com um clique
com um clique
How stagewise's agent history compression pipeline works — boundary selection, recency bias, chained compressions, and the SQLite-backed test harness for replaying real compressions in LLM playgrounds. Use when debugging, tuning, or extending history compression, when investigating context-window overflow, or when the user wants to probe compression quality against real chat histories.
Complete guide for the Figma plugin — REST API access, real-time selection monitoring via CDP, and the figma-app interactive UI. Read this IMMEDIATELY when the user asks to work with Figma.
Create a structured implementation plan before coding
Create or edit video with Remotion. First-party stagewise + Remotion skill. Contains full video-making process.
Use logging calls for in-depth debugging via local log files
Create, extract, or update a skill. Use when authoring a new skill from scratch, extracting knowledge from the current session, or updating an existing skill when the user's intentions contradicted skill guidance or content is confusing/outdated.
| name | Implement |
| description | Implement the most recent plan |
| user-invocable | false |
| agent-invocable | false |
Implement the most recently created plan.
- [ ] → - [x] in the plan file immediately — before moving on. Do NOT batch updates.[x]. Unnecessary tasks: delete the checkbox + add brief rationale. Never leave unchecked boxes.## Follow-ups for the user prose section, and continue. Never leave it unchecked waiting on the user.