> Draft voice-tuned X (Twitter) post variants from a free-form brief. Reads a personal voice guide (generated via generate-voice-guide), produces 2–5 variants with distinct framings (simple-howto, problem-first, hype, mechanism-breakdown, etc.), and self-checks against the voice guide's banned phrases before returning.
npx skills add https://github.com/gooseworks-ai/goose-skills --skill create-x-content
Draft X/Twitter post variants that sound like you, not like an AI. Reads a voice guide the user has already generated (or prompts to create one), produces multiple framings of the same idea, and saves each variant as its own markdown file with frontmatter.
This is an agent-executed skill — the agent does the drafting and self-check inline. No Python script.
/create-x-content --brief "New open-source CLI that turns Figma files into React components. Called figma2react. Free, MIT licensed."
Or interactively:
/create-x-content
| Flag | Required | Default |
|------|----------|---------|
| --brief | Yes (asked interactively if missing) | — |
| --variants | No | Skill decides based on brief richness (2–5) |
| --voice-guide | No | Resolved via chain below |
| --output | No | ./content/YYYY-MM-DD-<topic-slug>/ |
| --topic | No | Derived from brief |
Resolve in this order, stop at first hit:
--voice-guide <path> flag~/.goose-skills/config.json → voice_guides.x~/.goose-skills/voice-guides/voice-x.md (default path)/generate-voice-guide --platforms x now to create one (recommended)Never silently skip the voice guide. Generic posts are the failure mode to avoid.
Read the resolved voice guide into context. Extract, for use throughout drafting:
Decide variant count by richness:
If --variants is explicitly set, respect it. Otherwise pick the smallest count where each variant genuinely adds a different angle. Quality > quantity. 2 strong variants beat 5 watered-down ones.
Each variant gets a distinct *framing label* that determines its structure and hook:
| Framing | Structure | When to use |
|---------|-----------|-------------|
| simple-howto | Bare steps, no mechanism | Tool install + usage, 2–3 line how-to |
| howto-plus-mechanism | How-to + "here's how it works" breakdown | Tools where the mechanism is interesting |
| problem-first | Open with the pain, then solution | When the problem is visceral/relatable |
| hype | Punchy "someone just dropped X" energy | Launches, new OSS releases, cool builds |
| mechanism-breakdown | Focus on the *how* | Technical builds, systems, architectures |
| ecosystem-map | Curated list of N related tools/companies | Landscape posts |
| contrarian | "Most people do X wrong" opener | Opinion pieces with a clear counter-take |
| personal-experience | "We've been doing X. Here's what I learned" | Field notes, lessons learned |
Use framings the voice guide's hook patterns actually support. Don't force framings the user never employs.
Before saving, run each variant through these checks:
If a variant fails any check and two rewrite attempts don't fix it, drop the variant rather than ship something weak.
Write each variant as its own .md file. File naming:
variant-<letter>-<framing-slug>.md
Examples: variant-a-simple-howto.md, variant-b-problem-first.md.
Frontmatter schema:
---
id: <topic-slug>-<letter>
platform: x
format: short | long
topic: <slug>
framing: <framing-slug>
status: draft
---
Body: just the post text. No commentary, no surrounding markdown.
Print to the user:
/social-kit for a matching graphic)<output>/variant-<letter>-<framing>.md per variantSimple brief:
/create-x-content --brief "npx goose-skills install claude-code-hooks — a new skill that adds pre-commit, pre-tool-use, and post-response hooks to Claude Code so you can enforce coding standards automatically."
→ 3 variants (howto, hype, mechanism)
Rich brief:
/create-x-content --brief "Built a Claude-driven lead gen system. Scrapes Reddit for people asking about email deliverability, finds their domains, verifies their business email via Hunter, drafts a personalized DM. 47 leads in 6 hours at $0.03/lead."
→ 5 variants (personal-experience, mechanism-breakdown, hype, problem-first, simple-howto)
generate-voice-guide skill (for creating one when missing)Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Take gooseworks-ai/create-x-content from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx.
Without those the skill loads but fails at the first command.