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Strategic compact

Skill asong56/skills/00-foundation/strategic-compact

268 AI coding assistant skills, organized across 12 workflow layers. Sources include Anthropic official, FRM, SKC, LRN, SKA, and other mainstream AI coding frameworks.

Install
npx -y skills add asong56/skills --skill strategic-compact

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What its author says it does

Copied from the file, not written here

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

SKILL.md

6.3 KB, ~1.4k tokens by cl100k_base, as published. Nobody here has run it

Strategic Compact Skill

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

When to use

  • 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

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)

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

Gives 1 of the 12 instructions most roadmap strategy skills give in ~1.4k tokens

Counted across 591 of the 672 authors here whose files we hold, read 2026-08-06

  • read product marketing context before asking questionsin 21 of 591, across 10 files
  • base price on perceived value, not costin 15 of 591, across 4 files
  • compact after finalizing a planhere, and in 14 of 591, across 9 files
  • differentiate tiers using features, limits, or supportin 14 of 591, across 3 files
  • use Van Westendorp to find acceptable price rangein 13 of 591, across 2 files
  • use MaxDiff to identify highly valued featuresin 13 of 591, across 2 files
  • map topics to buyer journey stagesin 12 of 591, across 6 files
  • Extract domain capabilities and classify subdomainsin 11 of 591, across 1 file
  • Define bounded contexts around consistency and ownershipin 11 of 591, across 1 file
  • Establish a ubiquitous language glossary and anti-termsin 11 of 591, across 1 file
  • Capture context boundaries in ADRs before implementationin 11 of 591, across 1 file
  • Open the strategic design template if neededin 11 of 591, across 1 file

Said here and by no other author read

  • clear dead-end reasoning before new approaches
  • clear exploration context before different tasks
  • decide whether to compact after reading suggestion

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

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