meta-knowledge-base-bootstrap

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.