affaan-m/ecc

strategic-compact

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.

ソースを見る

使い方

  1. インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
  2. 必要なツール、認証情報、対応環境を原文で確認します。
  3. 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/affaan-m/ecc --skill strategic-compact

開始前の確認

  • 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
  • スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文

見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。

Strategic Compact Skill

Suggests manual /compact at strategic points in your workflow rather than relying on arbitrary auto-compaction.

When to Activate

  • Running long sessions that approach context limits (200K+ tokens)
  • Working on multi-phase tasks (research → plan → implement → test)
  • Switching between unrelated tasks within the same session
  • After completing a major milestone and starting new work
  • When responses slow down or become less coherent (context pressure)

Why Strategic Compaction?

Auto-compaction triggers at arbitrary points:

  • Often mid-task, losing important context
  • No awareness of logical task boundaries
  • Can interrupt complex multi-step operations

Strategic compaction at logical boundaries:

  • After exploration, before execution — Compact research context, keep implementation plan
  • After completing a milestone — Fresh start for next phase
  • Before major context shifts — Clear exploration context before different task

How It Works

The suggest-compact.js script runs on PreToolUse (Edit/Write) and combines two signals:

  1. Context size (primary) — Reads the latest usage record from the session transcript (transcript_path in the hook payload) and sums input_tokens + cache_read_input_tokens + cache_creation_input_tokens (the true context size of the turn). Suggests /compact at a window-scaled threshold — 160k tokens on a 200k window, 250k on a 1M window (detected from a [1m] model marker, or inferred when observed tokens already exceed 200k) — and re-reminds after every additional 60k tokens of context growth
  2. Tool-call count (secondary) — Counts tool invocations in session; suggests at a configurable threshold (default: 50 calls), then every 25 calls after

Tool count alone is a weak proxy for window pressure: a few large file reads or MCP responses can fill the window in very few calls, while many tiny calls can cross 50 with a near-empty window. The context-size signal fires when it actually matters.

Hook Setup

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:

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" }]
      }
    ]
  }
}

Configuration

Environment variables:

  • COMPACT_THRESHOLD — Tool calls before first suggestion (default: 50)
  • COMPACT_CONTEXT_THRESHOLD — Context tokens before the context-size suggestion (default: 160000 on a 200k window, 250000 on a 1M window; 0 disables the context signal)
  • COMPACT_CONTEXT_INTERVAL — Additional context tokens before the suggestion repeats (default: 60000)
  • COMPACT_STATE_TTL_DAYS — Days before stale per-session state files in the temp dir are swept (default: 14)
  • ECC_CONTEXT_WINDOW_TOKENS — Explicit context-window size, in tokens, overriding auto-detection. Set this for large-window models whose reported id lacks a [1m] marker (e.g. 400k Opus 4.x, or a new 1M-window model family) so the threshold scales to the real window instead of defaulting to 200k and overstating context usage.
  • CLAUDE_CODE_AUTO_COMPACT_WINDOW — Claude Code's native window-size override, in tokens; honored as a fallback when ECC_CONTEXT_WINDOW_TOKENS is unset.
The context window is otherwise auto-detected from a [1m] model marker or inferred when observed tokens already exceed 200k. On a large-window model that carries neither signal, set one of the overrides above so the /compact suggestion fires at the right point.

Compaction Decision Guide

Use this table to decide when to compact:

Phase TransitionCompact?Why
Research → PlanningYesResearch context is bulky; plan is the distilled output
Planning → ImplementationYesPlan is written down (a file, or the task list if you have one); free up context for code
Implementation → TestingMaybeKeep if tests reference recent code; compact if switching focus
Debugging → Next featureYesDebug traces pollute context for unrelated work
Mid-implementationNoLosing variable names, file paths, and partial state is costly
After a failed approachYesClear the dead-end reasoning before trying a new approach

What Survives Compaction

Understanding what persists helps you compact with confidence:

PersistsLost
CLAUDE.md instructionsIntermediate reasoning and analysis
Files on diskFile contents you previously read
Memory files (~/.claude/memory/)Multi-step conversation context
Git state (commits, branches)Tool call history and counts
The task list — only if you have the todo tools (see below)Nuanced user preferences stated verbally
### Don't rely on the task list surviving — it may not exist Claude Code 2.1.233 removed the todo/task tools by default on Opus 4.8, Sonnet 5, Fable 5, Mythos 5 and newer models (TodoWrite, TaskCreate/Get/Update/List). CLAUDE_CODE_ENABLE_TODO_TOOLS=1 brings them back, but that is a per-machine environment setting — it does not travel with this skill, so you cannot assume the reader has it. This matters because "my todo list survives compaction" is a reason people compact instead of writing state down. If the tools are absent there is no list to survive, and the plan is simply gone. Write the plan to a file before compacting — a file persists on every version and every model. Treat the task list as a convenience that may be missing, never as your durable record.

Best Practices

  1. Compact after planning — Once the plan is finalized and written to a file, compact to start fresh
  2. Compact after debugging — Clear error-resolution context before continuing
  3. Don't compact mid-implementation — Preserve context for related changes
  4. Read the suggestion — The hook tells you when, you decide if
  5. Write before compacting — Save important context to files or memory before compacting
  6. Use `/compact` with a summary — Add a custom message: /compact Focus on implementing auth middleware next

Token Optimization Patterns

Trigger-Table Lazy Loading

Instead 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%+:

TriggerSkillLoad When
"test", "tdd", "coverage"tdd-workflowUser mentions testing
"security", "auth", "xss"security-reviewSecurity-related work
"deploy", "ci/cd"deployment-patternsDeployment context

Context Composition Awareness

Monitor what's consuming your context window:

  • CLAUDE.md files — Always loaded, keep lean
  • Loaded skills — Each skill adds 1-5K tokens
  • Conversation history — Grows with each exchange
  • Tool results — File reads, search results add bulk

Duplicate Instruction Detection

Common sources of duplicate context:

  • Same rules in both ~/.claude/rules/ and project .claude/rules/
  • Skills that repeat CLAUDE.md instructions
  • Multiple skills covering overlapping domains

Context Optimization Tools

  • token-optimizer MCP — Automated 95%+ token reduction via content deduplication
  • context-mode — Context virtualization (315KB to 5.4KB demonstrated)

Related

  • The Longform Guide — Token optimization section
  • Memory persistence hooks — For state that survives compaction
  • continuous-learning skill — Extracts patterns before session ends

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