filter

Filter collection items by applying binary keep or drop criteria.

14|6|Updated Feb 3, 2026

Search Tags:#grep #remove #filter #prune #sift #exclude

Ready to run

npx skills add https://github.com/tyevans/tackline --skill filter-tyevans

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: filter
Source: https://github.com/tyevans/tackline/tree/main/skills/core/filter
Command: npx skills add https://github.com/tyevans/tackline --skill filter-tyevans

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill efficiently removes irrelevant items from a collection based on a specified criterion, ensuring you only work with the data that matters.

Core Features & Use Cases

Selective Removal: Applies a binary keep/drop logic to each item in a collection.
Contextual Filtering: Works with data piped from upstream skills or extracted directly from conversation context.
Use Case: After gathering a list of potential security vulnerabilities, use this Skill to filter out only those marked as "high risk" or "confirmed".

Quick Start

Filter the current list of items to keep only those that are security-related.

Frequently Asked Questions about filter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I filter items out of a data collection?▼

To filter items out of a collection, apply a binary keep or drop criterion against each element. The Skill evaluates your specified rules to retain matching entries and drops irrelevant ones from the dataset.

Can I use positive and negative criteria to exclude items from a list?▼

Yes, you can use both positive and negative criteria to exclude items from a list. When filtering rules are ambiguous, the mechanism conservatively retains items unless they are explicitly excluded by your negative criteria.

What is the best way to prune irrelevant entries after gathering data?▼

The best way to prune irrelevant entries after data gathering is applying binary keep or drop logic. This mechanism evaluates each element against your user-defined rules to selectively remove irrelevant items from the collection.

Does this filtering approach work with data piped from upstream tasks?▼

Yes, this filtering approach works with data piped from upstream tasks or extracted directly from conversation context. It processes the incoming collection to remove irrelevant entries based on your defined rules.

When should I not use a conservative filtering approach?▼

You should not use a conservative filtering approach when you need aggressive data reduction. Because it retains items unless explicitly excluded by your rules, ambiguous criteria will keep more items in the collection than a strict inclusion filter would.