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Official agent skill

Qdrant Edge

by qdrant in qdrant/skills

Guides building on Qdrant Edge, the embedded in-process shard.

OfficialApache-2.0Auto-check passedAI & LLM Engineering

Install Qdrant Edge

skills CLI
$ npx skills add qdrant/skills --skill qdrant-edge -a claude-code

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

GitHub CLI
$ gh skill install qdrant/skills qdrant-edge --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/qdrant/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/qdrant-edge .claude/skills/qdrant-edge && 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
qdrant-edge
GitHub stars
253
Token cost
~1.3k tokens
SKILL.md length
612 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
Apache-2.0

At a glance

Guides building on Qdrant Edge, the embedded in-process shard.

  • Someone asks how to sync Edge with the server
  • SKILL.md covers Syncing a Shard with a Qdrant…, Keyword and Hybrid Search on…, Operating the Shard and What NOT to Do
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Keep a local shard in sync with Qdrant Cloud

What it does

Qdrant Edge is an agent skill from qdrant/skills, published by the product's own GitHub organization. Guides building on Qdrant Edge, the embedded in-process shard. Use when someone asks 'how to sync Edge with the server', 'keep a local shard in sync with Qdrant Cloud', 'BM25 or keyword search on Edge', 'hybrid search on Edge', 'embeddings on device', 'Edge snapshots', 'apply a partial snapshot', 'why is my Edge search empty after inserts', or is writing custom sync, BM25, or fusion code against qdrant-edge. Also use when deciding what Edge ships built-in versus what you must implement.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Vector databases and Retrieval-augmented generation. It works with Qdrant. The repository describes itself as: Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across Python…. The licence is Apache-2.0.

When your agent uses it

  • Someone asks how to sync Edge with the server
  • Keep a local shard in sync with Qdrant Cloud
  • Keyword search on Edge
  • Hybrid search on Edge

Example prompts

  • “how to sync Edge with the server”
  • “keep a local shard in sync with Qdrant Cloud”
  • “BM25 or keyword search on Edge”
  • “/qdrant-edge”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 476a18d. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    Links to these hosts (documentation or services it may open):

    • skills.qdrant.tech

    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.

Context cost

Qdrant Edge loads about 1.3k tokens when it runs. Until then it costs about 126 tokens; SKILL.md has 612 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~126
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

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 qdrant/skills at commit 476a18d, republished under its Apache-2.0 licence (© qdrant). 612 words, ~1,345 tokens.

Download SKILL.mdSave it as .claude/skills/qdrant-edge/SKILL.md (or your agent's skills folder).
name
qdrant-edge
description
Guides building on Qdrant Edge, the embedded in-process shard. Use when someone asks 'how to sync Edge with the server', 'keep a local shard in sync with Qdrant Cloud', 'BM25 or keyword search on Edge', 'hybrid search on Edge', 'embeddings on device', 'Edge snapshots', 'apply a partial snapshot', 'why is my Edge search empty after inserts', or is writing custom sync, BM25, or fusion code against qdrant-edge. Also use when deciding what Edge ships built-in versus what you must implement.

Building on Qdrant Edge

Edge is the Qdrant engine embedded in your process (Python or Rust), not a thin local vector store to wrap. The failure mode is rebuilding what the shard already ships: keyword scoring, snapshot apply, faceting, counting. Before writing any of that, check the shard API. One thing Edge does NOT give you is a one-call cloud sync, so knowing what is built in keeps you from both reinventing built-ins and expecting capabilities Edge lacks. Edge is single-node and shares the server's data format.

  • Edge is in beta: pin your version, the API drifts between releases Qdrant Edge.

Syncing a Shard with a Qdrant Server

Use when: seeding a shard from a server, keeping it fresh, backing it up, or aggregating many devices into one collection.

There is no built-in .sync(). Sync is a pattern you assemble from shard helpers plus your own transport, so do not go looking for one call.

  • Follow the documented dual-shard pattern: a mutable shard for local writes plus an immutable shard restored from a server snapshot, query both, refresh on a schedule Edge synchronization guide.
  • You write the snapshot download (plain HTTP to the shard snapshot endpoint), then apply it with unpack_snapshot and update_from_snapshot. Do not untar or merge segments by hand Synchronization patterns.
  • Refresh incrementally with a partial snapshot built from snapshot_manifest, not a full snapshot every cycle Synchronization patterns.
  • Push is your own dual-write: on each local upsert, enqueue the point and let a background worker upsert it to the server, buffering while offline Synchronization patterns.

Keyword and Hybrid Search on Device

Use when: you need exact-term or BM25 matching, alone or alongside vectors.

  • BM25 is built into Edge (Bm25, Bm25Config, embed_document, embed_query) with the IDF Modifier on EdgeSparseVectorParams, and is wire-compatible with server BM25: a shard seeded from a server snapshot answers local BM25 queries without re-indexing. Do not ship a second BM25 library Edge BM25
  • Dense embeddings are NOT in Edge: generate them on device with the separate fastembed package FastEmbed embeddings
  • For hybrid search, run the dense and sparse legs as prefetches and fuse them with a Fusion query in a single query call, instead of combining rankings in application code Reading data
Show full SKILL.md (245 more words)Show less

Operating the Shard

Use when: writes have accumulated, search looks stale after inserts, or a backup is larger than the data.

  • Edge has NO background optimizer. Call optimize after bulk writes: it builds indexes (including the sparse index) and reclaims deleted points. Skip it and that data stays unindexed Edge quickstart
  • Faceting, counting, and enumeration are built in (facet, count, scroll); index the fields you filter or facet with create_field_index rather than aggregating in application code Edge quickstart
  • The write-ahead log is pre-allocated to 32 MB and inflates apparent disk and backup size. Shrink it with wal_options (Rust), and do not treat raw file size as real usage Edge quickstart

What NOT to Do

  • Expect a bidirectional .sync() or a built-in push path: Edge gives you snapshot apply, you own the transport and the dual-write
  • Untar or merge snapshot segments by hand instead of using unpack_snapshot and update_from_snapshot
  • Ship a custom or third-party BM25 when Edge has one built in
  • Use embed_document for queries or embed_query for documents: the weighting differs and results go wrong
  • Combine dense and sparse rankings in application code: Edge query accepts prefetches and fuses them with a Fusion query
  • Assume a background optimizer like the server's: nothing is indexed or compacted until you call optimize
  • Reach for Edge when you need distributed or multi-node search: it is single-node Qdrant Edge
  • Claim support for a language beyond Python and Rust, or an OS or accelerator the Edge docs do not state

© qdrant, Apache-2.0. 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 skills/qdrant-edge of qdrant/skills.

Open the folder on GitHubat commit 476a18d

Compare with similar skills

Qdrant Edge 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.

Qdrant Edge compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Qdrant Edge this skillqdrant/skills253—~1.3kAutomated safety check: PassApache-2.0
RAG Implementationwshobson/agents40k9 repos~1.1kAutomated safety check: PassMIT
Hunt RAG Vectorelementalsouls/Claude-BugHunter4.8k—~2.6kAutomated safety check: PassMIT
Qdrant Search Qualitygithub/awesome-copilot40k1 repos~336Automated safety check: PassMIT
QdrantLuciole-Studio/Misaka-Agent1251 repos~3.4kAutomated safety check: PassMIT
Building RAG Systemsaiskillstore/marketplace4301 repos~2.7kAutomated safety check: PassNone

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Works with

Categories

Questions about Qdrant Edge

What does Qdrant Edge do?

Guides building on Qdrant Edge, the embedded in-process shard. Qdrant Edge is an agent skill from qdrant/skills, published by the product's own GitHub organization. Guides building on Qdrant Edge, the embedded in-process shard.

When should I use Qdrant Edge?

Qdrant Edge fits situations like: someone asks how to sync Edge with the server; keep a local shard in sync with Qdrant Cloud; keyword search on Edge; hybrid search on Edge.

How do I install Qdrant Edge in Claude Code?

Run `npx skills add qdrant/skills --skill qdrant-edge -a claude-code`. Or copy the skill folder (skills/qdrant-edge in qdrant/skills) into .claude/skills/qdrant-edge in your project. Claude Code loads it when a task matches its description.

How do I install Qdrant Edge in Codex?

Run `npx skills add qdrant/skills --skill qdrant-edge -a codex`. Or copy the skill folder (skills/qdrant-edge in qdrant/skills) into .agents/skills/qdrant-edge in your project. Codex loads it when a task matches its description.

Can I use Qdrant Edge 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 qdrant/skills --skill qdrant-edge -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qdrant-edge, .gemini/skills/qdrant-edge, .github/skills/qdrant-edge and .opencode/skills/qdrant-edge in your project.

What does Qdrant Edge need to run?

SKILL.md names no scripts, command-line tools or credentials: Qdrant Edge is instructions for the agent only. Our summary lists: Python 3.

Does Qdrant Edge access the network?

SKILL.md names 1 domain. As links in the text: skills.qdrant.tech. This is read from the text; nothing was executed.

Is Qdrant Edge 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 Qdrant Edge use?

Qdrant Edge is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Qdrant Edge use?

About 1.3k tokens (SKILL.md is roughly 5.4k 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 Qdrant Edge?

Skills that share tags, products or a category with Qdrant Edge: RAG Implementation (wshobson/agents, 40k stars), Hunt RAG Vector (elementalsouls/Claude-BugHunter, 4.8k stars), Qdrant Search Quality (github/awesome-copilot, 40k stars) and Qdrant (Luciole-Studio/Misaka-Agent, 125 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qdrant Edge?

qdrant (a GitHub organization, an official publisher) maintains it in qdrant/skills, which has 253 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 6, 2026.

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