Learning & Documentation Agent Skills for Zed

Use whenever a hand-written or scanned answer PDF needs transcription to markdown for /grade.

Creates AI-generated videos from text scripts, URLs, or PPT/PDF documents using Visla.

Answer code/product questions as visual Plan artifacts using repo, bridge, or GitHub context; use for API specs, UI look, schema models…

Use when documenting anything visually and didactically — explaining a system, a flow, a protocol, or code so a reader learns it.

Use when performing the close visual and formal analysis that anchors an Art Bulletin article — describing and interpreting composition…

Provides expert guidance on photography, professional video production, animation principles, and social media content creation.

Transforms workflows, standard operating procedures (SOPs), and system screenshots into dense, single-page illustrated user manuals.

Open or create a repo-native visual documentation workspace backed by local Plan MDX files.

Use when a PVLDB paper receives a revision verdict and the response package must be built, covering the one-shot revision rule, the…

Use when reasoning about how PVLDB reviewing actually works, covering the rolling monthly pipeline, the roughly six-week review…

Use when deciding whether a project belongs at VLDB and in which PVLDB category, applying the data-management-primitive test, choosing…

Automates the collection, categorization, and analysis of closed GitHub issues to generate structured technical FAQs for vLLM-ascend…

Generate comprehensive Chinese technical tutorial documents for vLLM features and modules.

Use when drafting or editing release notes for vllm-project/vllm-omni, especially when summarizing changes between tags, organizing…

Define or enforce brand voice, messaging, terminology, tone, and style standards.

AI writing assistant for VMark editor. Use when helping users write, edit, reorganize, or format markdown documents through the VMark MCP…

Tier vocabulary from a text or topic into everyday, academic, and technical categories with teaching priorities.

Reverse-engineer voice profiles from sample content by analyzing writing patterns

Applies a voice profile to transform content.

Combine multiple voice profiles with weighted mixing to create hybrid voices

Generate custom voice profiles from natural language descriptions by mapping tone, formality, and domain to voice dimensions