Next From Knowledge
Paste the following prompt into your AI chat to install this skill:
Please follow https://skillhub.cn/install/skillhub.md to install @user_15292d5a/yjkj-next-from-knowledge.
About this skill
What It Solves
You may already have notes, research summaries, meeting minutes, or knowledge graph outputs, but still lack a clear answer to “what should I do now?” next-from-knowledge is not a passive summarizer. It turns collected knowledge into the next concrete action, a short plan, a decision, a minimal experiment, or the key missing information that would change the call.
How It Works
- Clarify the action target: decide whether the user needs a move, a plan, a decision, an experiment, or a blocking-question list.
- Distill working truths: separate confirmed facts, repeated signals, constraints, assumptions, and open unknowns.
- Find the leverage point: identify the small move that unlocks learning, validates a hypothesis, or moves the project forward.
- Compress into action: recommend one or three high-value moves instead of “collect more information.”
- Mark decision-changing gaps: list only the missing facts that would alter direction, sequencing, commitment level, or ownership.
Its core modes include next action, action plan, decision, experiment, and gap check. The output favors a direct bottom line: first the recommended move, then the supporting evidence, why it comes first, what to avoid for now, and which information would reverse the judgment.
Where It Fits
It does not replace knowledge search, relationship mapping, or note organization. If the input lacks critical facts, it names the gap rather than inventing a conclusion. For high-risk or irreversible decisions, it keeps the distinction between observed facts, inferences, and recommendations explicit.
Use Cases
- After reading competitor research and interview notes, choose whether to validate a feature or define the target user first.
- Turn multiple meeting summaries and discussion points into a 7-day action checklist with priorities.
- Use knowledge graph results to decide which doc to complete, experiment to run, or direction to set.
- From customer feedback notes, extract a smallest test and clear success criteria.
Best For
- Product owners who turn research and meeting conclusions into next moves.
- Researchers organizing customer feedback who need a minimal test and decision gaps.
- Research engineers using knowledge graphs who want to sequence actions from connections.
- Operations leads managing project plans who compress scattered notes into short checklists.
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.
A local wiki knowledge base manager that compiles raw documents into sourced, indexed Markdown pages with wikilinks, query support, and health checks.
DeepDigest turns web pages, PDFs, images, audio, and YouTube videos into layered summaries, key insights, extracted data, rebuilt structure, and optional action recommendations.