浏览 dredd-us 维护的已发布 AI 技能，比较用途与说明，并通过来源仓库了解安装方式。
已收录技能
18收录技能的仓库 Stars 合计
0仓库 Forks
0平均每个技能的仓库 Stars
0同一仓库中的多个技能可能共享 Stars，合计包含重复仓库数据。
Implement AsyncIO patterns for I/O-bound tasks with asyncio.gather, semaphores, and FastAPI async endpoints. Use for concurrent operations, parallel HTTP fetches, rate-limited operations, or async API developme...
Stack prompts in queue while agent runs, minimizing context switches to achieve sustained 6k lines per day output and preserved flow state. Use for heavy coding sessions, iterative refinements, rapid iteration...
Pattern for creating skills with YAML frontmatter that enables progressive disclosure and token optimization. Use when building skills, optimizing context usage, or implementing domain expertise with minimal to...
Scrape external documentation (API references, library docs, protocol specifications) and generate Claude Agent Skills in SKILL.md format. Use when creating skills from documentation, integrating third-party kn...
Central CLAUDE.md file with project guidelines auto-injected into system prompt, achieving 10% accuracy lift in multi-hop reasoning through consistent context. Use for repo-wide context, coding standards enforc...
Format and lint Markdown documents with consistent style, proper heading hierarchy, link validation, and code block formatting. Use when working with Markdown files, documentation, README files, or technical wr...
Integrate external REST and GraphQL APIs with proper authentication (Bearer, Basic, OAuth), error handling, retry logic, and JSON schema validation. Use when making API calls, database queries, or integrating e...
Capture task outcomes, score performance, and derive rules as token priors for continual learning without model weight changes. Use for post-task feedback, experience capture, pattern extraction, and learning f...
Meta-skill to generate new Claude Agent Skills from natural-language descriptions. Use when creating skills, building custom workflows, generating new capabilities, or extending Claude's functionality. Outputs...
Two-phase workflow that generates explicit YAML plan before execution, with approval gates and checkpointing. Use for complex multi-file changes, refactoring, bug fixes with dependencies, or any task where mist...
Route tasks to small model by default, escalate to large model only on low confidence detection, achieving 87% faster learning and 10-30x cost reduction while maintaining accuracy. Use for cost optimization, co...
AI outputs YAML descriptors instead of code, CLI executes deterministically for 100% auditable behavior with zero slop. Use when auditability is critical, generated code review needed, or deterministic executio...
Extract lessons from task failures using Reflector agent, merge insights via Curator pattern, achieving 10% accuracy improvement without context collapse. Use for post-failure analysis, lesson extraction, self-...
Generate and run unit and integration tests using pytest (Python) or Jest (JavaScript) with fixtures, mocks, and async support. Use for test-driven development, code review validation, coverage verification, an...
Auto-detect and load minimal context from Skills folders using progressive disclosure, trimming 1400 tokens from system prompt through metadata-first loading. Use when optimizing token usage, managing multiple...
Convert repeated tasks into versioned skills, track performance gaps, and iteratively polish through Git version control. Use for identifying repeated patterns, improving skill consistency, tracking skill evolu...
Run multiple agent tasks in parallel cloud sandboxes with real-time progress monitoring, achieving 2x throughput vs sequential execution. Use for multi-repo tasks, independent bug fixes, concurrent feature deve...
Query PubMed and scientific databases for protocols, analyze biological data with Biopython, handle HIPAA-compliant data. Use for biology research, protocol searches, sequence analysis, or scientific data handl...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。