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.
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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:
- Context size (primary) — Reads the latest
usagerecord from the session transcript (transcript_pathin the hook payload) and sumsinput_tokens + cache_read_input_tokens + cache_creation_input_tokens(the true context size of the turn). Suggests/compactat 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
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;0disables 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 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 |
What Survives Compaction
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 |
Best Practices
- Compact after planning — Once plan is finalized in TodoWrite, 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
/compactwith 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-optimizerMCP — Automated 95%+ token reduction via content deduplicationcontext-mode— Context virtualization (315KB to 5.4KB demonstrated)
Related
- The Longform Guide — Token optimization section
- Memory persistence hooks — For state that survives compaction
continuous-learningskill — 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.