数据与 AI技能

Comprehensive scientific research toolkit with 139 specialized skills for biology, chemistry, medicine, data science, and computational research. Transforms Claude into an AI research assistant with access to scientific databases, analysis tools, and domain-specific workflows.

中文简介正在准备中。当前显示原文说明。

Use when you need to auto-log all tool interactions into a self-organizing vector DB with instant recall. Intercepts interactions, extracts key information, generates embeddings, stores in LanceDB, auto-categorizes, and builds a retrieval index. Inspired by OpenClaw SQLite LCM + summary DAG pattern.

中文简介正在准备中。当前显示原文说明。

Autonomous fixed-budget ML experiment loop — setup, iterative hypothesis testing, git-based keep/discard tracking, and indefinite autonomous execution. Implements the karpathy/autoresearch protocol.

中文简介正在准备中。当前显示原文说明。

Medusa v2 rules and best practices for modular commerce architecture, Workflow SDK, data models, services, and admin customizations.

中文简介正在准备中。当前显示原文说明。

Orchestrate multi-LLM parallel debate and synthesis. Dispatches prompts to available omega CLI wrappers in parallel, collects independent responses, runs anonymized peer review ranking, and synthesizes via a chairman model. Supports collaboration templates, idle watchdog, inter-agent messaging, worktree isolation, and multi-turn sessions. No server required.

中文简介正在准备中。当前显示原文说明。

Specific optimization strategies for Python scripts working with larger-than-memory datasets via Dask.

中文简介正在准备中。当前显示原文说明。

Independent LLM judge evaluates task completion separately from the executing agent, catching false success claims by reviewing task goal, actions taken, final state, and evidence. Produces PASS/FAIL with confidence score and reasoning.

中文简介正在准备中。当前显示原文说明。

Focuses on pandas-specific rules for data manipulation, including method chaining, data selection using loc/iloc, and groupby operations.

中文简介正在准备中。当前显示原文说明。

Transforms vague UI/feature requests into structured, optimized prompts with design system awareness. Use when generating prompts for UI implementation, feature specification, or design-to-code translation. Triggers on tasks requiring prompt refinement, UI specification, or design system integration.

中文简介正在准备中。当前显示原文说明。

Background orchestrator that drains the system-wide cron-actions-queue.jsonl queue safely, preventing LLM context pollution in the primary router.

中文简介正在准备中。当前显示原文说明。

Sets standards for Data Transfer Objects (DTOs), typically records, including parameter validation in compact canonical constructors.

中文简介正在准备中。当前显示原文说明。

Generates architecture, database, and system diagrams using Mermaid syntax. Creates visual representations of system architecture, database schemas, component relationships, data flows, and standalone HTML exports.

中文简介正在准备中。当前显示原文说明。

Data processing expert including parsing, transformation, and validation

中文简介正在准备中。当前显示原文说明。

Specifies best practices, including following RESTful API design principles, implementing responsive design, using Zod for data validation, and regularly updating dependencies. This skill promotes modern coding standards and helps developers write consistent, maintainable code.

中文简介正在准备中。当前显示原文说明。

AI and ML expert covering PyTorch, TensorFlow, Hugging Face, scikit-learn, LLM integration, RAG pipelines, MLOps, and production ML systems

中文简介正在准备中。当前显示原文说明。

Benchmark external agent frameworks, auto-detect source type, scan for prompt injection, and convert findings into a concrete TDD upgrade backlog for agent-studio evolution.

中文简介正在准备中。当前显示原文说明。

Research-backed workflow to refresh existing agent prompts/frontmatter with diff-based risk scoring, TDD gates, and ecosystem validation.

中文简介正在准备中。当前显示原文说明。

LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations

中文简介正在准备中。当前显示原文说明。

Pure-Python knowledge base statistics dashboard. Reads shelf-index and log.md; emits Inventory, Layer distribution, Domain distribution, Recent Activity, and Staleness sections. No agent dispatch. Read-only.

中文简介正在准备中。当前显示原文说明。

Health-check the project knowledge base. Looks for contradictions between files, stale claims that newer sources have superseded, orphan files with no inbound cross-references, important concepts mentioned but lacking their own page, missing cross-references, and data gaps. Returns a structured report; does not auto-fix.

中文简介正在准备中。当前显示原文说明。

Manage the project's layer vocabulary — list allowed layers with file counts, add new layers, or safely remove unused layers. Reads the shelf-index for usage data; writes CLAUDE.md atomically. No agent dispatch.

中文简介正在准备中。当前显示原文说明。

This skill should be used when the user asks to "animate this diagram", "build a flowchart that reveals step by step", "animate an architecture/sequence diagram", "make a chart animate in", "grow the bars / draw the line / count up the number", "show data flowing along a connector", or "turn a static diagram into a guided reveal". Covers SVG, Framer Motion, D3, and Remotion.

中文简介正在准备中。当前显示原文说明。

Strip AI writing patterns from prose across five registers — casual, professional, academic, technical, and narrative. Applies 200+ pattern rules to eliminate predictable LLM tells. Triggers on clean up writing, remove AI slop, edit prose, make this sound less AI.

中文简介正在准备中。当前显示原文说明。

Analyze a repository's type system and generate type-safe DAG execution pipelines with GraphSentry-style certificate verification. This skill should be used when building LLM-driven workflows that need deterministic type safety, when composing typed operations into validated execution graphs, or when adding contract-checked pipeline orchestration to any codebase. Supports Python (Pydantic) and TypeScript (Zod).

中文简介正在准备中。当前显示原文说明。