Every premium and members-only resource for $9.99/month, as a no-commitment subscription. See the plans

PalateKit

Sign in
Menu

Request a resource

Describe the resource you are missing in one sentence. We will email you when it is published.

0 / 280

A page, a video or an image online.

Unlock PalateKit

Unlock everything

Plan

Paying means accepting our terms of sale.

Secure payment by Stripe. Receipts and invoices sent by email.

Welcome back

Sign in to install, download or save this resource. A free account is enough for free resources.

Math-heavy optimization for large data v1.0.0

Use this resource to find a better mathematical bound when a classic algorithm has reached its limit

New

  • 441 downloads
  • 139 likes
  • 131 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install math-heavy-algorithm-escalation

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent looks for approximate techniques suited to very large inputs (from about one million items): Bloom filters, HyperLogLog, MinHash, FFT and others. It states the expected gain and its limit, and reminds you that the caller must accept an approximate answer.

Mostly picked by

Updated November 2, 2026

Card for the “Math-heavy optimization for large data” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
Apache-2.0

Similar resources

View all

What you get

  • SKILL.md: rules and a protocol to follow before proposing a technique
  • SKILL.md: playbook by family (sketches, transforms, geometry, graphs, amortized algorithms)

Good fit for

  • Your processing on more than a million items is still too slow
  • You accept an approximate result with a known margin of error

Not for

    Tags

    • optimization
    • algorithms
    • large data
    • approximation

    About

    You say

    “Suggest an approximate approach to deduplicate 50 million IDs with limited memory.”

    Card for the “Math-heavy optimization for large data” skill

    Skill published by morsechimwai under the Apache-2.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to find a better mathematical bound when a classic algorithm has reached its limit
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md19.3 KB

    Origin and licence

    Listed unmodified

    Author
    morsechimwai
    Source
    github.com/sickn33/agentic-awesome-skills/tree/e9809578fd426a284af017c5db99f8eb6628e6ca/skills/mathguard
    Licence
    Apache-2.0

    Notice

    « mathguard » (morsechimwai, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

    User reviews

    –

    No ratings yet

    Loading reviews…

    Delete your review?

    Your rating and comment will be removed from the page.