Wiki Creator Knowledge Base Manager
Paste the following prompt into your AI chat to install this skill:
Install @user_5b28ea14/wiki-creator by following https://skillhub.cn/install/skillhub.md.
About this skill
What It Solves
When documents, meeting notes, or design specs are handed to an LLM, answers often come from ad-hoc fragments: no stable source, repeated concepts scattered, and conflicts silently overwritten. wiki-creator turns this into an auditable local Wiki: raw/ is read-only, the LLM only reads it and compiles pages like pages/<topic>/<slug>.md, each page has a two-sentence summary, claims cite source file and section, and conflicts are written to .conflicts.md for human resolution.
How It Works
It does not rely on vector search. Instead, it treats each complete page as a knowledge unit and uses a two-level index as a symbol table: read index.md to locate topics, then topics/*.md to locate pages, then read the selected page; [[kebab-case-slug]] links support multi-hop reasoning. Core flow:
- First creation: init_wiki.py builds the skeleton, parse_raw.py parses raw/, and the LLM drafts the SCHEMA.md topic list for user review.
- Compilation and indexing: diff.py lists new files, entities are extracted and pages are created, and build_index.py generates the index, backlinks, graph, and manifest.
- Query and health check: queries follow index.md → topics/*.md → pages only, without loading the whole context; lint.py checks isolated pages, dangling links, unsourced claims, and oversized topics.
Updates process only new/changed files via merge, ref-only, or conflict branches; new topics require user confirmation before SCHEMA.md is changed.
Boundaries
It suits project knowledge, product docs, architecture notes, and other scenarios where stable provenance matters. In coding assistants, it defaults to project .wiki-creator/; office agents can use global ~/.wiki-creator/, or override with --root. Do not split one Wiki across roots; keep topic merges, SCHEMA.md changes, and conflict resolution under user control rather than automatic LLM rewriting.
Use Cases
- Store design docs and meeting notes in raw/, then create a sourced Wiki with index and wikilinks.
- Run diff.py after new requirements, compile only affected pages, and route conflicts to .conflicts.md.
- Query architecture concepts via index.md, topics, then page, avoiding full-knowledge-base loading.
- Run lint.py to detect isolated pages, dangling links, unsourced claims, and oversized topics.
Best For
- Product documentation engineers who need to compile scattered design notes and change logs into a sourced Wiki.
- Developers using coding assistants who need project-root index.md, topics, and pages with reliable reference chains.
- Product managers reviewing knowledge quality who need to audit unsourced claims, conflicts, and topic misclassification.
- Technical writers using LLM Q&A who need to query the local Wiki before deciding whether to use WebSearch.
Related Skills
Search Huawei Cloud official docs and product pages to find ECS, OBS, RDS, CCE product specs, parameters, documentation, and API references without login.
OCR-based recognition for movie, train, flight, and event tickets in images or PDFs, extracting key fields into Markdown or JSON reports.
Turns notes, research, and meeting summaries into actionable next moves, plans, decisions, experiments, and decision-changing gaps.
DeepDigest turns web pages, PDFs, images, audio, and YouTube videos into layered summaries, key insights, extracted data, rebuilt structure, and optional action recommendations.