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Official agent skill

Qdrant Sliding Time Window

by qdrant in qdrant/skills

Guides sliding time window scaling in Qdrant. An agent skill from qdrant/skills.

OfficialApache-2.0Auto-check passedDatabases

Install Qdrant Sliding Time Window

skills CLI
$ npx skills add qdrant/skills --skill qdrant-sliding-time-window -a claude-code

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

GitHub CLI
$ gh skill install qdrant/skills qdrant-sliding-time-window --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-scaling/scaling-data-volume/sliding-time-window .claude/skills/qdrant-sliding-time-window && 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-sliding-time-window
GitHub stars
253
Used in
2 other repos
Token cost
~1.2k tokens
SKILL.md length
542 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
Apache-2.0

At a glance

Guides sliding time window scaling in Qdrant. An agent skill from qdrant/skills.

  • Works in 5 steps: Create a collection with user-defined… → Create one shard key per time period… → Ingest data into the current period's… → …
  • Someone asks only recent data matters
  • SKILL.md covers Shard Rotation (Recommended), Collection Rotation (Alias Swap), Filter-and-Delete and Hot/Cold Tiers, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Qdrant Sliding Time Window is an agent skill from qdrant/skills, published by the product's own GitHub organization. Guides sliding time window scaling in Qdrant. Use when someone asks 'only recent data matters', 'how to expire old vectors', 'time-based data rotation', 'delete old data efficiently', 'social media feed search', 'news search', 'log search with retention', or 'how to keep only last N months of data'.

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 asks only recent data matters
  • How to expire old vectors
  • Time-based data rotation
  • Delete old data efficiently

Example prompts

  • “only recent data matters”
  • “how to expire old vectors”
  • “time-based data rotation”
  • “/qdrant-sliding-time-window”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Create a collection with user-defined sharding enabled
  2. Create one shard key per time period (e.g., 2025-01, 2025-02, ..., 2025-06)
  3. Ingest data into the current period's shard key
  4. When a new period starts, create a new shard key and redirect writes
  5. Delete the oldest shard key outside the retention window

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 Sliding Time Window loads about 1.2k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 542 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~82
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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). 542 words, ~1,184 tokens.

Download SKILL.mdSave it as .claude/skills/qdrant-sliding-time-window/SKILL.md (or your agent's skills folder).
name
qdrant-sliding-time-window
description
Guides sliding time window scaling in Qdrant. Use when someone asks 'only recent data matters', 'how to expire old vectors', 'time-based data rotation', 'delete old data efficiently', 'social media feed search', 'news search', 'log search with retention', or 'how to keep only last N months of data'.

Scaling with a Sliding Time Window

Use when only recent data needs fast search -- social media posts, news articles, support tickets, logs, job listings. Old data either becomes irrelevant or can tolerate slower access.

Three strategies: shard rotation (recommended), collection rotation (when per-period config differs), and filter-and-delete (simplest, for continuous cleanup).

Use when: data has natural time boundaries (daily, weekly, monthly). Preferred because queries span all time periods in one request without application-level fan-out. User-defined sharding

  1. Create a collection with user-defined sharding enabled
  2. Create one shard key per time period (e.g., 2025-01, 2025-02, ..., 2025-06)
  3. Ingest data into the current period's shard key
  4. When a new period starts, create a new shard key and redirect writes
  5. Delete the oldest shard key outside the retention window
  • Deleting a shard key reclaims all resources instantly (no fragmentation, no optimizer overhead)
  • Pre-create the next period's shard key before rotation to avoid write disruption
  • Use shard_key_selector at query time to search only specific periods for efficiency
  • Shard keys can be placed on specific nodes for hot/cold tiering

Collection Rotation (Alias Swap)

Use when: you need per-period collection configuration (e.g., different quantization or storage settings). Collection aliases

  1. Create one collection per time period, point a write alias at the newest
  2. Query across all active collections in parallel, merge results client-side
  3. When a new period starts, create the new collection and swap the write alias Switch collection
  4. Drop the oldest collection outside the window

Trade-off vs shard rotation: allows per-collection config differences, but requires application-level fan-out and more operational overhead.

Filter-and-Delete

Use when: data arrives continuously without clear time boundaries, or you want the simplest setup.

  1. Store a timestamp payload on every point, create a payload index on it Payload index
  2. Filter to the desired window at query time using range condition Range filter
  3. Periodically delete expired points using delete-by-filter Delete points
  • Run cleanup during off-peak hours in batches (10k-50k points) to avoid optimizer locks
  • Deletes are not free: tombstoned points degrade search until optimizer compacts segments
  • Does not reclaim disk instantly (compaction is asynchronous)
Show full SKILL.md (189 more words)Show less

Hot/Cold Tiers

Use when: recent data needs fast in-RAM search, older data should remain searchable at lower performance.

  • Shard rotation: place current shard key on fast-storage nodes, move older shard keys to cheaper nodes via shard placement. All queries still go through a single collection.
  • Collection rotation: keep the current collection's quantized vectors in RAM (memory: pinned on Qdrant 1.19 or newer, always_ram: true on 1.18 or older) and its dense vectors in page cache (memory: cached, the default; Qdrant rejects pinned for dense vectors), move older collections to mmap/on-disk vectors (memory: cold on 1.19 or newer, on_disk: true on 1.18 or older). Quantization

What NOT to Do

  • Do not use filter-and-delete for high-volume time-series with millions of daily deletes (use rotation instead)
  • Do not forget to index the timestamp field (range filters without an index cause full scans)
  • Do not use collection rotation when shard rotation would suffice (unnecessary fan-out complexity)
  • Do not drop a shard key or collection before verifying its period is fully outside the retention window
  • Do not skip pre-creating the next period's shard key or collection (write failures during rotation are hard to recover)

© 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-scaling/scaling-data-volume/sliding-time-window 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 Sliding Time Window 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 Sliding Time Window compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Qdrant Sliding Time Window this skillqdrant/skills2532 repos~1.2kAutomated safety check: PassApache-2.0
Qdrant Performance Optimizationgithub/awesome-copilot40k1 repos~461Automated safety check: PassMIT
Qdrant Scalinggithub/awesome-copilot40k1 repos~467Automated safety check: PassMIT
Codebase Explorationgiancarloerra/SocratiCode3.3k1 repos~1.5kAutomated safety check: PassAGPL-3.0
Qdrant Vector SearchOrchestra-Research/AI-Research-SKILLs13k5 repos~3.4kAutomated safety check: PassMIT
Using Vector Databasesancoleman/ai-design-components5261 repos~3.5kAutomated safety check: PassMIT

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Works with

Categories

Questions about Qdrant Sliding Time Window

What does Qdrant Sliding Time Window do?

Guides sliding time window scaling in Qdrant. An agent skill from qdrant/skills. Qdrant Sliding Time Window is an agent skill from qdrant/skills, published by the product's own GitHub organization. Guides sliding time window scaling in Qdrant.

When should I use Qdrant Sliding Time Window?

Qdrant Sliding Time Window fits situations like: someone asks only recent data matters; how to expire old vectors; time-based data rotation; delete old data efficiently.

How do I install Qdrant Sliding Time Window in Claude Code?

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

How do I install Qdrant Sliding Time Window in Codex?

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

Can I use Qdrant Sliding Time Window 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-sliding-time-window -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-sliding-time-window, .gemini/skills/qdrant-sliding-time-window, .github/skills/qdrant-sliding-time-window and .opencode/skills/qdrant-sliding-time-window in your project.

What does Qdrant Sliding Time Window need to run?

SKILL.md names no scripts, command-line tools or credentials: Qdrant Sliding Time Window is instructions for the agent only.

Does Qdrant Sliding Time Window 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 Sliding Time Window 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 Sliding Time Window use?

Qdrant Sliding Time Window 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 Sliding Time Window use?

About 1.2k tokens (SKILL.md is roughly 4.7k 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 Sliding Time Window?

Skills that share tags, products or a category with Qdrant Sliding Time Window: Qdrant Performance Optimization (github/awesome-copilot, 40k stars), Qdrant Scaling (github/awesome-copilot, 40k stars), Codebase Exploration (giancarloerra/SocratiCode, 3.3k stars) and Qdrant Vector Search (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qdrant Sliding Time Window?

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.