Example domain intelligence
Skill krishanjogia-collab/plektis/sdk/skills/example-domain-intelligence
Example skill file demonstrating the domain intelligence format. This is a template with placeholder content showing the required structure, frontmatter fields, and section layout. Replace with your own domain expertise.From its SKILL.md
npx -y skills add krishanjogia-collab/plektis --skill example-domain-intelligenceAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its file declares
Copied from the file, not written here
The file declares its own license as CC BY-SA 4.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
2.2 KB, 283 tokens by cl100k_base, as published. Nobody here has run it
Example Domain Intelligence Skill
Purpose
This file demonstrates the domain intelligence skill file format. When loaded, a domain intelligence skill calibrates how the agent thinks about a specific domain. It provides persistent context, not step-by-step instructions.
Replace this section with a description of what changes about the agent's behaviour when your skill is loaded.
Professional Context
Describe the domain this skill covers, who uses it, and in what engagement context. Situate the skill within a real operational environment.
[Your Domain Knowledge Sections]
This is where the substantive content lives. Organise by the natural structure of your domain. Use tables for structured data (taxonomies, scoring frameworks, signal models). Use subsections for distinct conceptual areas.
A real skill file might have sections like:
- Industry-specific signal taxonomy
- Scoring methodology with defined bands
- Data source quality assessment
- Module-specific framing for different use cases
Quality Standards
Define the analytical, communication, and ethical standards that govern any output produced while this skill is active.
Anti-Patterns
List what NOT to do. Number them for easy reference. These should be specific enough that someone could accidentally violate them.
- Do not present inferred data with the same confidence as verified data.
- Do not use generic AI-sounding language in deliverables.
- Do not skip the confidence assessment on any substantive output.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.