Direktori skill

Temukan skill yang dapat digunakan kembali untuk AI agents.

Cari skill GitHub nyata berdasarkan tugas lalu periksa stars, trust, audit, kategori, dan jalur pemasangan sebelum digunakan.

Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.

Hasil pencarian: hallucinations

Direktori bahasa Inggris

A reusable skill kit for AI agents to generate structurally precise and aesthetically standardized draw.io diagrams across major cloud platforms and BPMN, with declarative layout, stencils, and validation.

620
Stars
84/100
Kepercayaan
Kategori: design-creativeAudit

A Claude Code skill that generates interactive HTML courses from any codebase for non-technical users.

5.2K
Stars
76/100
Kepercayaan
Kategori: developmentAudit

Agent skills for VueUse to help AI agents use Vue Composition utilities efficiently with minimal token usage.

377
Stars
73/100
Kepercayaan
Kategori: coding-agentsAudit

Open-source AI pair programming for desktop: a Mentor + Executor agent cross-check each other's code to catch AI hallucinations. Works with Claude Code, Codex, Gemini & opencode. macOS / Windows / Linux.

339
Stars
67/100
Kepercayaan
Kategori: coding-agentsAudit

Terraform Skill for Claude Code and Codex. LLMs hallucinate a lot with Terraform - TerraShark fixes this. It eliminates hallucinations, is designed for modular and secure code and grounds your IaC in the official Hashicorp Terraform best practices.

301
Stars
70/100
Kepercayaan
Kategori: devopsAudit

Kubernetes Skill for Claude Code and Codex. LLMs hallucinate a lot with K8s - KubeShark fixes this. It eliminates hallucinations and grounds your Kubernetes, Helm etc official best practices.

239
Stars
70/100
Kepercayaan
Kategori: devopsAudit

A library of verifiable AI agent skills for Claude Code, Cursor, VS Code, and Copilot to enforce formal traceability and reduce hallucinations.

51
Stars
69/100
Kepercayaan
Kategori: coding-agentsAudit

Nine quality-canary skills for AI coding agents covering code health, rule completeness, grounding, supply chain, resilience, and drift, with auto-cadence hooks for session start/end.

11
Stars
63/100
Kepercayaan
Kategori: coding-agentsAudit

Leverage hallucinations from Large Language Models (LLMs) for novelty-driven explorations.

590
Stars
64/100
Kepercayaan
Kategori: automationAudit

Recognize, diagnose, and mitigate patterns of context degradation in agent systems. Use when context grows large, agent performance degrades unexpectedly, or debugging agent failures.

33
Stars
64/100
Kepercayaan
Kategori: coding-agentsAudit

Scientific research engine with adversarial review, tree search, and serendipity detection. Use when: exploring hypotheses, validating findings against literature, running computational experiments with quality gates, or hunting for unexpected discoveries. Do NOT use for simple Q&A, code editing, or non-research tasks.

16
Stars
58/100
Kepercayaan
Kategori: researchAudit