Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component...
npx skills add ZhanlinCui/Ultimate-Agent-Skills-Collection --skill "chat-compactor"
Install specific skill from multi-skill repository
# Description
Generate structured session summaries optimized for future AI agent consumption. Use when (1) ending a coding/debugging session, (2) user says "compact", "summarize session", "save context", or "wrap up", (3) context window is getting long and continuity matters, (4) before switching tasks or taking a break. Produces machine-readable handoff documents that let the next session start fluently without re-explaining.
# SKILL.md
name: chat-compactor
description: Generate structured session summaries optimized for future AI agent consumption. Use when (1) ending a coding/debugging session, (2) user says "compact", "summarize session", "save context", or "wrap up", (3) context window is getting long and continuity matters, (4) before switching tasks or taking a break. Produces machine-readable handoff documents that let the next session start fluently without re-explaining.
Chat Compactor
Generate structured summaries optimized for AI agent continuity across sessions.
Why This Exists
Human-written summaries and ad-hoc AI summaries lose critical context:
- Decision rationale gets lost (why X, not Y)
- Dead ends get forgotten (agent re-tries failed approaches)
- Implicit knowledge isn't captured (file locations, naming conventions, gotchas)
- State is unclear (what's done, what's pending, what's blocked)
This skill produces agent-optimized handoff documents that prime the next session.
Output Format
Generate a markdown file with this structure:
# Session: [Brief Title]
Date: [YYYY-MM-DD]
Duration: ~[X] messages
## Context Snapshot
[1-2 sentences: What project/task, what state it's in right now]
## What Was Accomplished
- [Concrete outcome 1]
- [Concrete outcome 2]
## Key Decisions & Rationale
| Decision | Why | Alternatives Rejected |
|----------|-----|----------------------|
| [Choice] | [Reason] | [What didn't work and why] |
## Current State
- **Working**: [files/features that are functional]
- **Broken/Blocked**: [what's not working and why]
- **Modified files**: [list with brief note on changes]
## Dead Ends (Don't Retry)
- β [Approach that failed] β [why it failed]
## Next Steps (Prioritized)
1. [ ] [Most important next action]
2. [ ] [Second priority]
## Environment & Gotchas
- [Any setup notes, versions, quirks discovered]
## Key Code/Commands Reference
[Only if there are non-obvious commands or snippets the next session needs]
Workflow
- Scan conversation for: decisions, outcomes, failures, file changes, blockers
- Identify the "handoff moment" β what would a fresh agent need to continue?
- Generate structured summary using format above
- Save to file:
session-[topic]-[date].mdin project root or/home/claude/sessions/
Compaction Triggers
Invoke this skill when:
- User says: "compact", "wrap up", "save session", "summarize for next time"
- Context window exceeds ~50% capacity and task is ongoing
- Before major context switches
- End of debugging/implementation session
Quality Criteria
Good compactions are:
- Scannable: Next agent gets orientation in <30 seconds
- Actionable: Clear next steps, not vague summaries
- Defensive: Dead ends documented to prevent re-exploration
- Minimal: No fluff, every line earns its tokens
Anti-Patterns
Avoid:
- Narrative prose ("First we tried X, then Y, then Z...")
- Redundant context (don't repeat what's in code comments)
- Vague summaries ("Made good progress on the feature")
- Missing failure documentation (most valuable part!)
Example Trigger & Response
User: "Let's wrap up, compact this session"
Agent:
1. Reviews conversation for key decisions, outcomes, failures
2. Generates structured markdown per format above
3. Saves to session-[topic]-[date].md
4. Confirms: "Session compacted to session-auth-refactor-2025-01-06.md β ready for next time."
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.