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GeniusHTX
GitHub creator profile

GeniusHTX

Repository-level view of 9 collected skills across 1 GitHub repositories.

skills collected
9
repositories
1
updated
2026-04-14
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Where the skills live

Top repositories by collected skill count, with their share of this creator catalog and occupation spread.

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Repositories and representative skills

add-admin-api-endpoint
software-developers

Add a new endpoint or endpoints to Ghost's Admin API at `ghost/api/admin/**`.

2026-04-14
turborepo
software-developers

Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.

2026-04-14
add-uint-support
software-developers

Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.

2026-03-23
analytics-events
software-developers

Add product analytics events to track user interactions in the Metabase frontend

2026-03-23
analyze-ci
software-developers

Analyze failed GitHub Action jobs for a pull request.

2026-03-23
clojure-write
software-developers

Guide Clojure and ClojureScript development using REPL-driven workflow, coding conventions, and best practices. Use when writing, developing, or refactoring Clojure/ClojureScript code.

2026-03-23
implementing-jsc-classes-zig
software-developers

Creates JavaScript classes using Bun's Zig bindings generator (.classes.ts). Use when implementing new JS APIs in Zig with JSC integration.

2026-03-23
llm-evaluation
data-scientists-152051

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

2026-03-23
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