菜单
Use when retrieving from or asking questions against a WeKnora knowledge base via the `weknora` CLI — and especially when unsure whether to use `chat`, `session ask`, or `search chunks` for a given goal.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
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。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/Tencent/WeKnora --skill weknora-rag-search命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Use when driving a WeKnora RAG server through the `weknora` CLI as an agent — authenticating, managing knowledge bases / documents / sessions / agents, running search or chat, or interpreting the CLI's JSON envelopes and exit codes. Read this before any other weknora-* skill.
将 RAG 检索结果、文档块或知识图谱概念转换为 OpenMAIC 互动课程。当用户要求将知识库内容、检索到的文档片段、上传的文档、或知识图谱中的概念批量转换为教学课件/互动课堂时使用此技能。支持纯需求生成、基于 PDF 内容的课程生成、和基于概念图遍历的批量课堂生成。
Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.
正在显示 SKILL.md
基于 SOC 职业分类
| name | weknora-rag-search |
| description | Use when retrieving from or asking questions against a WeKnora knowledge base via the `weknora` CLI — and especially when unsure whether to use `chat`, `session ask`, or `search chunks` for a given goal. |
| metadata | {"tested_against":"v0.10"} |
REQUIRED BACKGROUND: read the weknora-shared skill first (auth, --kb
resolution, the JSON envelope, exit codes, streaming/NDJSON output).
WeKnora gives you several ways to "ask about a knowledge base." Picking the wrong one wastes turns or returns the wrong shape. Use the decision table.
| Your goal | Command | LLM synthesis? | Returns |
|---|---|---|---|
| Natural-language answer grounded in a KB | chat "<q>" --kb <kb> | yes | bounded answer events; --reference adds citations; --verbose adds execution detail |
| Answer via a custom agent (its own KB scope, tools, web search) | session ask --agent <id> "<q>" | yes (+ tools) | bounded answer events; --reference adds citations; --verbose adds execution detail |
| Raw context chunks to reason over yourself (no answer) | search chunks "<q>" --kb <kb> | no | ranked chunk list |
| Which documents match a keyword (title/filename) | search docs "<q>" --kb <kb> | no | document list |
| Find a knowledge base by name | search kb "<q>" | no | KB list |
| Find a past session by title | search sessions "<q>" | no | session list |
chat / session ask.
Want chunks to feed into your own reasoning (e.g. you'll synthesize across
sources) → search chunks. Don't call chat just to read source text.chat vs session ask. chat = plain KB RAG Q&A. session ask --agent <id> = invoke a configured custom agent (it may scope its own KBs, call
tools, do web search). If the user set up an agent for this, prefer it
(weknora agent list to find ids); otherwise chat.chat and session ask return a
data.session_id in default JSON output. Pass --session <id> on the next
call to continue the conversation. In NDJSON mode, read it from init.chat, search chunks, search docs need a KB: pass --kb <id-or-name>, or
set WEKNORA_KB_ID, or weknora link the directory (resolved in that order).
If none resolves it's exit 1 (local.kb_id_required); a bad name is exit 1
(local.kb_not_found). Resolve names with weknora kb list / search kb.
(search kb / search sessions are tenant-wide and take no --kb.)chat / session ask return one buffered JSON envelope with answer
events by default. Add --reference for indexed citations and --verbose
for execution detail; use --format ndjson for raw events or --format text for the live human-readable projection.weknora session stop <session-id> --message <message-id> (session_id from
data.session_id, or from init under --format ndjson).
Re-attach to a stream with weknora session resume <session-id> --message <message-id>.search chunks --limit defaults to 8 (tuned for an LLM context window);
the search docs/kb/sessions lists default to 30. Tune retrieval with
--vector-threshold / --keyword-threshold, or --no-vector/--no-keyword
to disable a channel. Details: references/search-chunks.md.# raw retrieval to reason over
weknora search chunks "retry backoff policy" --kb engineering --limit 12
# grounded answer (human transcript)
weknora chat "How do we handle retries?" --kb engineering --format text
# continue the conversation (session id from data.session_id above)
weknora chat "And the max attempts?" --kb engineering --session sess_abc
# answer via a custom agent
weknora session ask --agent ag_123 "Summarize this quarter's incidents"