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strategic-compact
Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
基于本能的学习系统,通过钩子观察会话,创建带置信度评分的原子本能,并将其进化为技能/命令/代理。v2.1版本增加了项目范围的本能,以防止跨项目污染。
任意の自動コンパクションではなく、タスクフェーズを通じてコンテキストを保持するための論理的な間隔での手動コンパクションを提案します。
임의의 자동 컴팩션 대신 논리적 간격에서 수동 컨텍스트 압축을 제안하여 작업 단계를 통해 컨텍스트를 보존합니다.
建议在逻辑间隔处手动压缩上下文,以在任务阶段中保留上下文,而非任意的自动压缩。
Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
| name | strategic-compact |
| description | Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction. |
| origin | ECC |
Suggests manual /compact at strategic points in your workflow rather than relying on arbitrary auto-compaction.
Auto-compaction triggers at arbitrary points:
Strategic compaction at logical boundaries:
The suggest-compact.js script runs on PreToolUse (Edit/Write) and:
Installed as a plugin? No setup is needed. The plugin's hooks/hooks.json already registers suggest-compact.js (hook id pre:edit-write:suggest-compact, active in the standard and strict hook profiles). Do not copy the block below into ~/.claude/settings.json — ~/.claude/scripts/ does not exist on plugin installs, and duplicating a plugin hook causes double execution.
If installed manually (./install.sh), add to your ~/.claude/settings.json:
{
"hooks": {
"PreToolUse": [
{
"matcher": "Edit",
"hooks": [{ "type": "command", "command": "node ~/.claude/scripts/hooks/suggest-compact.js" }]
},
{
"matcher": "Write",
"hooks": [{ "type": "command", "command": "node ~/.claude/scripts/hooks/suggest-compact.js" }]
}
]
}
}
Environment variables:
COMPACT_THRESHOLD — Tool calls before first suggestion (default: 50)Use this table to decide when to compact:
| Phase Transition | Compact? | Why |
|---|---|---|
| Research → Planning | Yes | Research context is bulky; plan is the distilled output |
| Planning → Implementation | Yes | Plan is in TodoWrite or a file; free up context for code |
| Implementation → Testing | Maybe | Keep if tests reference recent code; compact if switching focus |
| Debugging → Next feature | Yes | Debug traces pollute context for unrelated work |
| Mid-implementation | No | Losing variable names, file paths, and partial state is costly |
| After a failed approach | Yes | Clear the dead-end reasoning before trying a new approach |
Understanding what persists helps you compact with confidence:
| Persists | Lost |
|---|---|
| CLAUDE.md instructions | Intermediate reasoning and analysis |
| TodoWrite task list | File contents you previously read |
Memory files (~/.claude/memory/) | Multi-step conversation context |
| Git state (commits, branches) | Tool call history and counts |
| Files on disk | Nuanced user preferences stated verbally |
/compact with a summary — Add a custom message: /compact Focus on implementing auth middleware nextInstead of loading full skill content at session start, use a trigger table that maps keywords to skill paths. Skills load only when triggered, reducing baseline context by 50%+:
| Trigger | Skill | Load When |
|---|---|---|
| "test", "tdd", "coverage" | tdd-workflow | User mentions testing |
| "security", "auth", "xss" | security-review | Security-related work |
| "deploy", "ci/cd" | deployment-patterns | Deployment context |
Monitor what's consuming your context window:
Common sources of duplicate context:
~/.claude/rules/ and project .claude/rules/token-optimizer MCP — Automated 95%+ token reduction via content deduplicationcontext-mode — Context virtualization (315KB to 5.4KB demonstrated)continuous-learning skill — Extracts patterns before session ends