adobe-debug-bundle
Collect Adobe debug evidence for support tickets and troubleshooting. Use when encountering persistent issues, preparing support tickets, or collecting diagnostic information for Adobe API problems. Trigger with phrases like "adobe debug", "adobe support bundle", "collect adobe logs", "adobe diagnostic". '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill adobe-debug-bundle --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Adobe Debug Bundle ## Overview Collect all necessary diagnostic information for Adobe support tickets. This script gathers SDK versions, credential validation status, API connectivity, and redacted configuration into a support-ready archive. ## Prerequisites - Adobe credentials configured (env vars or `.env` file) - Node.js or Python environment with Adobe SDKs installed - Permission to run netw
What does the adobe-debug-bundle skill do?
Collect Adobe debug evidence for support tickets and troubleshooting. Use when encountering persistent issues, preparing support tickets, or collecting diagnostic information for Adobe API problems. Trigger with phrases like "adobe debug", "adobe support bundle", "collect adobe logs", "adobe diagnostic". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill adobe-debug-bundle --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
