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skill-agentic-initializer

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更新时间2026年6月7日 02:34

Professional bootstrapper for Vercel-style Agentic Repositories using compressed AGENTS.md manifests.

安装

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

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来源

rb1whitney

rb1whitney/agentic-project-factory

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Agentic Initializer (Vercel-Standard)

This skill automates the creation of a high-performance AGENTS.md manifest. Inspired by Vercel's research, it prioritizes "retrieval-led reasoning" over model pre-training by embedding a compressed documentation index directly into the repository root.

Logic Overview

Deterministic Scanning: Scans a designated documentation directory (default: {PROJECT_DIR}/docs/) using {SKILL_DIR}/scripts/scanner.py.
Compressed Indexing: Builds a pipe-delimited 8KB "World Map" that maps paths to documentation files.
Passive Context Delivery: Generates an AGENTS.md that acts as the primary cognitive guide for LLM agents, ensuring they always have access to version-matched documentation.
Retrieval-Led Reasoning: Injects explicit instructions to prefer retrieval from local docs over potentially outdated training data.

Usage

# Initialize a repository with Vercel-style AGENTS.md
python3 {SKILL_DIR}/scripts/logic.py <target_path> <project_name> [docs_dir]

References

See {SKILL_DIR}/references/vercel-agents-md.md for the original research findings by Jude Gao (Next.js/Vercel).

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name	skill-agentic-initializer
description	Professional bootstrapper for Vercel-style Agentic Repositories using compressed AGENTS.md manifests.

Agentic Initializer (Vercel-Standard)

Logic Overview

Deterministic Scanning: Scans a designated documentation directory (default: {PROJECT_DIR}/docs/) using {SKILL_DIR}/scripts/scanner.py.
Compressed Indexing: Builds a pipe-delimited 8KB "World Map" that maps paths to documentation files.
Passive Context Delivery: Generates an AGENTS.md that acts as the primary cognitive guide for LLM agents, ensuring they always have access to version-matched documentation.
Retrieval-Led Reasoning: Injects explicit instructions to prefer retrieval from local docs over potentially outdated training data.

Usage

# Initialize a repository with Vercel-style AGENTS.md
python3 {SKILL_DIR}/scripts/logic.py <target_path> <project_name> [docs_dir]

References

See {SKILL_DIR}/references/vercel-agents-md.md for the original research findings by Jude Gao (Next.js/Vercel).