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.
62
73%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Passed
No findings from the security scan
Fix and improve this skill with Tessl
tessl review fix ./.agents/skills/strategic-compact/SKILL.mdSuggests manual /compact at strategic points in your workflow rather than relying on arbitrary auto-compaction.
Auto-compaction triggers at arbitrary points:
Strategic compaction at logical boundaries:
The suggest-compact.js script runs on PreToolUse (Edit/Write) and combines two signals:
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 growthAdd to your ~/.claude/settings.json:
{
"hooks": {
"PreToolUse": [
{
"matcher": "Edit",
"hooks": [{ "type": "command", "command": "node ~/.claude/skills/strategic-compact/suggest-compact.js" }]
},
{
"matcher": "Write",
"hooks": [{ "type": "command", "command": "node ~/.claude/skills/strategic-compact/suggest-compact.js" }]
}
]
}
}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)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/compactsuggestion fires at the right point.
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 |
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 |
/compact with a summary — Add a custom message: /compact Focus on implementing auth middleware nextcontinuous-learning skill — Extracts patterns before session endsd8409a4
Canonical home
since Feb 12, 2026
Also appears in
last in sync Mar 28, 2026
last in sync Mar 6, 2026
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.