技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: hallucinations

英文目录

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
信任
分类: design-creative审计

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

5.2K
Stars
76/100
信任
分类: development审计

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

377
Stars
73/100
信任
分类: coding-agents审计

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
信任
分类: coding-agents审计

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
信任
分类: devops审计

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
信任
分类: devops审计

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
信任
分类: coding-agents审计

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
信任
分类: coding-agents审计

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

590
Stars
64/100
信任
分类: automation审计

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
信任
分类: coding-agents审计

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
信任
分类: research审计