{
    "app": {
        "name": "strategic-compact",
        "description": "Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction. Use when a session is approaching a context limit and a task phase is a natural place to compact.",
        "mode": "advanced-chat",
        "model_config": {
            "provider": "deepseek",
            "model": "deepseek-chat",
            "parameters": {
                "temperature": 0.7,
                "max_tokens": 4096
            }
        }
    },
    "instructions": "name strategic-compact description Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction. Use when a session is approaching a context limit and a task phase is a natural place to compact. metadata {\"origin\":\"ECC\"} 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: 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 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 : { \"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 Transition Compact? Why Research → Planning Yes Research context is bulky; plan is the distilled output Planning → Implementation Yes Plan is written down (a file, or the task list if you have one); 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 What Survives Compaction Understanding what persists helps you compact with confidence: Persists Lost CLAUDE.md instructions Intermediate reasoning and analysis Files on disk File 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 Compact after planning — Once the plan is finalized and written to a file , compact to start fresh Compact after debugging — Clear error-resolution context before continuing Don't compact mid-implementation — Preserve context for related changes Read the suggestion — The hook tells you when , you decide if Write before compacting — Save important context to files or memory before compacting 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%+: 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 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",
    "variables": [],
    "opening_statement": "你好，我是 strategic-compact，Suggests manual context compaction at logical inte...",
    "suggested_questions": [],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=affaan-m-ecc-skills-strategic-compact-skill-md"
}