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Diagnoses and fixes slow Qdrant search. An agent skill from qdrant/skills.
Install Qdrant Search Speed Optimization
$ npx skills add qdrant/skills --skill qdrant-search-speed-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install qdrant/skills qdrant-search-speed-optimization --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/qdrant/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/qdrant-performance-optimization/search-speed-optimization .claude/skills/qdrant-search-speed-optimization && 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 "qdrant-search-speed-optimization" agent skill from https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization/search-speed-optimization into .claude/skills/qdrant-search-speed-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qdrant-search-speed-optimization", 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/qdrant/skills/tree/main/skills/qdrant-performance-optimization/search-speed-optimizationType 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 qdrant/skills --skill qdrant-search-speed-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install qdrant/skills qdrant-search-speed-optimization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/qdrant/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/qdrant-performance-optimization/search-speed-optimization .agents/skills/qdrant-search-speed-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "qdrant-search-speed-optimization" agent skill from https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization/search-speed-optimization into .agents/skills/qdrant-search-speed-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qdrant-search-speed-optimization", 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 qdrant/skills --skill qdrant-search-speed-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install qdrant/skills qdrant-search-speed-optimization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/qdrant/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/qdrant-performance-optimization/search-speed-optimization .cursor/skills/qdrant-search-speed-optimization && 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 "qdrant-search-speed-optimization" agent skill from https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization/search-speed-optimization into .cursor/skills/qdrant-search-speed-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qdrant-search-speed-optimization", 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/qdrant/skills.git --path skills/qdrant-performance-optimization/search-speed-optimization--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 qdrant/skills --skill qdrant-search-speed-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install qdrant/skills qdrant-search-speed-optimization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/qdrant/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/qdrant-performance-optimization/search-speed-optimization .gemini/skills/qdrant-search-speed-optimization && 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 "qdrant-search-speed-optimization" agent skill from https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization/search-speed-optimization into .gemini/skills/qdrant-search-speed-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qdrant-search-speed-optimization", 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 qdrant/skills qdrant-search-speed-optimizationInstalls 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 qdrant/skills --skill qdrant-search-speed-optimization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/qdrant/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/qdrant-performance-optimization/search-speed-optimization .github/skills/qdrant-search-speed-optimization && 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 "qdrant-search-speed-optimization" agent skill from https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization/search-speed-optimization into .github/skills/qdrant-search-speed-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qdrant-search-speed-optimization", 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 qdrant/skills --skill qdrant-search-speed-optimization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install qdrant/skills qdrant-search-speed-optimization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/qdrant/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/qdrant-performance-optimization/search-speed-optimization .opencode/skills/qdrant-search-speed-optimization && 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 "qdrant-search-speed-optimization" agent skill from https://github.com/qdrant/skills/tree/main/skills/qdrant-performance-optimization/search-speed-optimization into .opencode/skills/qdrant-search-speed-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qdrant-search-speed-optimization", 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.
Facts
- Skill name
qdrant-search-speed-optimization- GitHub stars
- 253
- Used in
- 2 other repos
- Token cost
- ~1.2k tokens
- SKILL.md length
- 470 words
- Files
- 1
- Skills in repo
- 33
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Diagnoses and fixes slow Qdrant search. An agent skill from qdrant/skills.
- Someone reports search is slow
- SKILL.md covers Single Query Too Slow (Latency), Can't Handle Enough QPS…, Filtered Search Is Slow and Optimize search performance…, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Queries take too long
What it does
Qdrant Search Speed Optimization is an agent skill from qdrant/skills, published by the product's own GitHub organization. Diagnoses and fixes slow Qdrant search. Use when someone reports 'search is slow', 'high latency', 'queries take too long', 'low QPS', 'throughput too low', 'filtered search is slow', or 'search was fast but now it's slow'. Also use when search performance degrades after config changes or data growth.
Its SKILL.md is about 1.2k 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 Databases, covering Vector databases. 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 reports search is slow
- Queries take too long
- Throughput too low
- Filtered search is slow
Example prompts
- “search is slow”
- “high latency”
- “queries take too long”
- “/qdrant-search-speed-optimization”
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 Search Speed Optimization loads about 1.2k tokens when it runs. Until then it costs about 84 tokens; SKILL.md has 470 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.
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). 470 words, ~1,231 tokens.
Download SKILL.mdSave it as
.claude/skills/qdrant-search-speed-optimization/SKILL.md (or your agent's skills folder).- name
- qdrant-search-speed-optimization
- description
- Diagnoses and fixes slow Qdrant search. Use when someone reports 'search is slow', 'high latency', 'queries take too long', 'low QPS', 'throughput too low', 'filtered search is slow', or 'search was fast but now it's slow'. Also use when search performance degrades after config changes or data growth.
Diagnose a problem
There the multiple possible reasons for search performance degradation. The most common ones are:
- Memory pressure: if the working set exceeds available RAM
- Complex requests (e.g. high
hnsw_ef, complex filters without payload index) - Competing background processes (e.g. optimizer still running after bulk upload)
- Problem with the cluster (e.g. network issues, hardware degradation)
Single Query Too Slow (Latency)
Use when: individual queries take too long regardless of load.
Diagnostic steps:
- Check if second run of the same request is significantly faster (indicates memory pressure)
- Try the same query with
with_payload: falseandwith_vectors: falseto see if payload retrieval is the bottleneck - If request uses filters, try to remove them one by one to identify if a specific filter condition is the bottleneck
Common fixes:
- Tune HNSW parameters: Fine-tuning search
- Enable in-memory quantization: Scalar quantization
- Reduce Vector Dimensionality with Matryoshka Models: Matryoshka Models
- Use oversampling + rescore for high-dimensional vectors Search with quantization
- Enable io_uring for disk-heavy workloads on Linux io_uring
Can't Handle Enough QPS (Throughput)
Use when: system can't serve enough queries per second under load.
- Reduce segment count (
default_segment_numberto 2) Maximizing throughput - Use batch search API instead of single queries Batch search
- Enable quantization to reduce CPU cost Scalar quantization
- Add replicas to distribute read load Replication
Filtered Search Is Slow
Use when: filtered search is significantly slower than unfiltered. Most common SA complaint after memory.
- Create payload index on the filtered field Payload index
- Use
is_tenant=truefor primary filtering condition: Tenant index - Try ACORN algorithm for complex filters: ACORN
- Avoid using
nestedfiltering conditions as a primary filter. It might force qdrant to read raw payload values instead of using index. - If payload index was added after HNSW build, trigger re-index to create filterable subgraph links
Show full SKILL.md (179 more words)Show less
Optimize search performance with parallel updates
Diagnostic steps
- Try to run the same query with
indexed_only=trueparameter, if the query is significantly faster, it means that the optimizer is still running and has not yet indexed all segments. - If CPU or IO usage is high even with no queries, it also indicates that the optimizer is still running.
Recommended configuration changes
- reduce
optimizer_cpu_budgetto reserve more CPU for queries - Use
prevent_unoptimized=trueto prevent creating segments with a large amount of unindexed data for searches. Instead, once a segment reaches the so called indexing_threshold, all additional points will be added in ‘deferred state’.
Learn more here
What NOT to Do
- Set quantization to not stay in RAM (disk thrashing on every search): avoid
memory: cold/cachedon Qdrant 1.19 or newer; on 1.18 or older, avoid leavingalways_ramfalse or unset while the original vectors areon_disk: true - Put HNSW on disk for latency-sensitive production (only for cold storage)
- Increase segment count for throughput (opposite: fewer = better)
- Create payload indexes on every field (wastes memory)
- Blame Qdrant before checking optimizer status
© 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-performance-optimization/search-speed-optimization of qdrant/skills.
Open the folder on GitHubat commit 476a18d
Used in 2 other repositories
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in qdrant/skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Qdrant Search Speed Optimization 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 |
|---|---|---|---|---|---|---|
| Qdrant Search Speed Optimization this skillqdrant/skills | 253 | 2 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Codebase Explorationgiancarloerra/SocratiCode | 3.3k | 1 repos | ~1.5k | Automated safety check: Pass | AGPL-3.0 | |
| Qdrant Vector SearchOrchestra-Research/AI-Research-SKILLs | 13k | 5 repos | ~3.4k | Automated safety check: Pass | MIT | |
| Using Vector Databasesancoleman/ai-design-components | 526 | 1 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Qdrant Search Strategiesgithub/awesome-copilot | 40k | 1 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Qdrantgiuseppe-trisciuoglio/developer-kit | 355 | 1 repos | ~1.6k | Automated safety check: Notes | MIT |
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Related
Works with
Categories
Questions about Qdrant Search Speed Optimization
What does Qdrant Search Speed Optimization do?
Diagnoses and fixes slow Qdrant search. An agent skill from qdrant/skills. Qdrant Search Speed Optimization is an agent skill from qdrant/skills, published by the product's own GitHub organization. Diagnoses and fixes slow Qdrant search.
When should I use Qdrant Search Speed Optimization?
Qdrant Search Speed Optimization fits situations like: someone reports search is slow; queries take too long; throughput too low; filtered search is slow.
How do I install Qdrant Search Speed Optimization in Claude Code?
Run `npx skills add qdrant/skills --skill qdrant-search-speed-optimization -a claude-code`. Or copy the skill folder (skills/qdrant-performance-optimization/search-speed-optimization in qdrant/skills) into .claude/skills/qdrant-search-speed-optimization in your project. Claude Code loads it when a task matches its description.
How do I install Qdrant Search Speed Optimization in Codex?
Run `npx skills add qdrant/skills --skill qdrant-search-speed-optimization -a codex`. Or copy the skill folder (skills/qdrant-performance-optimization/search-speed-optimization in qdrant/skills) into .agents/skills/qdrant-search-speed-optimization in your project. Codex loads it when a task matches its description.
Can I use Qdrant Search Speed Optimization 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-search-speed-optimization -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-search-speed-optimization, .gemini/skills/qdrant-search-speed-optimization, .github/skills/qdrant-search-speed-optimization and .opencode/skills/qdrant-search-speed-optimization in your project.
What does Qdrant Search Speed Optimization need to run?
SKILL.md names no scripts, command-line tools or credentials: Qdrant Search Speed Optimization is instructions for the agent only.
Does Qdrant Search Speed Optimization 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 Search Speed Optimization 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 Search Speed Optimization use?
Qdrant Search Speed Optimization 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 Search Speed Optimization use?
About 1.2k tokens (SKILL.md is roughly 4.9k 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 Search Speed Optimization?
Skills that share tags, products or a category with Qdrant Search Speed Optimization: Codebase Exploration (giancarloerra/SocratiCode, 3.3k stars), Qdrant Vector Search (Orchestra-Research/AI-Research-SKILLs, 13k stars), Using Vector Databases (ancoleman/ai-design-components, 526 stars) and Qdrant Search Strategies (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Qdrant Search Speed Optimization?
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.