knowledge-connectors

Configure source connectors, ranking strategies, and provenance depth for knowledge retrieval.

Updated May 11, 2026

Search Tags:#retrieval #provenance #knowledge #lineage #harness #connectors

Ready to run

npx skills add https://github.com/AesopScott/mojo --skill knowledge-connectors

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: knowledge-connectors
Source: https://github.com/AesopScott/mojo/tree/main/harnesses/skills/knowledge-connectors
Command: npx skills add https://github.com/AesopScott/mojo --skill knowledge-connectors

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the problem of uncontrolled or opaque knowledge retrieval by providing a structured harness to manage source connectors, ranking strategies, and provenance depth.

Core Features & Use Cases

Capability Control: Explicitly define which data sources are searched and how chunks are ranked.
Provenance Tracking: Ensure all retrieved information includes traceable lineage for auditability.
Use Case: When integrating a new internal documentation corpus, use this skill to configure the ranking strategy and ensure the system only surfaces information with verified provenance.

Quick Start

Use the knowledge-connectors skill to define a new ranking strategy for the internal documentation harness.

Frequently Asked Questions about knowledge-connectors

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

FAQPage Schema

How do I configure source connectors for AI information retrieval?▼

Source connectors are configured using a structured harness that explicitly defines which data sources are searched and manages chunk ranking strategies to control retrieval boundaries.

How does provenance tracking work for retrieved knowledge chunks?▼

Provenance tracking ensures all retrieved information includes traceable lineage, providing auditability for AI-driven retrieval systems by recording the origin and depth of the data source.

What is the best way to enforce bounded capability expansion in a retrieval system?▼

Bounded capability expansion is enforced by managing source connectors and ranking strategies within a structured harness, ensuring the system only surfaces information with verified provenance and controlled access.

How do I apply a new ranking strategy to an internal documentation corpus?▼

Apply a new ranking strategy to an internal documentation corpus by using the knowledge harness to configure chunk evaluation rules, ensuring only explicitly defined sources are surfaced during retrieval.

When do I need traceable lineage for AI-driven information retrieval?▼

Traceable lineage is required when integrating internal documentation corpora or operating AI retrieval systems that demand verifiable retrieval performance, auditability, and controlled data access.

Can I control data access boundaries without modifying the underlying ranking strategies?▼

Data access boundaries are controlled by explicitly defining source connectors within the harness, functioning independently to restrict searched sources while ranking strategies manage chunk prioritization.