dag-skills-matcher

Name: dag-skills-matcher
Availability: InStock
Author: Curiositech

Match task descriptions to suitable skills using semantic similarity and performance history.

2|Updated Feb 11, 2026

Search Tags:#automation #workflow #catalog #ranking #dag #skill-matching #semantic-similarity

Ready to run

npx skills add https://github.com/curiositech/port-daddy --skill dag-skills-matcher

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dag-skills-matcher
Source: https://github.com/curiositech/port-daddy/tree/main/skills/dag-skills-matcher
Command: npx skills add https://github.com/curiositech/port-daddy --skill dag-skills-matcher

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill maps natural language task descriptions to the most suitable skills, ranks candidates by fit and performance history, and maintains the skill catalog to streamline DAG node assignments.

Core Features & Use Cases

Semantic similarity-based matching to identify the best-fitting skills for a given task description.
Candidate ranking by fit score, Elo, and historical performance, with escalation when needed.
Catalog maintenance to keep the skill marketplace up-to-date and browsable.

Quick Start

Query the system with a task description to find the most compatible skill from the catalog.

Frequently Asked Questions about dag-skills-matcher

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

FAQPage Schema

How do I match natural language task descriptions to the right skills for DAG node assignment?▼

Match task descriptions to suitable skills using semantic similarity and performance history. The system normalizes input, scores candidates by fit and Elo, and filters results with NOT clauses to streamline DAG node assignments.

What is the best way to rank candidate skills by fit and historical performance?▼

Rank candidate skills using a multi-criteria scoring system that evaluates semantic similarity, Elo ratings, and historical performance. This ranking identifies the best-fitting skills and routes escalations when suitable matches are not found.

How does semantic similarity work for discovering skills in an automation workflow catalog?▼

Semantic similarity compares normalized natural language task descriptions against a browsable skill catalog. It calculates fit scores to identify and retrieve the most compatible skills available for your automation workflow.

Can I filter out specific skills or apply exclusion criteria when matching tasks?▼

Yes, you can exclude specific skills using NOT clause filtering. This removes unwanted candidates from the matching results before final ranking, ensuring only relevant skills are considered for your task.

When should I use escalation routing for skill matching in a DAG?▼

Use escalation routing when semantic similarity and performance history cannot identify a suitable skill match for your task description. It handles edge cases where no existing catalog entry meets the required fit score threshold.

Does the skill matcher require dependencies to maintain a browsable skill catalog?▼

No dependencies are required. The skill matcher operates independently to maintain a browsable skill catalog, providing input normalization, multi-criteria scoring, and candidate ranking for task matching without external libraries.