> ## Documentation Index
> Fetch the complete documentation index at: https://www.conductor.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Build a Data-Backed Content Strategy
> Decide what to write — and whether to write or optimize — by grounding every choice in live AI citation data.
export const DownloadTemplate = ({file, href}) => {
return
Download
;
};
*New to using LLM skills? Check out our [Introduction to Using Skills](/templates/introduction-to-using-skills)*
This template uses Conductor's MCP
This template uses Claude Cowork to produce its output
The `conductor-content-angle-finder` skill turns a topic into a data-backed content strategy using live Conductor MCP data.
This skill identifies which tracked prompts exist for the topic, which competitors are winning citations, and where your brand has gaps. It maps the question landscape with per-competitor performance, drills into top-cited competitor URLs to understand why they're winning, and—if a content inventory is provided—distinguishes real content gaps from AEO performance issues on existing pages.
## Walkthrough
## Change Log
*No changes to report*
The `SKILL.md` templates (and their supporting files and ZIP bundles) are
open-sourced under the **Apache License 2.0**. You may reproduce, modify,
and distribute them, provided you include a copy of the license, preserve
existing copyright and attribution notices, note any modifications you
make to the files, and propagate any `NOTICE` file that ships with the
work. Each downloadable ZIP includes `LICENSE` and `NOTICE` files with the
full terms. Access to the underlying Conductor MCP server still requires
an active Conductor MCP subscription.