Agent skill
gist-upload
Upload a summary or plan from the current conversation as a GitHub Gist using the `gh` CLI.
Install this agent skill to your Project
npx add-skill https://github.com/opendatahub-io/ai-helpers/tree/main/helpers/skills/gist-upload
SKILL.md
Upload to GitHub Gist
Upload content from the current conversation (a plan, summary, analysis, or other output) as a GitHub Gist using the gh CLI.
Prerequisites
ghCLI must be installed and authenticated (gh auth statusshould succeed)
Usage
This skill triggers when the user asks to upload conversation content to a gist, for example:
- "Upload the plan to gist"
- "Upload the summary of our conversation as a gist"
- "Create a gist with the analysis above"
- "Share this as a gist"
Implementation
Step 1: Identify the Content
- Look at the conversation history to identify what the user wants uploaded
- If the user says "the plan", "the summary", "the analysis", etc., find that specific content in the conversation
- If ambiguous, ask the user: "Which part of our conversation should I upload? For example, the plan, summary, or a specific section?"
Step 2: Format the Content
- Take the identified content and format it as clean markdown
- Choose a descriptive filename based on the content type, e.g.
plan.md,summary.md,analysis.md - If the content relates to a specific project or topic, include that in the filename, e.g.
migration-plan.md
Step 3: Upload via gh gist create
- Write the content to a temporary file in
/tmp/ - Upload using
gh:bashgh gist create /tmp/<filename>- Gists are created as secret by default. Note: secret gists are unlisted, not private, anyone with the URL can view them. Warn the user about this before uploading sensitive content.
- If the user explicitly asks for a public gist, add
--public
- Capture the gist URL from the command output
Step 4: Report and Clean Up
- Show the user the gist URL
- Delete the temporary file
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
python-packaging-env-finder
Investigate environment variables that can be set when building Python wheels for a given project. Analyzes setup.py, CMake files, and other build configuration files to discover customizable build environment variables.
torchtalk-analyzer
Analyze PyTorch internals across Python, C++, and CUDA layers using the TorchTalk MCP server. Use when asked about how PyTorch operators work internally, where functions are implemented, what would break if code is modified, or finding tests for PyTorch operators.
ai-bug-fix-triage
Triage JIRA bugs against repository code to classify AI fixability. Use when reviewing a backlog of bugs to determine which ones an AI agent can fix.
python-packaging-complexity
Analyze Python package build complexity by inspecting PyPI metadata. Evaluates compilation requirements, dependencies, distribution types, and provides recommendations for wheel building strategies.
coderabbit-review
Evaluate CodeRabbit PR comments and fix or reply
git-shallow-clone
Perform a shallow clone of a Git repository to a temporary location.
Didn't find tool you were looking for?