From evernote-pack
Optimize Evernote integration costs and resource usage. Use when managing API quotas, reducing storage usage, or optimizing upload limits. Trigger with phrases like "evernote cost", "evernote quota", "evernote limits", "evernote upload".
How this skill is triggered — by the user, by Claude, or both
Slash command
/evernote-pack:evernote-cost-tuningThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Optimize resource usage and manage costs in Evernote integrations, focusing on upload quotas, storage efficiency, and account limits.
Optimize resource usage and manage costs in Evernote integrations, focusing on upload quotas, storage efficiency, and account limits.
For full implementation details and code examples, load:
references/implementation-guide.md
For architecture patterns, see evernote-reference-architecture.
| Error | Cause | Resolution |
|---|---|---|
| Authentication failure | Invalid or expired credentials | Refresh tokens or re-authenticate with API |
| Configuration conflict | Incompatible settings detected | Review and resolve conflicting parameters |
| Resource not found | Referenced resource missing | Verify resource exists and permissions are correct |
Basic usage: Apply evernote cost tuning to a standard project setup with default configuration options.
Advanced scenario: Customize evernote cost tuning for production environments with multiple constraints and team-specific requirements.
npx claudepluginhub terrylica/claude-code-plugins-plus --plugin evernote-pack4plugins reuse this skill
First indexed Jul 11, 2026
Guides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.
Creates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.
Synthesizes the current conversation into a structured spec (PRD) and publishes it to the project issue tracker with a ready-for-agent label, without interviewing the user.