github/awesome-copilot
These skills were imported into SkillJury from the public skills ecosystem.
roundup
Source details, install context, and public review data are available on the full page.
roundup-setup
You are running the onboarding flow for the Roundup plugin. Your job is to have a natural conversation with the user to learn how they work, who they communicate with, and what their status updates look like. By the end, you'll generate a configuration file that the roundup skill uses to produce draft briefings on...
daily-prep
Generate a structured prep file for the next working day with meeting details, prep bullets, linked tasks, and productivity recommendations.
ruff-recursive-fix
Use this skill to enforce code quality with Ruff in a controlled, iterative workflow. It supports:
gdpr-compliant
Actionable GDPR reference for engineers, architects, DevOps, and tech leads. Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.
threat-model-analyst
Source details, install context, and public review data are available on the full page.
arize-prompt-optimization
LLM applications emit spans following OpenInference semantic conventions. Prompts are stored in different span attributes depending on the span kind and instrumentation:
arize-evaluator
This skill covers designing, creating, and running LLM-as-judge evaluators on Arize. An evaluator defines the judge; a task is how you run it against real data.
arize-instrumentation
Use this skill when the user wants to add Arize AX tracing to their application. Follow the two-phase, agent-assisted flow from the Agent-Assisted Tracing Setup and the Arize AX Tracing — Agent Setup Prompt .
integrate-context-matic
When the user asks to integrate a third-party API or implement anything involving an external API or SDK, follow this workflow. Do not rely on your own knowledge for available APIs or their capabilities — always use the context-matic MCP server.
arize-ai-provider-integration
Proceed directly with the task — run the ax command you need. Do NOT check versions, env vars, or profiles upfront.
arize-experiment
The typical flow: export a dataset → process each example → collect outputs and evaluations → create an experiment with the runs.
arize-trace
Use ax spans export to download individual spans, or ax traces export to download complete traces (all spans belonging to matching traces).
arize-annotation
This skill focuses on annotation configs — the schema for human feedback — and on programmatically annotating project spans via the Python SDK. Human review in the Arize UI (including annotation queues, datasets, and experiments) still depends on these configs; there is no ax CLI for queues yet.
arize-dataset
System-managed fields on examples ( id , created_at , updated_at ) are auto-generated by the server -- never include them in create or append payloads.
phoenix-tracing
Comprehensive guide for instrumenting LLM applications with OpenInference tracing in Phoenix. Contains reference files covering setup, instrumentation, span types, and production deployment.
phoenix-evals
Build evaluators for AI/LLM applications. Code first, LLM for nuance, validate against humans.
arize-link
Generate deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs.
onboard-context-matic
This skill delivers a guided, interactive tour of the context-matic MCP server. Follow every phase in order. Stop after each interaction point and wait for the user's reply before continuing.
phoenix-cli
Source details, install context, and public review data are available on the full page.
git-commit
Standardized git commits using Conventional Commits specification with intelligent diff analysis and message generation.
gh-cli
Complete GitHub CLI reference for repositories, issues, pull requests, Actions, projects, releases, and all command-line GitHub operations.
documentation-writer
Expert technical writer for Diátaxis-framework documentation creation across tutorials, how-to guides, reference, and explanation formats.
prd
Generate comprehensive Product Requirements Documents that translate business vision into technical specifications.