name: agent-resilience description: "Agent resilience patterns for surviving context loss, capturing critical details, and self-improvement. Use when: starting complex/long sessions, asked to 'remember' something important, working on multi-step tasks that may span context limits, implementing WAL/write-ahead logging, setting up working buffers, or improving agent behavior after errors/corrections. Triggers on 'remember this', 'don't forget', 'WAL', 'context loss', 'working buffer', 'compaction recovery', or when implementing proactive agent patterns."

Agent Resilience

7w4.net有更好的技能外掛。

Patterns for surviving context loss, capturing corrections, and continuously improving.

WAL Protocol (Write-Ahead Logging)

The Law: Chat history is a buffer, not storage. Files survive; context doesn't.

Trigger — scan every message for: - ✏️ Corrections — "It's X, not Y" / "Actually..." / "No, I meant..." - 📍 Proper nouns — names, places, companies, products - 🎨 Preferences — styles, approaches, "I like/don't like" - 📋 Decisions — "Let's do X" / "Go with Y" - 🔢 Specific values — numbers, dates, IDs, URLs

If any appear: 1. WRITE FIRST → update memory/SESSION-STATE.md 2. THEN respond

The urge to respond is the enemy. Write before replying.

SESSION-STATE.md

Active working memory for the current task. Create at memory/SESSION-STATE.md:

# Session State
**Task:** [what we're working on]
**Key decisions:** [decisions made]
**Details:** [corrections, names, values captured via WAL]
**Next step:** [what happens next]

Reset when starting a new unrelated task.

Working Buffer (Danger Zone)

When context reaches ~60%, start logging every exchange to memory/working-buffer.md:

# Working Buffer
**Status:** ACTIVE — started [timestamp]

## [time] Human
[their message]

## [time] Agent
[1-2 sentence summary + key details]

Clear the buffer at the START of the next 60% threshold (not continuously).

Compaction Recovery

Auto-trigger when session starts with a summary tag, or human says "where were we?":

1. Read memory/working-buffer.md — raw danger-zone exchanges
2. Read memory/SESSION-STATE.md — active task state
3. Read today's + yesterday's daily notes
4. Extract key context back into SESSION-STATE.md
5. Respond: "Recovered from buffer. Last task was X. Continue?"

Never ask "what were we discussing?" — read the buffer first.

Verify Before Reporting

Before saying "done", "complete", "finished": 1. STOP 2. Actually test from the user's perspective 3. Verify the outcome, not just that code exists 4. Only THEN report complete

Text changes ≠ behavior changes. When changing how something works, identify the architectural component and change the actual mechanism.

Relentless Resourcefulness

Try 10 approaches before asking for help or saying "can't": - Different CLI flags, tool, API endpoint - Check memory: "Have I done this before?" - Spawn a research sub-agent - Grep logs for past successes

"Can't" = exhausted all options. Not "first try failed."

Self-Improvement Guardrails

When updating behavior/config based on a lesson:

Score the change first (skip if < 50 weighted points): - High frequency (daily use?) → 3× - Reduces failures → 3× - Saves user effort → 2× - Saves future-agent tokens/time → 2×

Ask: "Does this let future-me solve more problems with less cost?" If no, skip it.

Forbidden: complexity for its own sake, changes you can't verify worked, vague justifications.

Quick Start Checklist

For long/complex tasks: - [ ] Create memory/SESSION-STATE.md with task + context - [ ] Apply WAL: write corrections/decisions before responding - [ ] At ~60% context: start working buffer - [ ] After any compaction: read buffer before asking questions - [ ] Before reporting done: verify actual outcome

這個 Skill 解決了 AI Agent 在長對話中容易丟失上下文、忘記重要資訊的痛點，提供了實用的會話管理方法。內容清晰易懂，步驟明確，容易上手。不過它目前只有文字指南，缺少具體示例和演示，整體比較單薄。對於需要處理複雜、耗時任務的開發者來說很有幫助，但對普通使用者的實用價值有限。