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- Yeachan Heo
- Oh My Claudecode
- Learn About Omc
learn-about-omc_skill
- TypeScript
9k
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill yeachan-heo/oh-my-claudecode --skill learn-about-omc- SKILL.md1.0 KB
Overview
This skill analyzes your oh-my-claudecode (OMC) usage to surface patterns and deliver personalized recommendations. It turns session history, state, and agent traces into a concise report with actionable steps to improve workflows and productivity.
How this skill works
The skill scans local OMC artifacts such as session logs, state files, project memory, notepad entries, and agent flow traces to build an activity profile. It identifies frequent modes, agent types, workflows, and completion metrics, then maps those insights to targeted recommendations for feature adoption, skill combinations, and configuration tweaks.
When to use it
- Onboard a new team to understand current OMC habits and weaknesses
- After a sprint or month to evaluate productivity and session outcomes
- When adoption stalls and you need targeted, low-friction improvements
- Before standardizing processes to align agent types and modes
- When you want to optimize configuration for speed, cost, or accuracy
Best practices
- Run the analysis periodically (weekly or monthly) to track trends over time
- Keep .omc session and state files available and unaltered for accurate results
- Combine report recommendations with a short pilot to validate changes
- Share the findings with the team and prioritize 1–3 high-impact changes
- Use the suggested skill combinations in a dedicated test session before broad rollout
Example use cases
- Discovering that a specific agent type handles bug triage far faster and adjusting workflows accordingly
- Identifying underused modes (e.g., parallel execution) and enabling them for applicable tasks
- Reducing session durations by recommending more efficient skill sequences and shortcuts
- Tuning configuration options to lower resource use while preserving completion rates
- Creating a training checklist that introduces overlooked features to new teammates
FAQ
It inspects local OMC artifacts such as .omc/sessions/, .omc/state/, .omc/notepad.md, .omc/project-memory.json, and agent flow traces.
Is any data uploaded externally?
No. The analysis runs locally on the available OMC files and produces a local report unless you choose to share it.