By hamondyan
Curate an academic knowledge base from arXiv, Semantic Scholar, and OpenAlex by ingesting papers as raw Markdown, distilling them into canonical wiki pages with metadata and wikilinks, surfacing research ideas and gap analyses from local evidence, and auditing vault health.
Use when the user wants to find new papers, pull a daily digest, or search arXiv/Semantic Scholar/OpenAlex for a research topic. Runs stateless v3 discovery and returns chat-only candidates.
Use when the user wants to capture one or more resolved arXiv URLs, arXiv IDs, or arXiv DOI values. Writes raw evidence to raw/evidence/.
Use when the user wants to audit the vault for dead links, alias issues, schema problems, concept/link coverage, or orphaned concept pages. Reports issues; does not rewrite files.
Use when the user wants a vault health snapshot: page counts, recent activity, and outstanding lint issues.
Use when the user or another skill needs QMD CLI syntax, collection handles, retrieval recipes, or post-write index refresh guidance. Centralizes the read/index surface that sits alongside the Paper Distill business MCP.
Use when the user asks research questions against the vault, wants canonical wiki synthesis saved, asks for concept maintenance, runs QMD CLI read/index flows, or wants business writes and linting.
Use when the user asks for research ideas, gap analysis, open problems, novel angles, what to work on, or wants to curate idea notes from local paper evidence.
Use when the user wants to distill a captured paper into a canonical wiki page, write the wiki page for a paper, or process the raw evidence of a specific paper. Handles the raw/evidence to wiki/papers transition.
Use when the user wants chat-only paper discovery, candidate summaries, direct arXiv URL/ID/arXiv DOI ingest, or natural paper names resolved before capture.
Admin access level
Server config contains admin-level keywords
Requires secrets
Needs API keys or credentials to function
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Paper Distill is a Markdown-first research knowledge system for chat-only discovery, direct paper capture, preserving raw evidence, and turning papers into canonical wiki pages.
v3.0 uses qmd as the read/index path, keeps Markdown as the source of truth, and gives business workflows to a small MCP surface.
Most research stacks are good at one layer and fuzzy everywhere else: they can search, or summarize, or store notes, but they do not keep a clean boundary between discovery, capture, retrieval, and canonical synthesis.
Paper Distill is built around those boundaries:
The result is a vault that stays readable as plain Markdown while still being usable by agents.
raw/evidence/.wiki/papers/ pages with required metadata and concept links./status snapshot.The normal workflow is:
/discover -> agent presents chat-only candidates -> /ingest <resolved arXiv URL|ID|arXiv DOI> -> raw evidence -> distill_paper -> qmd update -> /lint
Direct ingestion is available when you already know the paper identity:
/ingest https://arxiv.org/abs/2410.24164
/ingest 10.48550/arxiv.2410.24164
/ingest 1706.03762
/ingest 10.48550/arxiv.2410.24164, 1706.03762
The agent resolves natural references to arXiv identities before capture. After write-heavy work, run qmd update; run qmd embed -f only when semantic retrieval must reflect new content immediately.
Paper Distill has three clear surfaces:
raw/evidence/, wiki/, and insights/In practice that means:
qmd update and qmd embed -f are explicit follow-up steps, not hidden side effects.For the repo-level architecture guide, see docs/architecture.md. For QMD usage, see docs/qmd-cli.md.
uv sync
settings.json with an absolute paper_distill.vault_path:cp settings.example.json settings.json
uv run paper-distill-admin --help
qmd --help
uv run paper-distill-admin bootstrap
uv run paper-distill-server
/discover
/ingest 10.48550/arxiv.2410.24164
qmd query "your topic"
When installed as a namespaced plugin, slash commands may appear with a plugin prefix such as /paper-distill:discover.
Paper Distill uses the repository root as the plugin root. Installation means registering this checkout with the host rather than moving the project into a separate plugin bundle.
Codex can also discover Paper Distill from the repo-local marketplace at .agents/plugins/marketplace.json.
That marketplace entry points at ./plugins/paper-distill, a Codex compatibility plugin that resolves back to the repository root at runtime.
For host-specific installation and uninstall notes, see docs/plugin-installation.md.
| Command | Use it when | Backing surface |
|---|---|---|
/discover | you want new papers, a daily digest, or a topic search | discover_papers |
/ingest | you want to capture resolved arXiv URLs, IDs, or arXiv DOI values | ingest_and_read |
MCP distill_paper(s) | you want to turn captured evidence into canonical paper pages | distill_paper, distill_papers |
/lint | you want a structural and weak-link audit of the vault | lint_vault |
/status | you want a quick health snapshot and next action | agent-side summary |
For command details, see docs/commands.md.
npx claudepluginhub hamondyan/paper-distillClaude + Obsidian knowledge companion. Sets up a persistent, compounding wiki vault (Karpathy's LLM Wiki pattern). v1.7 "Compound Vault" + v1.8 methodology modes close 5 of 5 priority gaps from the May 2026 compass artifact. Ships: substrate alignment with kepano/obsidian-skills, default Obsidian CLI transport, hybrid retrieval (contextual prefix + BM25 + cosine rerank per Anthropic's Sept 2024 research), per-file advisory locking for multi-writer safety, pre-commit verifier agent, AND methodology modes (LYT / PARA / Zettelkasten / Generic) for first-class organizational support no other Claude+Obsidian competitor offers. v1.7.x audit closure: every BLOCKER + HIGH + MEDIUM + LOW finding from the v1.7.0 audit is CLOSED or DEFERRED-with-rationale. Optional DragonScale Memory extension (log folds, deterministic addresses, semantic tiling lint, boundary-first autoresearch).
Build and maintain an LLM-curated personal knowledge base in your project — Andrej Karpathy's LLM Wiki pattern, designed to scale to thousands of pages without becoming a context bottleneck. Now with an optional compiled graph layer for typed, provenance-backed relationships.
Complete AI coding workflow system. Self-correcting memory + persistent FTS5-indexed research wikis + auto-research loop + multi-LLM council on a single SQLite store. 33 skills, 8 agents, 22 commands, 37 hook scripts across 24 events. Cross-agent via SkillKit.
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Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Connect to Atlassian products including Jira and Confluence. Search and create issues, access documentation, manage sprints, and integrate your development workflow with Atlassian's collaboration tools.