Analyze one competitor's organic footprint, ranking keywords, content themes, backlinks, and gaps.

Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.

PC and console game development principles. Engine selection, platform features, optimization strategies.

API — System — 2 abstractions. System installation event handlers and use cases.

API — Security & Auth — 53 abstractions. Authentication, API keys, roles, users, teams event handlers and use cases.

API — File Manager — 28 abstractions. File event handlers and use cases.

admin/build-params — 3 abstractions.

ClawWork economic survival protocol — work/learn daily cycle

网络表单填报技能 — 从信息搜集到浏览器填报的完整工作流，确保框架受控组件正确写入、页面切换前暂存、最终提交由用户确认。

内容校准预测循环——打分+盲预测合一 → 发布 → 记录 → T+3d 复盘 → 进化 rubric。本技能负责打分+预测（blind sub-agent + score-only.sh + commit-prediction.sh + 阈值门）与校准闭环；发布记录与数据采集由 published-track 统一管理。

Use for authorized multi-stage attack-path planning and orchestration when a task spans reconnaissance, initial access, privilege escalation, lateral movement, or impact assessment. Route single-stage tasks directly to their specialist skill.

Clone the later half of the current conversation, discarding earlier context to reduce token usage while preserving recent work.

Auto-commit changes after a Spec Kit command completes

Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

Use when planning or documenting KrillinAI cover generation from an original video cover and prompt templates; the current CLI cover command is a reserved/planned surface unless implementation is wired in.

Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.

Review code for bugs, security issues, performance problems, and best practices. Provide actionable feedback.

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

Use only when a focused Sales workflow has selected a present and connected Apollo connector, or the user explicitly asks for Apollo prospecting, enrichment, Company Details, records, sequences, or outbound planning. Apply Apollo v2-specific behavior only after verifying app version 2.0.0 or later.

Create, update, inspect, or repair Data Analytics semantic layers. Use when the user asks to save data context or create a semantic layer that future Data Analytics work can inspect and cite.