open-knowledge-pack-knowledge-base-research
Investigate a topic against preserved sources and write a provisional research article under `research/` in a Knowledge Base project (the `knowledge-base` starter pack). Read when asked to research a topic, compare options, synthesize sources, gather evidence, or extend an existing research doc. Carries the full procedure: scan existing coverage, agree a research rubric, capture every source verbatim before analyzing, write the article incrementally so a crash never loses work, cite every claim, and link it back into the graph. Does not promote findings to canonical knowledge — that is the sib
npx skills add inkeep/open-knowledge --skill research --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Conduct evidence-driven research on a topic and produce a provisional research article under research/ in a Knowledge Base project. The article is provisional, not canonical, and should capture findings, trade-offs, and open questions at a point in time. It preserves sources verbatim via an ingest workflow and writes the article incrementally so crashes do not lose work. It always cites every claim and links findings back into the graph. It does not promote findings to canonical knowledge on its own.
How it works
- Step 0: Create workflow checkpoint tasks via TaskCreate for each stage (e.g., scan coverage, collaborative scoping, ingest, read/analyze, write article, link Q&A, validate, recap).
- Step 1: Scan existing coverage in the content directory using commands like grep and ls to determine prior work and route. Classify coverage as Fully covered, Partially covered, or Not covered and present routing options accordingly.
- Step 2: Collaborative scoping (Supervised). Propose a rubric structure including the narrowed question, dimensions, candidate sources, success criteria, and output format. In Supervised mode, wait for user confirmation before external fetch; Headless mode auto-confirms and proceeds.
- Step 3: Capture raw sources via ingest for each relevant URL/document, ensuring sources are preserved before analysis.
- Step 4: Read + analyze ingested sources plus existing canonical articles, prior research, relevant code if requested, and project context. Take structured notes including key claims with evidence, trade-offs, contradictions, unknowns, and relevance. Write notes into the article as you go and create the article skeleton before deep reading.
- Step 5: Write the research article (Path A). If the article already exists from Step 4, finalize and tighten it; if starting anew after an interruption, load partial content and fill missing sections. Save the markdown document under the project content directory following the repository’s conventions.
- Step 6–8: Link aggressively, file Q&A back, validate frontmatter and dead links, and provide a recap with follow-up directions.
When to use it
Use Path A (default) to create a persistent provisional article. Use Path B only when the user explicitly requests a direct answer (no doc). Path C is for updating an existing article.
What it can touch
This skill relies on external sources and the knowledge-base project structure. It uses commands and ingest procedures defined by the /open-knowledge platform rules and the project’s ingest workflow. It requires the OpenKnowledge MCP server and skills/tools: Claude Code, Claude Desktop, Claude Cowork, Claude.ai web.
Caveats
Provisional articles are not canonical and require the /consolidate-notes skill to promote findings. All claims must be cited with sources captured via ingest, and the process enforces crash-safety by persisting work incrementally. If a fetch fails, the agent should pause and ask the user to supply the missing source instead of fabricating evidence.
# Research — gather sources and write provisional findings > This skill is pack guidance. The platform `open-knowledge` skill (read/write/preview/linking/grounding rules) still governs every markdown operation — this layers the procedure on top. Conduct **evidence-driven research** on a topic and produce a provisional research article under `research/`. Provisional, not canonical: research article
What does the open-knowledge-pack-knowledge-base-research skill do?
Investigate a topic against preserved sources and write a provisional research article under `research/` in a Knowledge Base project (the `knowledge-base` starter pack). Read when asked to research a topic, compare options, synthesize sources, gather evidence, or extend an existing research doc. Carries the full procedure: scan existing coverage, agree a research rubric, capture every source verbatim before analyzing, write the article incrementally so a crash never loses work, cite every claim, and link it back into the graph. Does not promote findings to canonical knowledge — that is the sib
How do I install it?
Run `npx skills add inkeep/open-knowledge --skill research --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From inkeep/open-knowledge, a repository with 3,279 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.