How do I install the Meta Knowledge Base Bootstrap skill?

Run npx skillmds@latest add gabrielmoreira/meta-knowledge-base-bootstrap in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Meta Knowledge Base Bootstrap skill do?

Bootstrap a domain knowledge base from a single seed (URL / PDF path / git repo / free-text topic): classify source → ingest with the right tool → persist to memory + xlsx index. It is listed under Data & Analytics on SkillMD.

Is Meta Knowledge Base Bootstrap safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Meta Knowledge Base Bootstrap?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Meta Knowledge Base Bootstrap free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Meta Knowledge Base Bootstrap?

gabrielmoreira (@gabrielmoreira) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Meta Knowledge Base Bootstrap by gabrielmoreira

Name: Meta Knowledge Base Bootstrap
Rating: 4.666666666666667 (3 reviews)
Author: gabrielmoreira

File contents

Knowledge Base Bootstrap (Meta-Skill)

Seed a domain knowledge base in one turn. The pipeline classifies the seed source type (URL / PDF / GIT / TEXT) and ingests it via the multi-search-engine skill, then persists the report and produces an index.

step	kind	skill	what it does
classify	`llm_classify`	—	label the seed as one of `URL / PDF / GIT / TEXT`
ingest	`skill_exec`	`multi-search-engine`	run a DuckDuckGo search (JSON to stdout)
memorize	`tool_call`	— (`memory_save`)	append the ingestion summary to memory
index	`agent`	`xlsx`	write `kb-index.xlsx` with the result table

The classifier is currently informational only — the ingest step always calls multi-search-engine. A previous design routed PDF → pdf-toolkit and GIT → github, but those branches were dropped when the DSL moved to skill_exec. A follow-up will reintroduce per-classification routing once the corresponding bundled skills also expose entrypoint: manifests.

Fallback

If the meta-flow fails: run the classifier prompt manually, then invoke the appropriate ingestion skill, then memory_save the result, then create the xlsx index with openpyxl.

Frequently asked questions

Meta Knowledge Base Bootstrap