meta-knowledge-base-bootstrap
Bootstrap a domain knowledge base from a single seed (URL / PDF path / git repo / free-text topic): classify source → ingest with the right tool → p…
它会碰到什么
这一栏是扫描器报的事实，不是结论。命中多不等于有毒（安全工具、规则库、示例脚本本来就会包含危险写法），命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系，需要你自己看。
技能内容
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.
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它属于哪个仓库
src/opensquilla/skills/exp/meta-knowledge-base-bootstrap/SKILL.md