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Agent skill

Ndk Batch Event Queries

by divinevideo in divinevideo/divine-mobile

Optimize Nostr relay queries using NDK batch fetching. An agent skill from divinevideo/divine-mobile.

MPL-2.0Auto-check passed

Install Ndk Batch Event Queries

skills CLI
$ npx skills add divinevideo/divine-mobile --skill ndk-batch-event-queries -a claude-code

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

GitHub CLI
$ gh skill install divinevideo/divine-mobile ndk-batch-event-queries --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/divinevideo/divine-mobile.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/ndk-batch-event-queries .claude/skills/ndk-batch-event-queries && 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
ndk-batch-event-queries
GitHub stars
266
Token cost
~1k tokens
SKILL.md length
225 words
Files
1
Skills in repo
103
Repo updated
First seen
Licence
MPL-2.0

At a glance

Optimize Nostr relay queries using NDK batch fetching. An agent skill from divinevideo/divine-mobile.

  • Works in 4 steps: Array filters: #d, #p, #e, authors all… → Chunk size: Use 50-100 items per query… → Multiple authors: Pass array of pubkeys… → …
  • Checking existence of many events one-by-one is slow
  • SKILL.md covers Problem, Context / Trigger Conditions, Solution and Verification, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ndk Batch Event Queries is an agent skill from divinevideo/divine-mobile. Optimize Nostr relay queries using NDK batch fetching. Use when: (1) Checking existence of many events one-by-one is slow, (2) Loop with individual fetchEvents calls causing N+1 query problem, (3) Need to verify multiple addressable events (Kind 30000+) exist. NDK's fetchEvents accepts arrays for tag filters (d, p, e, authors), enabling batch queries that reduce hundreds of round-trips to a single request.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The licence is MPL-2.0.

When your agent uses it

  • Checking existence of many events one-by-one is slow
  • Loop with individual fetchEvents calls causing N+1 query problem
  • Need to verify multiple addressable events (Kind 30000+) exist

Example prompts

  • “/ndk-batch-event-queries”

Workflow steps

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

  1. Array filters: #d, #p, #e, authors all accept arrays
  2. Chunk size: Use 50-100 items per query to avoid relay limits
  3. Multiple authors: Pass array of pubkeys if checking across users
  4. Extract results: Parse the d-tag from returned events to build a Set

What it can do on your machine

Read from SKILL.md and the folder at commit 6487b05. 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 (its code samples are typescript).

    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):

    • github.com
    • nostr-dev-kit.github.io
    • nostrbook.dev

    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

Ndk Batch Event Queries loads about 1k tokens when it runs. Until then it costs about 109 tokens; SKILL.md has 225 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~109
When it runs · the whole SKILL.md, loaded when a task matches
~1k

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 divinevideo/divine-mobile at commit 6487b05, republished under its MPL-2.0 licence (© divinevideo). 225 words, ~1,005 tokens.

Download SKILL.mdSave it as .claude/skills/ndk-batch-event-queries/SKILL.md (or your agent's skills folder).
name
ndk-batch-event-queries
description
Optimize Nostr relay queries using NDK batch fetching. Use when: (1) Checking existence of many events one-by-one is slow, (2) Loop with individual fetchEvents calls causing N+1 query problem, (3) Need to verify multiple addressable events (Kind 30000+) exist. NDK's fetchEvents accepts arrays for tag filters (#d, #p, #e, authors), enabling batch queries that reduce hundreds of round-trips to a single request.
author
Claude Code
version
1.0.0
date
2026-01-25

NDK Batch Event Queries

Problem

When checking if many Nostr events exist (e.g., 300 videos for a user), querying one-by-one causes hundreds of sequential relay round-trips, making the operation extremely slow (minutes instead of seconds).

Context / Trigger Conditions

  • Loop with await fetchEvents() inside, checking events individually
  • Processing takes minutes when it should take seconds
  • Checking existence of addressable events (Kind 30000-39999) by d-tag
  • Need to find which items from a list already exist on a relay

Solution

NDK's fetchEvents filter accepts arrays for most fields. Instead of:

typescript
// SLOW: 300 sequential queries
for (const id of vineIds) {
  const exists = await ndk.fetchEvents({
    kinds: [34236],
    authors: [pubkey],
    "#d": [id],  // Single value
  });
}

Use a batch query:

typescript
// FAST: 1-3 queries (chunked if needed)
const CHUNK_SIZE = 100;  // Relays may limit query size
const existingIds = new Set<string>();

for (let i = 0; i < vineIds.length; i += CHUNK_SIZE) {
  const chunk = vineIds.slice(i, i + CHUNK_SIZE);
  const events = await ndk.fetchEvents({
    kinds: [34236],
    authors: pubkeys,  // Can also be an array
    "#d": chunk,       // Array of d-tag values
  });

  for (const event of events) {
    const dTag = event.tags.find(t => t[0] === "d");
    if (dTag?.[1]) existingIds.add(dTag[1]);
  }
}

// O(1) lookup in processing loop
for (const id of vineIds) {
  if (existingIds.has(id)) continue;  // Skip existing
  // Process new items...
}
Key Points
  1. Array filters: #d, #p, #e, authors all accept arrays
  2. Chunk size: Use 50-100 items per query to avoid relay limits
  3. Multiple authors: Pass array of pubkeys if checking across users
  4. Extract results: Parse the d-tag from returned events to build a Set

Verification

  • Processing time drops from minutes to seconds
  • Total relay connections decrease dramatically
  • Same results as individual queries (verified by comparison)

Example

Real-world application - checking 294 videos across 2 pubkeys:

typescript
async videosExistBatch(pubkeys: string[], vineIds: string[]): Promise<Set<string>> {
  await this.connect();
  const existingIds = new Set<string>();
  const CHUNK_SIZE = 100;

  for (let i = 0; i < vineIds.length; i += CHUNK_SIZE) {
    const chunk = vineIds.slice(i, i + CHUNK_SIZE);
    const events = await this.ndk.fetchEvents({
      kinds: [34236],
      authors: pubkeys,
      "#d": chunk,
    });

    for (const event of events) {
      const dTag = event.tags.find((t) => t[0] === "d");
      if (dTag && dTag[1]) {
        existingIds.add(dTag[1]);
      }
    }
  }

  return existingIds;
}

Usage:

typescript
const vineIds = vines.map(v => v.vine_id);
const existingVineIds = await relay.videosExistBatch([pubkey, oldPubkey], vineIds);
console.log(`Found ${existingVineIds.size}/${vineIds.length} already on relay`);

Notes

  • Some relays may have stricter limits on query size; adjust CHUNK_SIZE accordingly
  • The buffered queries feature in NDK can also help with component-level batching
  • For very large sets, consider parallel chunk requests with Promise.all
  • This pattern works for any tag-based lookup, not just #d tags

References

© divinevideo, MPL-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 .agents/skills/ndk-batch-event-queries of divinevideo/divine-mobile.

Open the folder on GitHubat commit 6487b05

Compare with similar skills

Ndk Batch Event Queries 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.

Ndk Batch Event Queries compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ndk Batch Event Queries this skilldivinevideo/divine-mobile266—~1kAutomated safety check: PassMPL-2.0
Optimizing Clickhouse And Hogql QueriesPostHog/posthog40k—~5.7kAutomated safety check: PassCustom licence
SQL Optimizationgithub/awesome-copilot40k2 repos~2.3kAutomated safety check: PassMIT
Optimizing SQL Queriesjeremylongshore/tons-of-skills-marketplace2.8k—~1.7kAutomated safety check: PassMIT
Detecting Ntlm Relay With Event Correlationmukul975/Anthropic-Cybersecurity-Skills34k—~8.7kAutomated safety check: PassApache-2.0
Django Orm Query Optimizationhashgraph-online/awesome-codex-plugins1.3k—~650Automated safety check: PassMIT

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Questions about Ndk Batch Event Queries

What does Ndk Batch Event Queries do?

Optimize Nostr relay queries using NDK batch fetching. An agent skill from divinevideo/divine-mobile. Ndk Batch Event Queries is an agent skill from divinevideo/divine-mobile. Optimize Nostr relay queries using NDK batch fetching.

When should I use Ndk Batch Event Queries?

Ndk Batch Event Queries fits situations like: checking existence of many events one-by-one is slow; loop with individual fetchEvents calls causing N+1 query problem; need to verify multiple addressable events (Kind 30000+) exist.

How do I install Ndk Batch Event Queries in Claude Code?

Run `npx skills add divinevideo/divine-mobile --skill ndk-batch-event-queries -a claude-code`. Or copy the skill folder (.agents/skills/ndk-batch-event-queries in divinevideo/divine-mobile) into .claude/skills/ndk-batch-event-queries in your project. Claude Code loads it when a task matches its description.

How do I install Ndk Batch Event Queries in Codex?

Run `npx skills add divinevideo/divine-mobile --skill ndk-batch-event-queries -a codex`. Or copy the skill folder (.agents/skills/ndk-batch-event-queries in divinevideo/divine-mobile) into .agents/skills/ndk-batch-event-queries in your project. Codex loads it when a task matches its description.

Can I use Ndk Batch Event Queries 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 divinevideo/divine-mobile --skill ndk-batch-event-queries -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ndk-batch-event-queries, .gemini/skills/ndk-batch-event-queries, .github/skills/ndk-batch-event-queries and .opencode/skills/ndk-batch-event-queries in your project.

What does Ndk Batch Event Queries need to run?

SKILL.md names no scripts, command-line tools or credentials: Ndk Batch Event Queries is instructions for the agent only.

Does Ndk Batch Event Queries access the network?

SKILL.md names 3 domains. As links in the text: github.com, nostr-dev-kit.github.io and nostrbook.dev. This is read from the text; nothing was executed.

Is Ndk Batch Event Queries 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 Ndk Batch Event Queries use?

Ndk Batch Event Queries is published under the MPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ndk Batch Event Queries use?

About 1k tokens (SKILL.md is roughly 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 Ndk Batch Event Queries?

Skills that share tags, products or a category with Ndk Batch Event Queries: Optimizing Clickhouse And Hogql Queries (PostHog/posthog, 40k stars), SQL Optimization (github/awesome-copilot, 40k stars), Optimizing SQL Queries (jeremylongshore/tons-of-skills-marketplace, 2.8k stars) and Detecting Ntlm Relay With Event Correlation (mukul975/Anthropic-Cybersecurity-Skills, 34k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ndk Batch Event Queries?

divinevideo (a GitHub organization) maintains it in divinevideo/divine-mobile, which has 266 GitHub stars. The repository holds 103 skills in this directory. The repository was last updated on October 9, 2026.

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