Vault Contextual Retrieval
AgriciDaniel/claude-obsidian
Builds and queries a local contextual BM25 index over an Obsidian vault, with optional Nomic reranking through Ollama and strict consent rules before any text leaves the machine.
Searches, summarizes, compares and answers questions from an already configured AutoRAG librarian agent over local documents and authorized datasources.
$ npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Marker-Inc-Korea/AutoRAG.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/autorag .claude/skills/autorag && rm -rf skills-srcUse ~/.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/
Install the "autorag" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag into .claude/skills/autorag/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autoragType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Marker-Inc-Korea/AutoRAG.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/autorag .agents/skills/autorag && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "autorag" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag into .agents/skills/autorag/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Marker-Inc-Korea/AutoRAG.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/autorag .cursor/skills/autorag && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "autorag" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag into .cursor/skills/autorag/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Marker-Inc-Korea/AutoRAG.git --path skills/autorag--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Marker-Inc-Korea/AutoRAG.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/autorag .gemini/skills/autorag && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "autorag" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag into .gemini/skills/autorag/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Marker-Inc-Korea/AutoRAG autoragInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Marker-Inc-Korea/AutoRAG.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/autorag .github/skills/autorag && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "autorag" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag into .github/skills/autorag/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Marker-Inc-Korea/AutoRAG.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/autorag .opencode/skills/autorag && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "autorag" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag into .opencode/skills/autorag/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
autoragSearches, summarizes, compares and answers questions from an already configured AutoRAG librarian agent over local documents and authorized datasources.
The skill assumes AutoRAG is already configured and routes search, summarize, compare and question-answering requests over local PDFs, wikis, notes, papers or other authorized datasources to it. One configured model plans the search itself, calling MinSync, Jikji, datasource and filesystem tools, reading sources, judging evidence and curating the final answer, with no separate subagent or model role; AutoRAG only reads source documents and writes indexes under its own workspace directories, never moving, renaming, editing or deleting source files.
Before anything else, it confirms a config file exists at one of several standard locations and inspects only non-secret search paths and model metadata, then runs duplicates, status and health commands as JSON. A duplicate-file review command finds exact or near/contains duplicate files read-only, useful for reducing index space, with exact matches found by a canonical text hash and near matches needing human review; an excludePaths setting in the config keeps specific files or folders out of the index entirely, reversible by removing the entry and refreshing.
The status command is model-free, while health resolves the configured model, checks that credentials are present, and normally probes one live completion, falling back to a separate autorag-setup skill rather than guessing at private provider details when something is unhealthy.
Read from SKILL.md and the folder at commit 29ccab9. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AutoRAG Librarian loads about 2.1k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 977 words of instructions outside code blocks.
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.
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.
The full file from Marker-Inc-Korea/AutoRAG at commit 29ccab9, republished under its MIT licence (© Marker-Inc-Korea). 977 words, ~2,055 tokens.
.claude/skills/autorag/SKILL.md (or your agent's skills folder).Use this skill when AutoRAG is already configured and the user asks to search, summarize, compare, or answer questions from local PDFs, wikis, notes, research papers, knowledge bases, or configured datasources.
AutoRAG is the specialized librarian agent. One configured model plans the search, calls MinSync, Jikji, datasource, and filesystem tools, reads sources, judges evidence, and curates the final answer. There is no subagent or separate model role.
AutoRAG reads source documents and writes indexes only under the configured
workspace .autorag/ directory and Jikji's per-source .jikji/ caches. Never
move, rename, edit, or delete source files.
Confirm a config exists at --config, AUTORAG_CONFIG,
$AUTORAG_HOME/config.json, or ~/.autorag/config.json. Inspect only
non-secret searchPaths and model metadata, then run:
autorag duplicates --json
autorag status --json
autorag health --jsonUse autorag duplicates when the user asks to find duplicate files, choose
likely latest copies, or reduce corpus/index space. The command and the
scan_duplicate_documents Agent tool are read-only and never delete or move
source files. Exact means dupey's canonical extracted-text hash matches;
near/contains families require human review. Exact duplicate exclusion during
refresh is enabled by default and can be disabled with
"excludeExactDuplicates": false in config.json.
"excludePaths" in config.json lists files or folders (absolute, or relative
to workspacePath) that refresh keeps out of the parsed mirror and MinSync.
A folder entry excludes everything under it. Removing an entry and running
autorag refresh --method minsync indexes the file again. Excluded sources are
recorded as user-excluded skips, so they are not reported as stale. Jikji
indexes the source folders directly and is not refreshed here, so AutoRAG also
drops excluded paths from the jikji_find answer pack and the baseline prefetch
at retrieval time; the on-disk .jikji_agent_map.md stays complete, and direct
file reads remain available.
status is model-free and path-opaque. health resolves the single model,
checks credential presence, and normally probes one live completion. If the
model, authentication, configuration, or indexes are unhealthy, use
autorag-setup rather than guessing private provider details.
MinSync and Jikji should normally be healthy. Answering a question never
builds or installs them: autorag refresh auto-installs both by default and
builds their indexes incrementally. If they are missing or stale, run a full
autorag refresh or return to setup rather than silently degrading to
lexical-only search.
Prefer --json --debug when another agent will consume the result.
--json alone omits sessionId. --debug adds session/diagnostics fields and
does not print filesystem paths.
autorag search "what were the key findings in the Q3 report" --top-k 5 --json --debug--json --debug includes answer, numbered results (number, title,
summary, optional source), and sessionId. --json without --debug is
only answer plus results. Every
bracketed [n] citation in answer resolves to a results[].number of the
same response; an unmatched citation is removed and reported as a
citation-without-result diagnostic.
To inspect the exact persisted evidence behind numbered results, use:
autorag evidence <sessionId> --result 1 --jsonThe response includes the original source, retrieval method, stable evidence
ID, raw excerpt/content, and any available chunkIndex, lineNumber,
retrievalResultId, and metadata. Omit --result to inspect every result in
the session. Prefer this command whenever the caller wants detailed chunk text
rather than only the curated summary.
--scope narrows datasource retrieval to a requested sub-path (ordinary
per-query filtering).--json is required for programmatic consumption.--debug is required for sessionId and diagnostics in search output.autorag evidence is the detailed source/chunk inspection path.Do not bypass the librarian with ad hoc raw search when the user requested
AutoRAG. The search loop can use Jikji, MinSync lexical/vector/hybrid retrieval, datasource retrieval, and
direct source reading as appropriate. If search fails because of model,
provider, auth, or timeout problems, diagnose with autorag health --json.
Every search is two-phase: a fast answer, then verification. With Jev on (the default, OpenRouter), Jev first routes the question:
autorag launch.After the fast answer, Jev ends the run if the answer is complete and
evidence-backed. So results may come straight from the fast answer, with no
verification phase. --debug diagnostics show the decision: query-routed
(branch and queries), datasources-selected (datasources searched or skipped,
with probabilities), follow-up-skipped (fast answer final), or
query-route-fallback (Jev unavailable, single local search).
autorag setup --format json
autorag status --json
autorag health --json
autorag refresh --json
autorag refresh --method minsync,jikji --json
autorag watch --once --json
autorag watch
autorag refresh --force --json
autorag index rebuild --yes --json
autorag index reset --method parsed --yes --json
autorag memory inspect --json
autorag tui
autorag serve --force
autorag p2p policy list --jsonPrefer a full refresh so parsed mirrors, MinSync, Jikji, configured
datasources, and (on Windows) the bundled Everything file-name index stay
aligned. --method accepts
parsed,minsync,datasources,jikji,everything,all. BM25 is a MinSync retrieval mode, not
a --method name. Use --method only for deliberate narrowing. Scheduled
maintenance should use non-daemon autorag watch --once, typically every
1 hour, with the same config used by search and no overlapping runs.
autorag tui is the shipped beta terminal UI. autorag serve / autorag p2p
are opt-in SimpleX peer sharing (disabled until p2p.enabled is true, unless
--force).
Reset and rebuild commands remove only selected workspace .autorag indexes.
Never target source documents. memory inspect is read-only and path-opaque.
--json --debug when another agent consumes search output.autorag --help is the command list of record,
including the shipped setup, gateway, models, serve, p2p, tui, and lite
commands. autorag <command> --help prints that command's own flags, and
autorag --version prints the installed version. See
docs/embedding-runtime.md for the local embedding runtime
and gateway setup.© Marker-Inc-Korea, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/autorag of Marker-Inc-Korea/AutoRAG.
Open the folder on GitHubat commit 29ccab9
AutoRAG Librarian 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AutoRAG Librarian this skillMarker-Inc-Korea/AutoRAG | 5.1k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Vault Contextual RetrievalAgriciDaniel/claude-obsidian | 15k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Knowledgebaseopen-edge-platform/edge-ai-suites | 140 | — | ~900 | Automated safety check: Pass | Apache-2.0 | |
| Clarity Gatesickn33/agentic-awesome-skills | 47k | 3 repos | ~709 | Automated safety check: Pass | CC-BY-4.0 | |
| Openloomimelandlabs/openloomi | 1k | — | ~835 | Automated safety check: Pass | Apache-2.0 | |
| Gnogmickel/gno | 115 | 1 repos | ~1.6k | Automated safety check: Pass | MIT |
AgriciDaniel/claude-obsidian
Builds and queries a local contextual BM25 index over an Obsidian vault, with optional Nomic reranking through Ollama and strict consent rules before any text leaves the machine.
open-edge-platform/edge-ai-suites
Generic RAG query skill - Retrieve any information from the local knowledge base and generate structured reports, summaries, or Q&A responses.
sickn33/agentic-awesome-skills
Pre-ingestion verification for epistemic quality in RAG systems.
melandlabs/openloomi
OpenLoomi entrypoint for skill-only agent runtimes without a plugin mechanism.
gmickel/gno
Search local documents, files, notes, and knowledge bases. An agent skill from gmickel/gno.
praneybehl/llm-wiki-plugin
Build and maintain an LLM-curated knowledge base from papers, articles, transcripts, notes and project findings.
Marker-Inc-Korea/AutoRAG
Diagnoses and repairs a broken AutoRAG install so every configured datasource is both indexed and returns real search hits.
Marker-Inc-Korea/AutoRAG
Bootstraps and repairs the model-free AutoRAG Lite MCP server: installing it, initializing a config with approved search roots, building indexes and verifying discovery.
Marker-Inc-Korea/AutoRAG
Installs, configures, and repairs AutoRAG's search model, approved folders, indexes, and datasources, and registers its Lite MCP server.
Categories
Searches, summarizes, compares and answers questions from an already configured AutoRAG librarian agent over local documents and authorized datasources. The skill assumes AutoRAG is already configured and routes search, summarize, compare and question-answering requests over local PDFs, wikis, notes, papers or other authorized datasources to it. One configured model plans the search itself, calling MinSync, Jikji, datasource and filesystem tools, reading sources, judging evidence and curating the final answer, with no separate subagent or model role; AutoRAG only reads source documents and writes indexes under its own workspace directories, never moving, renaming, editing or deleting source files.
AutoRAG Librarian fits situations like: searching local PDFs, wikis or notes through an already-configured AutoRAG agent; finding and reviewing duplicate files in the AutoRAG-indexed corpus; checking whether AutoRAG's configured model and index are healthy; excluding specific files or folders from the AutoRAG index.
Run `npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a claude-code`. Or copy the skill folder (skills/autorag in Marker-Inc-Korea/AutoRAG) into .claude/skills/autorag in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a codex`. Or copy the skill folder (skills/autorag in Marker-Inc-Korea/AutoRAG) into .agents/skills/autorag in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Marker-Inc-Korea/AutoRAG --skill autorag -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/autorag, .gemini/skills/autorag, .github/skills/autorag and .opencode/skills/autorag in your project.
SKILL.md names no scripts, command-line tools or credentials: AutoRAG Librarian is instructions for the agent only. Our summary lists: An already configured AutoRAG instance with a config.json.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
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.
AutoRAG Librarian is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with AutoRAG Librarian: Vault Contextual Retrieval (AgriciDaniel/claude-obsidian, 15k stars), Knowledgebase (open-edge-platform/edge-ai-suites, 140 stars), Clarity Gate (sickn33/agentic-awesome-skills, 47k stars) and Openloomi (melandlabs/openloomi, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Marker-Inc-Korea (a GitHub organization) maintains it in Marker-Inc-Korea/AutoRAG, which has 5,122 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 11, 2026.
Source: Marker-Inc-Korea/AutoRAG on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.