render again as a result.
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Test and debug REST and GraphQL APIs using curl, httpie, Postman collections, or scripted tests. Check authentication, invalid inputs, pagination, and response details to identify failures that a successful status code alone may miss.
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Check whether the official Obsidian command-line interface is ready, then use it to read and search a selected vault. Access supported backlinks and tags, with direct file reading as a fallback when the interface is unavailable.
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Configure Convex deployment environment variables for secrets such as API keys, read them from application actions, and check the configured values while keeping secrets out of source code and Git.
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Turn plain-language app ideas into Convex backend designs and code. Cover data structure, authentication, live updates, file storage, scheduled tasks, and LLM features, with type checking and deployment verification before treating the backend as complete.
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Assess test strength by introducing deliberate code changes with mewt or muton. Configure test runs, examine changes that tests miss, distinguish harmless equivalents from testing gaps, and investigate potential bugs in the affected code.
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