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.zipInstalls 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.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
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:
- 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
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;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)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 whenECC_CONTEXT_WINDOW_TOKENSis 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.
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
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.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| strategic-compact (this skill) | 9 | 2mo | No flags | Beginner |
| pptx | 393 | 6mo | Review | Advanced |
| nano-pdf | 63 | 2mo | Review | Beginner |
| video-downloader | 101 | 7mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by affaan-m
View all by affaan-m →You might also like
pptx
anthropics
Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks
nano-pdf
openclaw
Edit PDFs with natural-language instructions using the nano-pdf CLI.
video-downloader
ComposioHQ
Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.
youtube-transcript
michalparkola
Download YouTube video transcripts when user provides a YouTube URL or asks to download/get/fetch a transcript from YouTube. Also use when user wants to transcribe or get captions/subtitles from a YouTube video.
using-superpowers
obra
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
browser-automation
browserbase
Automate web browser interactions using natural language via CLI commands. Use when the user asks to browse websites, navigate web pages, extract data from websites, take screenshots, fill forms, click buttons, or interact with web applications. Triggers include "browse", "navigate to", "go to website", "extract data from webpage", "screenshot", "web scraping", "fill out form", "click on", "search for on the web". When taking actions be as specific as possible.