Chroma Vector Database
Orchestra-Research/AI-Research-SKILLs
Shows how to store documents and embeddings in Chroma, query them by similarity with metadata filters, and persist them to disk for RAG and semantic search projects.
Diagnoses and repairs a broken AutoRAG install so every configured datasource is both indexed and returns real search hits.
$ npx skills add Marker-Inc-Korea/AutoRAG --skill autorag-doctor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag-doctor --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-doctor .claude/skills/autorag-doctor && 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-doctor" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag-doctor into .claude/skills/autorag-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag-doctor", 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/autorag-doctorType 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-doctor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag-doctor --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-doctor .agents/skills/autorag-doctor && 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-doctor" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag-doctor into .agents/skills/autorag-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag-doctor", 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-doctor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag-doctor --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-doctor .cursor/skills/autorag-doctor && 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-doctor" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag-doctor into .cursor/skills/autorag-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag-doctor", 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-doctor--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-doctor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Marker-Inc-Korea/AutoRAG autorag-doctor --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-doctor .gemini/skills/autorag-doctor && 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-doctor" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag-doctor into .gemini/skills/autorag-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag-doctor", 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 autorag-doctorInstalls 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-doctor -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-doctor .github/skills/autorag-doctor && 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-doctor" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag-doctor into .github/skills/autorag-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag-doctor", 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-doctor -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-doctor --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-doctor .opencode/skills/autorag-doctor && 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-doctor" agent skill from https://github.com/Marker-Inc-Korea/AutoRAG/tree/main/skills/autorag-doctor into .opencode/skills/autorag-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autorag-doctor", 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.
autorag-doctorDiagnoses and repairs a broken AutoRAG install so every configured datasource is both indexed and returns real search hits.
The goal is that each datasource is indexed and actually answers a query; a green status alone is not enough. The agent triages the core with status, health and gateway status commands in JSON, reads the config for search paths, workspace, MinSync, Jikji and datasources, then probes every datasource with its own native check, since each CLI owns its archive. If the CLI or config is missing it stops and points to the setup skill, because the doctor repairs an install and does not create one.
Repairs cover orphan locks and processes, embedding dimension or identity mismatches, stale indexes and missing setup, with re-sync through refresh by method. Safety rules forbid deleting or editing source documents or a datasource's native store, allow resetting only AutoRAG-owned state, never print token values and kill a process only after confirming it is an AutoRAG orphan. Datasources include CLIs such as qmd, rclone and Spotlight, and the run always ends with a status table.
4 steps, taken from the step headings in SKILL.md.
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.
Shell commands in SKILL.md call:
cargoFrom 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 these keys or tokens, usually read from environment variables:
OPENROUTER_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AutoRAG Doctor loads about 3.4k tokens when it runs. Until then it costs about 166 tokens; SKILL.md has 1,625 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). 1,625 words, ~3,437 tokens.
.claude/skills/autorag-doctor/SKILL.md (or your agent's skills folder).Goal: every configured datasource is indexed and actually returns
hits. A green status is not enough — the run is done only when a real query
returns a real hit per datasource, or the datasource is reported as genuinely
empty or not configured.
Always finish with the status table in Report.
~/Library/Application Support/katok, ~/.discrawl,
~/.mailcrawl, .qmd, Telegram/WhatsApp/Notion archives). AutoRAG only
reads them; rebuilding them is the owning CLI's job.AUTORAG_HOME and the workspace .autorag
directory may be reset.autorag status --json
autorag health --json
autorag gateway status --format jsonstatus reports state, stale, diagnostics, and per-component state for
minsync, jikji, and datasources. stale: true or any stale-index
diagnostic means the corpus changed since the last successful refresh.health resolves the single search model and does one live completion probe.
--skip-probes only proves config shape, never live access; do not claim a
healthy model from it.stopped is normal when nothing is embedding.
unavailable while a refresh is running is a real failure.Config lives at --config, AUTORAG_CONFIG, $AUTORAG_HOME/config.json, or
~/.autorag/config.json. Read searchPaths, workspacePath, minSync,
jikji, and datasources before changing anything.
If the CLI itself is missing or the config does not exist, stop and run the
autorag-setup skill first — doctor repairs an existing install, it does not
create one.
Each CLI owns its archive, so ask the CLI, not AutoRAG. A datasource is only
active when its binary exists, its store is present, and its own check passes.
| Datasource | Native check | Re-sync when empty or stale |
|---|---|---|
| MinSync (local docs) | minsync status, minsync check, minsync verify | autorag refresh --method minsync |
| Jikji (discovery) | jikji doctor | autorag refresh --method jikji |
| Everything (Windows file names) | autorag status --json → components.everything | autorag refresh --method everything --json |
| KakaoTalk | lazykatok doctor | lazykatok sync && lazykatok index |
| Discord | discrawl --json metadata | discrawl sync |
| Slack | slacrawl --json doctor | slacrawl sync |
wacrawl --json doctor | wacrawl import | |
| Telegram | telecrawl --json doctor, telecrawl --json status | telecrawl import |
| Notion | notcrawl doctor, notcrawl status | notcrawl sync --source desktop |
| Obsidian / notes | qmd status | qmd update && qmd embed |
mailcrawl doctor, mailcrawl status | mailcrawl sync && mailcrawl index | |
| Cloud drive | rclone listremotes | autorag refresh --method datasources |
| Spotlight (macOS) | mdutil -s / | indexed by the OS; no AutoRAG sync |
| Lark / Feishu | lark-cli auth status --format json | no local sync; search is remote |
Rules:
telecrawl and slacrawl
return JSON null (not []) for no hits — treat that as empty, not broken.slacrawl sql "select count(*) from message_fts where message_fts match 'x';"
against slacrawl search x). A populated index plus an empty CLI result is an
upstream bug: report it with the exact reproduction instead of re-syncing.Indexing without retrieval is a failed run. Probe retrieval per datasource through the model-free MCP tools, then once end to end:
autorag.status {}
autorag.search {"query":"a word that certainly appears","topK":3}
autorag.search {"query":"recent topic","datasourceIds":["discord"],"topK":3}
autorag.search {"query":"recent mail subject","scope":"/mailcrawl/**","topK":3}autorag search "summarize the collection" --top-k 3 --json --debugdiagnostics returned by MCP autorag.search. A run
that silently dropped a whole retrieval method still looks successful, just
with fewer results; only the diagnostics name it (retrieval-method-failed).
The model-backed CLI autorag search --json
hides diagnostics, sessionId, and per-result evidence unless --debug is
set, so pass --debug when diagnosing that path.method values means that method
contributed nothing. During a full MinSync re-sync this is expected: the
store is being rebuilt, minsync status reports NotSynced, and local-file
hits stay absent until it finishes. Confirm with minsync status before
treating it as a failure, and never kill a running sync to "fix" it.autorag.search needs no model, so it isolates retrieval from model
failures.datasourceIds to select configured connections before retrieval;
scope narrows results within scope-capable datasources. Discover connection
IDs with autorag.datasources.list; descriptor tags are metadata only, not
search filters. Every configured connection is searchable — if one returns
nothing, investigate its native store, connector, or the query itself.autorag.evidence {"sessionId":"...","resultNumber":N} shows the exact chunk
behind a numbered result; use it to confirm a hit is real and its source is
readable. The CLI autorag evidence SESSION --json remains for terminal
repair./kakao/personal/chunks/42; those are not
filesystem paths and must never be passed to cat.The embedding runtime keeps embedding-runtime.lock, embedding-runtime.pid,
and embedding-runtime.port in AUTORAG_HOME. It reclaims them automatically
when the recorded PID is dead; a lock-conflict means the PID is alive.
autorag gateway status --format json
autorag gateway stopOnly when gateway stop cannot clear it, and the recorded PID is confirmed
dead (kill -0 PID fails), remove the three files by hand and retry.
Index locks are owned by their engines: MinSync/tantivy locks under
<workspace>/.autorag/, and per-CLI locks such as
<workspace>/.autorag/datasources/discrawl/.discrawl-sync.lock. Delete one
only after confirming no owning process is alive; otherwise wait for the run
that holds it.
pgrep -fl 'autorag|autorag-gateway|minsync' | grep -v pgrepA refresh that was killed mid-run can leave the gateway or a minsync child
alive. Stop the gateway with autorag gateway stop first; only kill a PID
directly when it is confirmed orphaned (no parent CLI, no live refresh).
Re-run autorag status --json afterwards to confirm inFlight: false.
embedding-identity-mismatch or a dimension error means the vectors on disk
were built with a different embedder than the configured one. Vectors of two
different dimensions can never be compared, so the index must be rebuilt:
autorag models prefetch --profile qwen3-embedding-0.6b
autorag index rebuild --method minsyncThe current default is the local native:Qwen/Qwen3-Embedding-0.6B runtime at
1024 dimensions. A workspace still pinned to the legacy 768-dimension
Ollama/TEI path must be reindexed explicitly, or pinned to an explicit profile.
Changing embedder.dimension in config without a rebuild leaves retrieval
silently empty. Keep embeddings local; do not point the embedder at a remote
endpoint to work around a local failure.
stale-index diagnostics or stale: true mean sources changed after the last
refresh.
autorag refresh --method parsed,minsync --json
autorag refresh --force --jsonUse --force only when incremental refresh does not clear it. For continuous
freshness install an hourly autorag watch --once job (cron, launchd, systemd
timer, or Task Scheduler).
unknown-datasource-skill: the config key is not a builtin template and has
no "type". It is skipped, not fatal — fix the name or add "type".datasource-index-failed / sync-failed: the backing CLI errored. Run that
CLI's own check from the table above and fix it there.autorag search, autorag refresh
and MCP tools fail with MinSync is required ... and a non-zero exit. Install it
(cargo install minsync) or leave minSync.autoInstall on, then retry.jikji-unavailable: the binary is missing and auto-install failed. It
installs through cargo; verify the Rust toolchain, then autorag refresh --method jikji to retry.auth-error / rate-limited: model or datasource credentials. Report the
missing environment-variable name and let the user supply it.| Code | Meaning | First move |
|---|---|---|
stale-index | Sources changed since last refresh | autorag refresh --method parsed,minsync |
index-not-ready | Index missing or never built | autorag refresh --json |
minsync-sync-failed | MinSync indexing failed; the message carries MinSync's own reason | Fix the reported cause, then autorag refresh --method minsync |
jikji-unavailable | Jikji binary missing or install failed | Check cargo, retry refresh |
everything-index-failed | Windows Everything instance could not start or index; message carries ES exit code and stderr | Fix the reported cause, autorag refresh --method everything --json |
embedding-identity-mismatch | Indexed vectors use a different embedder | autorag index rebuild --method minsync |
embedder-unavailable | Embedding gateway or runtime down | autorag gateway status --format json |
lock-conflict | Another runtime holds the lock | autorag gateway stop |
datasource-index-failed | Backing CLI failed to index | Run that CLI's own doctor |
datasource-empty | Store has no matching content | Re-sync with the CLI, or accept as empty |
unknown-datasource-skill | Config name is not a known template | Fix the name or add "type" |
retrieval-method-failed | One method errored during the query | Read --debug diagnostics |
auth-error | Credentials missing or rejected | Report the env var name |
query-route-fallback | Jev routing unavailable (often OPENROUTER_API_KEY unset); searched local with the original question | test -n "$OPENROUTER_API_KEY"; report the env var name, never its value |
query-decomposition-failed | Decomposition model call failed; searched the original question | Check queryDecomposition.model resolves (autorag models list --provider openrouter) |
follow-up-check-fallback | Jev post-fast-answer check unavailable; the run verified | Same as query-route-fallback |
datasource-selection-fallback | Jev datasource check unavailable; no datasource was searched before the fast answer | Same as query-route-fallback |
query-routed / datasources-selected / follow-up-skipped | Info: Jev's branch and queries / datasources searched and skipped / fast answer judged final | None; working as intended. A datasource that is never selected usually needs a clearer description in the config |
Always end with this table, one row per datasource and per AutoRAG component:
| Source | Configured | Indexed | Searchable | Issue found | Fix applied |
|---|---|---|---|---|---|
| minsync | yes | yes | yes (3 hits) | – | – |
| discord | yes | yes | no | stale archive | discrawl sync |
| telegram | no | – | – | CLI not installed | reported |
Searchable must come from an actual query in step 3, never inferred from
index state. Follow the table with the exact remaining action for every row
that is not fully green.
Done only when: core triage is clean or every remaining diagnostic is explained, every configured datasource passed its native check, every one of them returned a real hit or is proven empty, every repair was re-verified by re-running the failing check, and the report table was delivered.
© 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-doctor of Marker-Inc-Korea/AutoRAG.
Open the folder on GitHubat commit 29ccab9
AutoRAG Doctor 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 Doctor this skillMarker-Inc-Korea/AutoRAG | 5.1k | — | ~3.4k | Automated safety check: Pass | MIT | |
| Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs | 13k | 7 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Embeddings via 9Routerdecolua/9router | 31k | — | ~604 | Automated safety check: Pass | MIT | |
| AI SDK Developmenttrypostit/trypost | 692 | 1 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Retail Product Search Agentgoogle/adk-recipes | 10k | — | ~3k | Automated safety check: Pass | Apache-2.0 | |
| Evaluate RAGai-evals-course/evals-skills | 1.5k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 |
Orchestra-Research/AI-Research-SKILLs
Shows how to store documents and embeddings in Chroma, query them by similarity with metadata filters, and persist them to disk for RAG and semantic search projects.
decolua/9router
Generates vector embeddings through the 9Router /v1/embeddings endpoint, using models from providers such as OpenAI, Gemini, Mistral and Voyage for RAG and semantic search.
trypostit/trypost
TRIGGER when working with ai-sdk which is Laravel official first-party AI SDK.
google/adk-recipes
Builds a retail product search agent on Google Cloud, from catalog ingestion into BigQuery and Vector Search to ADK scaffolding, evaluation and Cloud Run deployment.
ai-evals-course/evals-skills
Guides evaluation of a RAG system by diagnosing failures in traces, building a retrieval test set and scoring retrieval and generation separately.
PackmindHub/packmind
Produce proof-of-execution demos of the Packmind CLI (packmind-cli) as terminal-styled images (colors and formatting preserved exactly), for embedding in a GitHub PR.
Marker-Inc-Korea/AutoRAG
Searches, summarizes, compares and answers questions from an already configured AutoRAG librarian agent over local documents and authorized datasources.
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
Diagnoses and repairs a broken AutoRAG install so every configured datasource is both indexed and returns real search hits. The goal is that each datasource is indexed and actually answers a query; a green status alone is not enough. The agent triages the core with status, health and gateway status commands in JSON, reads the config for search paths, workspace, MinSync, Jikji and datasources, then probes every datasource with its own native check, since each CLI owns its archive.
AutoRAG Doctor fits situations like: search returns nothing or too little; A refresh hangs or fails; A datasource has disappeared from the results; the embedding gateway will not start.
Run `npx skills add Marker-Inc-Korea/AutoRAG --skill autorag-doctor -a claude-code`. Or copy the skill folder (skills/autorag-doctor in Marker-Inc-Korea/AutoRAG) into .claude/skills/autorag-doctor in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Marker-Inc-Korea/AutoRAG --skill autorag-doctor -a codex`. Or copy the skill folder (skills/autorag-doctor in Marker-Inc-Korea/AutoRAG) into .agents/skills/autorag-doctor 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-doctor -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-doctor, .gemini/skills/autorag-doctor, .github/skills/autorag-doctor and .opencode/skills/autorag-doctor in your project.
Going by SKILL.md and its folder, AutoRAG Doctor needs the command-line tools its instructions call (cargo) and credentials named OPENROUTER_API_KEY. Our summary lists: The autorag CLI and an existing config; The CLIs of the datasources you configured.
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 Doctor is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.4k tokens (SKILL.md is roughly 14k 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 Doctor: Chroma Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars), Embeddings via 9Router (decolua/9router, 31k stars), AI SDK Development (trypostit/trypost, 692 stars) and Retail Product Search Agent (google/adk-recipes, 10k 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.