Agent skill

Research With Sources

by inkeep in inkeep/open-knowledge

Investigate a topic against preserved sources and write a draft-status research article under research/ in a Knowledge Base project (the knowledge-base starter pack).

GPL-3.0Auto-check passedKnowledge Management

Install Research With Sources

skills CLI
$ npx skills add inkeep/open-knowledge --skill research-with-sources -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install inkeep/open-knowledge research-with-sources --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/inkeep/open-knowledge.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/server/assets/skills/packs/knowledge-base/research .claude/skills/research-with-sources && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
research-with-sources
GitHub stars
4.4k
Token cost
~5.6k tokens
SKILL.md length
2,610 words
Files
1
Skills in repo
18
Repo updated
First seen
Licence
GPL-3.0

At a glance

Investigate a topic against preserved sources and write a draft-status research article under research/ in a Knowledge Base project (the knowledge-base starter pack).

  • Works in 9 steps: Create workflow checkpoint tasks → Scan existing coverage + route → Collaborative scoping (Supervised STOP… → …
  • Tasks that involve Knowledge bases
  • SKILL.md covers Three paths, Autonomy mode, Mandatory execution order and Report framing default:…, plus 11 more sections
  • Calls curl

What it does

Research With Sources is an agent skill from inkeep/open-knowledge. Investigate a topic against preserved sources and write a draft-status 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…

Its SKILL.md is about 5.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Any agent host with the OpenKnowledge MCP server configured. Installed project-local by ok seed --pack knowledge-base.

It sits in Knowledge Management, covering Knowledge bases and Quizzes and assessments. The repository describes itself as: Beautiful, AI-native markdown IDE and LLM wiki. The licence is GPL-3.0.

When your agent uses it

  • Tasks that involve Knowledge bases
  • Tasks that involve Quizzes and assessments

Example prompts

  • “/research-with-sources”

Requirements

  • Compatibility (from SKILL.md): Any agent host with the OpenKnowledge MCP server configured. Installed project-local by `ok seed --pack knowledge-base`.

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Create workflow checkpoint tasks
  2. Scan existing coverage + route
  3. Collaborative scoping (Supervised STOP gate)
  4. Capture raw sources via ingest
  5. Read + analyze
  6. Write the research article (Path A only)
  7. Link aggressively + file valuable Q&A back
  8. Validate
  9. Recap + follow-up directions

What it can do on your machine

Read from SKILL.md and the folder at commit 205b3bd. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use curl, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Any agent host with the OpenKnowledge MCP server configured. Installed project-local by `ok seed --pack knowledge-base`.

    From compatibility in the SKILL.md frontmatter.

Context cost

Research With Sources loads about 5.6k tokens when it runs. Until then it costs about 170 tokens; SKILL.md has 2,610 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~170
When it runs · the whole SKILL.md, loaded when a task matches
~5.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from inkeep/open-knowledge at commit 205b3bd, republished under its GPL-3.0 licence (© inkeep). 2,610 words, ~5,556 tokens.

Download SKILL.mdSave it as .claude/skills/research-with-sources/SKILL.md (or your agent's skills folder).
name
research-with-sources
description
Investigate a topic against preserved sources and write a draft-status 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 sibling `consolidate-notes` skill, after a decision lands.
compatibility
Any agent host with the OpenKnowledge MCP server configured. Installed project-local by `ok seed --pack knowledge-base`.
type
Document
metadata.pack
knowledge-base
metadata.author
Inkeep
metadata.repository
https://github.com/inkeep/open-knowledge-skills

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 articles capture findings, trade-offs, and open questions at a point in time. They are promoted to canonical articles via the /consolidate-notes skill only when decisions solidify.

The content directory is the resolved content.dir — read it with config({ key: 'content.dir' }) if you don't already know it. Paths below are relative to it.

Three paths

  • Path A — Research article (DEFAULT): A persistent provisional article with status: draft and an inline sources: frontmatter list pointing at raw sources captured via the ingest procedure. This is the default unless the user explicitly opts out.
  • Path B — Direct answer: Findings delivered in conversation only. Requires explicit user request (e.g., "just tell me", "no doc needed", "quick answer").
  • Path C — Update existing research: Surgical additions/corrections to an existing research article. Triggered when the user references an existing research doc or says "update/refresh/extend."

Path A is the default because provisional articles compound over time; spoken answers do not.

Legacy reads: Existing articles may use status: provisional and string paths under sources:. Treat those as draft research and source resources. Do not mass-rewrite them; new writes use the OKF shapes below.

Autonomy mode

ModeBehaviorHow entered
Supervised (default)Stop at the scoping gate for user rubric confirmation. Route coverage decisions interactively.Default when a user drives the session.
HeadlessAuto-confirm rubric after proposing it. Auto-select routing decisions. Skip interactive prompts. All other gates (scan, analysis, validation, grounding) still enforced.Explicit "don't wait for me", "just proceed", "run headless" — or non-interactive container environments.

In headless mode, propose the rubric AND proceed immediately. Mark the Scoping task completed after proposing.


Mandatory execution order

Hard gates — do NOT skip ahead. If you find yourself about to run a WebFetch or WebSearch without completing Steps 0-2, STOP — you skipped a gate.

  1. Step 0: Create workflow checkpoint tasks — ALWAYS the first action.
  2. Step 1: Scan existing coverage + route — scan the content directory for prior work; classify coverage; present options before new research begins.
  3. Step 2: Collaborative scoping — propose a research rubric. In Supervised mode, STOP and WAIT for user confirmation before any external fetch.
  4. Step 3: Capture raw sources via ingest — preserve before analyzing.
  5. Step 4: Read + analyze — third-party/external by default; first-party codebase only when the user explicitly requests.
  6. Step 5: Write the research article — Path A only.
  7. Step 6: Link aggressively + file valuable Q&A back.
  8. Step 7: Validate — frontmatter, dead-links, sources alignment.
  9. Step 8: Recap + follow-up directions.

Path B shortcut: If the user explicitly requested a direct answer in Step 2, skip Steps 5 and 7. Steps 0, 1, 3, 4, 6, 8 still apply (evidence discipline doesn't relax just because output is conversational).


Report framing default: external / third-party sources

Research articles default to external framing — investigating third-party topics, technologies, concepts, public repos, papers, official docs. Do NOT mix the user's own codebase analysis into the research article unless the user explicitly asks. Mixing drifts findings from factual synthesis toward opinion-forming applied to the organization, reducing factual fidelity.

  • Default: external sources (web, open-source repos, papers, official APIs).
  • Exception: if the user asks "research how our X compares to Y" or "include our codebase," include it — but clearly separate first-party observations from third-party findings in the article so a reader can distinguish externally-verifiable facts from organization-specific takes.

Persist as you go — the article IS your checkpoint

PERSIST AS YOU GO — crash-safe checkpoint rule. The single most expensive failure this procedure produces is completed research lost to a mid-session rate limit or crash — analysis held in context, never written, discarded when the session died. The user paid for work that vanished. The knowledge base is the checkpoint; two rules make every step crash-safe:

  • Ingest each source the moment you fetch it (Step 3), one at a time — never fetch all sources and ingest them in a trailing batch. An ingested source survives a crash; a fetched-but-unwritten one does not.
  • Create the article skeleton early and fill it section-by-section as you read (Steps 4-5), not in one final write at the end. After you analyze each source, edit its findings into the article before moving to the next. A crash after reading five of eight sources then leaves five sections safely in the KB; you resume by reading the partial article back, not by re-running the whole sweep.

Structured notes that live only in your context are not persisted work. If a finding is worth keeping, it belongs in an ingested source or in the article — written, not held.


Step 0: Create workflow checkpoint tasks

ALWAYS THE FIRST ACTION. Before any read, any scan, any fetch — create tasks. They persist across context compaction, make skipped steps immediately visible, and show progress to the user.

Create these tasks via your host's task system (TaskCreate in Claude; equivalent elsewhere):

TaskCreate: "Research: Scan existing coverage + route"        → start as in_progress
TaskCreate: "Research: Collaborative scoping — rubric gate"   → pending, blocked by #1
TaskCreate: "Research: Capture sources via ingest"            → pending, blocked by #2
TaskCreate: "Research: Read + analyze"                        → pending, blocked by #3
TaskCreate: "Research: Write the research article"            → pending, blocked by #4
TaskCreate: "Research: Link aggressively + file Q&A back"     → pending, blocked by #5
TaskCreate: "Research: Validate (frontmatter + dead-links)"   → pending, blocked by #6
TaskCreate: "Research: Recap + follow-up directions"          → pending, blocked by #7

Use the host's blocked-by relation to enforce ordering. As you complete each step, mark the task completed and the next task in_progress.

Path B variant: If scoping determines Path B (direct answer), drop tasks #5 and #7 — they don't apply.

Path C variant: If Step 1 routes to Path C (update existing), drop tasks #3 and #5 (ingest is usually unnecessary and no new article is created) and rename task #4 to "Research: Read existing article + diff deltas."

Why tasks: the observed failure mode is the agent jumping straight to WebFetch without scanning or scoping. Tasks make the skipped gates obvious to the user mid-session.


Step 1: Scan existing coverage + route

MANDATORY FIRST RESEARCH STEP. Before any external fetch, scan what the knowledge base already holds.

Phase 1: Check existing knowledge

If the user explicitly references an existing research article (names it, links it, says "update/refresh/extend"): → Skip the scan. Go directly to Path C.

Otherwise, always scan first:

  1. exec("grep -rln <topic-keyword> <content-dir>") — returns matching files with frontmatter enrichment so you can judge relevance without opening each.
  2. exec("ls -A <content-dir>") — surfaces folder layout and most-recent-updated doc per subdir.
  3. For the 1-3 most promising candidates, exec("cat <path>") — returns full doc + frontmatter + backlinks + recent shadow-repo activity.

Classify:

CoverageWhat it meansRoute to
Fully coveredAn existing article directly answers the question with evidencePresent findings; offer to elaborate, verify, extend, or explicitly new-report
Partially coveredRelated research exists; the specific question is a natural extensionOffer: (1) extend existing via Path C, (2) new article via Path A
Not coveredNo meaningful overlapProceed to Path A (default) or Path B
Phase 2: Present routing options (Supervised mode)

Fully covered:

"We already have research on this in <path>. Here's what it found: [2-4 key findings]. Options: (1) use as-is, (2) verify / refresh (article is from [date]), (3) extend on [specific dimension], (4) new angle if this is a different framing."

Let the user choose. Do NOT start new research when existing research already answers the question.

Partially covered:

"We have related research in <path> covering [scope]. Your question about [topic] isn't directly answered but it's a natural extension. Options: (1) extend existing via Path C, (2) start new article via Path A. I'd recommend [1 or 2] because [reason]."

Not covered:

Proceed to Step 2 (scoping). If the user asked for a quick answer, flag that Path B may apply and confirm in Step 2's scoping exchange.

Headless mode: auto-select — fully-covered → proceed to new article on the specific angle the caller requested; partially-covered → start new article; not-covered → Path A.

Scan discipline
  • Do not skip the scan. Even 30 seconds of grep + cat prevents duplicate research AND gives the user context on what's already known.
  • Bias toward extending (Path C) when topics are semantically coherent — one comprehensive article beats two overlapping ones.
  • Bias toward new (Path A) when framing, audience, or primary question differs materially.

Step 2: Collaborative scoping (Supervised STOP gate)

HARD GATE (Supervised mode). Do NOT start external research until the user confirms the rubric. After proposing it, STOP and WAIT for user response. Only then mark the Scoping task completed.

In headless mode: propose the rubric AND proceed. Mark the task completed after proposing.

Propose a rubric

Return this structure to the user:

## Proposed research rubric

**Question:** [narrowed from the original topic — concrete, answerable, bounded]

**Dimensions to investigate:** [3-7 facets]
1. [Dimension 1]
2. [Dimension 2]
...

**Candidate sources:** [3-8 initial guesses]
- [Source 1 — why it's relevant]
- [Source 2 — why it's relevant]
...

**Success criteria:** [2-3 concrete outcomes — "the article cites X authoritative sources", "open questions are marked explicitly", etc.]

**Output format:** Path A (article) | Path B (direct answer) | Path C (update `<existing-article>`)
Scoping discipline
  • If the original topic is vague ("research LLM agents"), narrow it before fetching: "What specific agents? For what decision? Over what time horizon?"
  • If the topic is itself a URL, treat that URL as the anchor and widen to 2-4 adjacent authoritative sources.
  • Name the decision this research informs. Research without a decision context meanders.
  • Do not over-specify the rubric — the user can adjust. Propose, don't prescribe.

Step 3: Capture raw sources via ingest

For each relevant URL, paper, or document in the confirmed rubric, follow the ingest procedure — it lives in the platform /open-knowledge skill at references/ingest-and-sources.md, not in this pack. Typical research pulls 3-8 sources. Too few → thin synthesis. Too many → you'll be reading for the rest of the session.

  • Don't skip ingest. Raw preservation separates capture from interpretation and makes research reproducible. An article without preserved sources is just opinion; an article with preserved sources is a trail someone else can follow.
  • If a fetch fails for a source you specifically need, stop and ask the user to paste it — don't silently drop it. Write-time fabrication of missing evidence is the biggest failure mode.
  • If a fetch returns an obvious summary instead of the raw bytes (some LLM-backed fetch tools do this), note it and try a raw alternative (curl -sL <url>, or ask the user to paste).

Show full SKILL.md (1,002 more words)Show less

Step 4: Read + analyze

Read each ingested source carefully. Also load:

  • Existing canonical articles on the topic — exec("cat <path>") (returns frontmatter + backlinks + shadow-repo activity).
  • Prior research on adjacent topics — same: exec("cat <path>") for OpenKnowledge markdown.
  • Relevant source code — ONLY if the user asked for first-party analysis. Use native Read for .ts / .js / etc.; exec for in-scope .md / .mdx.
  • Project context — wherever the project keeps design material.

Take structured notes:

  • Key claims and their evidence — every claim needs a source you can point at
  • Trade-offs between options
  • Contradictions between sources — these are often the most valuable part of the article
  • Unknowns and open questions — the boundary of what you know
  • Relevance to the specific decision at hand

Write these notes into the article as you take them, not after (MUST — see Persist as you go above). Create the article skeleton — frontmatter + the Step 5 section headings — before you start reading, then edit each source's findings into the relevant section the moment you finish analyzing it. The "notes" ARE the article's Findings section in progress; don't hold them in context to transcribe in one pass at Step 5. A rate limit between here and Step 5 must not be able to discard analysis you've already done. By the time you reach Step 5 the article is mostly written, and Step 5 becomes finalize-and-polish.

Grounding discipline

Every factual claim in the article must cite its source inline. No unsourced speculation. If you don't have evidence: (a) run another search and cite it, (b) mark inline (TODO: needs source), or (c) don't write the claim. Never fabricate.


Step 5: Write the research article (Path A only)

If you followed Persist as you go, the article already exists and is substantially filled from Step 4 — this step finalizes it (fill any remaining sections, tighten the recommendation, run the structure + validation checks below) rather than writing from a blank doc. If it does not exist or is thin, and you are resuming after an interruption: exec("cat <path>") the partial article back first and fill only the missing sections — and note that any Step 4 analysis that was never written to the KB was lost when the session broke, so re-derive only what's actually missing. Creating the doc from scratch here means the incremental rule was skipped; that's the failure mode, not the happy path.

Save a markdown document inside the content directory. Path convention:

  • If the project adopted the three-layer lifecycle (external-sources/ → research/ → articles/), save under research/<slug>.md.
  • If the project has an existing docs/reports/specs layout, match it.
  • Large topics warrant a subfolder: research/<topic>/<subtopic>.md.

Filename: descriptive, kebab-case (crdt-alternatives-for-editor.md, llm-wikis-and-knowledge-bases.md). No dates — dates go in frontmatter.

Frontmatter
yaml
---
title: Descriptive title
description: One-line summary of the research question
type: research-note
status: draft
date: YYYY-MM-DD
tags:
  - research
  - provisional
  - <topic-tag>
sources:
  - resource: ../external-sources/<source-1>.md
  - resource: ../external-sources/<source-2>.md
---
Structure
markdown
## Question

[What specific question does this research answer? Be precise.]

## Context

[Why does this matter? What decision does it inform? Who is the reader?]

## Findings

[Main findings organized by theme, option, or criterion. Every claim cites a source inline.]

### Theme / Option 1

- Pros — with evidence links
- Cons — with evidence links
- Evidence: [Source A](../external-sources/source-a.md), [Source B](../external-sources/source-b.md)

### Theme / Option 2

...

## Trade-offs

[What you gain vs. lose with each option. A comparison table often helps.]

## Open questions

[What you still don't know — candidates for further research, prototyping, or human-judgment decisions.]

## Tentative recommendation

[Your best guess, clearly marked as tentative. Explain the reasoning so a future reader can re-evaluate when new information arrives.]

## Further reading

[Links to the ingested sources + adjacent research + any canonical articles on the topic.]
Voice
  • Provisional, not canonical. Use "tentative", "initial findings", "based on current understanding."
  • Do NOT write as if it were canonical — that's misleading. Canonicality is the /consolidate-notes skill's job, after decisions land.
  • Explicit about uncertainty. Research is the layer where uncertainty is allowed to live.

Research articles are discovery surfaces. Under-linked research becomes an island nobody finds.

  • Every noun-phrase that names another document is a link. Use standard markdown: [text](./relative/path.md).
  • Link sources inline where you cite them, not just in the frontmatter sources: list: According to [LLM Agents](../external-sources/llm-agents.md)... is stronger than a bare sources: entry.
  • Cross-link sibling research: if an adjacent topic has its own research doc, link it under "Open questions" or inline. Readers following one thread should find the others.
  • After writing, update 1-2 closely-related existing pages to link back to this research (usually under "Further reading" or "See also"). This is how the research becomes discoverable via backlinks.
  • Never wrap links in backticks; never use HTML anchors — matches the platform skill's linking rules.
File valuable Q&A back

If the user asked a specific question during the research session that produced a citable answer, capture it as its own short page alongside the research — not just as chat. Concrete questions with sourced answers are the highest-signal unit of knowledge you can produce.

  • Short filename: what-does-X-mean.md, how-does-Y-work.md
  • Include the same object-shaped sources: frontmatter
  • Link the answer from this research doc under "Further reading"
  • Answers too small to justify a separate file stay in chat; don't fragment

Step 7: Validate

Run this checklist before marking complete:

  • File exists at the chosen path under the content directory
  • Frontmatter has title, description, type: research-note, status: draft, date, and an object-shaped sources: list
  • exec("ls -A <dir>") lists the new file with frontmatter enrichment
  • audit({ path: "<doc-path>.md" }) returns clean (every lint violation + broken internal link) — fix every finding
  • Every factual claim in Findings cites a source inline
  • Linked source files from Step 3 all exist (broken source links → ingest went wrong somewhere)
  • At least 1-2 neighbor docs now link to this research (per Step 6's "After writing, update ..." rule)

Step 8: Recap + follow-up directions

Close the loop with the user in conversation:

## Recap

- [Finding 1 — with source]
- [Finding 2 — with source]
- [Key trade-off / contradiction surfaced]
- [1-2 open questions that remain]

**Tentative recommendation:** [state it in one sentence]

**Follow-up research directions** (Path A candidates for later):
1. [Direction 1 — what would it investigate?]
2. [Direction 2 — what would it investigate?]
3. [Direction 3 — what would it investigate?]

Follow-ups should be external-source investigations — not actions on the user's codebase (those belong in a spec, not more research). Each direction should be a standalone topic someone could later research.

In headless mode, write the recap into the research article's "Further reading" section rather than prompting interactively.


Non-goals

  • Don't promote to a canonical article. That's the /consolidate-notes skill's job after a decision actually lands. Premature canonicalization buries uncertainty and misleads future readers.
  • Don't hide uncertainty. Research is the layer where "we don't know yet" is acceptable prose. Say it explicitly.
  • Don't skip ingest. Always capture raw sources first, then analyze. An article without preserved sources is opinion.
  • Don't skip the Step 1 scan. Duplicate research wastes the user's time AND misses chances to extend prior work.
  • Don't skip the scoping gate in Supervised mode. The user's rubric shapes everything downstream; you cannot recover a wrong-scope article cheaply.
  • Don't mix first-party codebase analysis into the article unless asked. Findings drift from factual synthesis to opinion when you do.
  • Don't overwrite existing research silently. If the topic was researched before, either iterate (Path C) or create a clearly-named successor (crdt-alternatives-2.md) and mark the old one as superseded.

© inkeep, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in packages/server/assets/skills/packs/knowledge-base/research of inkeep/open-knowledge.

Open the folder on GitHubat commit 205b3bd

Compare with similar skills

Research With Sources next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Research With Sources compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research With Sources this skillinkeep/open-knowledge4.4k—~5.6kAutomated safety check: PassGPL-3.0
DeepTutor CLIHKUDS/DeepTutor41k—~2.8kAutomated safety check: PassApache-2.0
Learn From Materialsdmoshehun-prog/learn-from-materials937—~7.9kAutomated safety check: PassMIT
Nlm Skilliusztinpaul/ai-research-os-workshop1791 repos~6.9kAutomated safety check: PassMIT
NotebookLM CLI Guidejacob-bd/notebooklm-cli256—~3.4kAutomated safety check: WarnMIT
Wiki ReviewIssacW228/student-llm-wiki177—~259Automated safety check: PassMIT

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  • Consolidate Notes

    inkeep/open-knowledge

    Promote existing research into a stable-status canonical article under articles/ in a Knowledge Base project (the knowledge-base starter pack).

    4.4k GitHub stars~2.3k tokensUpdated today
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Questions about Research With Sources

What does Research With Sources do?

Investigate a topic against preserved sources and write a draft-status research article under research/ in a Knowledge Base project (the knowledge-base starter pack). Research With Sources is an agent skill from inkeep/open-knowledge. Investigate a topic against preserved sources and write a draft-status research article under research/ in a Knowledge Base project (the knowledge-base starter pack).

When should I use Research With Sources?

Research With Sources fits situations like: tasks that involve Knowledge bases; tasks that involve Quizzes and assessments.

How do I install Research With Sources in Claude Code?

Run `npx skills add inkeep/open-knowledge --skill research-with-sources -a claude-code`. Or copy the skill folder (packages/server/assets/skills/packs/knowledge-base/research in inkeep/open-knowledge) into .claude/skills/research-with-sources in your project. Claude Code loads it when a task matches its description.

How do I install Research With Sources in Codex?

Run `npx skills add inkeep/open-knowledge --skill research-with-sources -a codex`. Or copy the skill folder (packages/server/assets/skills/packs/knowledge-base/research in inkeep/open-knowledge) into .agents/skills/research-with-sources in your project. Codex loads it when a task matches its description.

Can I use Research With Sources in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add inkeep/open-knowledge --skill research-with-sources -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-with-sources, .gemini/skills/research-with-sources, .github/skills/research-with-sources and .opencode/skills/research-with-sources in your project.

What does Research With Sources need to run?

Going by SKILL.md and its folder, Research With Sources needs the command-line tools its instructions call (curl). Compatibility (from SKILL.md): Any agent host with the OpenKnowledge MCP server configured. Installed project-local by `ok seed --pack knowledge-base`..

Does Research With Sources access the network?

SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Research With Sources safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Research With Sources use?

Research With Sources is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Research With Sources use?

About 5.6k tokens (SKILL.md is roughly 22k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Research With Sources?

Skills that share tags, products or a category with Research With Sources: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), Learn From Materials (dmoshehun-prog/learn-from-materials, 937 stars), Nlm Skill (iusztinpaul/ai-research-os-workshop, 179 stars) and NotebookLM CLI Guide (jacob-bd/notebooklm-cli, 256 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research With Sources?

inkeep (a GitHub organization) maintains it in inkeep/open-knowledge, which has 4,433 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on October 9, 2026.

Source: inkeep/open-knowledge on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.