ST

strategic-compact

Suggests strategic context compaction at logical task boundaries to preserve session focus.

Install

mkdir -p .claude/skills/strategic-compact && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/716" && unzip -o skill.zip -d .claude/skills/strategic-compact && rm skill.zip

Installs to .claude/skills/strategic-compact

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
134 charsno explicit “when” trigger
Beginner

Key capabilities

  • Suggest manual context compaction at logical intervals
  • Monitor context window usage based on token count
  • Suggest compaction when switching between unrelated tasks
  • Recommend compaction after completing major milestones
  • Provide a decision guide for when to compact context

How it works

The skill suggests manual context compaction by monitoring context size based on token count and tool-call count, recommending compaction at strategic points like task phase transitions or when context pressure is high.

Inputs & outputs

You give it
Session transcript and tool invocation count
You get back
Suggestion to run `/compact` command

When to use strategic-compact

  • Managing session context limits
  • Switching task focus
  • Clearing context after milestone completion

About this skill

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:

{
  "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 in TodoWrite or a file; 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
TodoWrite task listFile contents you previously read
Memory files (~/.claude/memory/)Multi-step conversation context
Git state (commits, branches)Tool call history and counts
Files on diskNuanced user preferences stated verbally

Best Practices

  1. Compact after planning — Once plan is finalized in TodoWrite, 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

When not to use it

  • Mid-implementation, to avoid losing variable names or partial state
  • When the task requires continuous access to intermediate reasoning

Limitations

  • Does not automatically compact context
  • Tool count alone is a weak proxy for window pressure

How it compares

This skill suggests compaction at logical workflow boundaries, such as after research and before execution, unlike arbitrary auto-compaction which can interrupt complex operations.

Compared to similar skills

strategic-compact side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
strategic-compact (this skill)92moNo flagsBeginner
pptx3936moReviewAdvanced
nano-pdf632moReviewBeginner
video-downloader1017moReviewBeginner

Try saying

Example prompts that trigger this skill in your AI assistant.

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