Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.
Install
The skill file stays in the publisher's repository.
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
npx skills add rohitg00/pro-workflow --skill context-engineering -a cursor -y
Download skills/context-engineering/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does context-engineering live?
The publisher keeps it at https://github.com/rohitg00/pro-workflow.
Which agents can use context-engineering?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.
Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.
name: context-engineering
description: Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.
user-invocable: true
Context Engineering
Four operations control everything about how context flows through an AI coding session. Master them and you control the quality of every response.
The Four Operations
1. Write — Persist Info Outside Context
Move information out of the context window into durable storage so it survives compaction and session boundaries.
Where to write:
Target
When
Example
CLAUDE.md
Permanent project rules
"Always use pnpm, never npm"
NOTES.md / scratchpad
Working state for current task
Architecture decisions, open questions
.claude/memory/
Learnings and patterns
[LEARN] rules from corrections
External files
Data too large for context
Test plans, migration checklists
Pattern — Scratchpad workflow:
1. Start complex task → create NOTES.md with goals and constraints
2. After research → write findings to NOTES.md
3. After compaction → NOTES.md survives, context does not
4. Resume → read NOTES.md to recover full state
2. Select — Retrieve Relevant Info
Pull the right information into context at the right time. Precision matters more than volume.
Methods ranked by precision:
@file references — exact file injection
grep / Glob — targeted pattern search
Subagent exploration — delegated deep search
RAG / embeddings — semantic retrieval for large codebases
A surgical grep result that returns the exact function signature beats dumping an entire module into context. Every irrelevant token dilutes attention.
Pattern — Progressive retrieval:
1. Start with file names (Glob)
2. Narrow to specific functions (Grep)
3. Read only the relevant lines (Read with offset+limit)
4. Never read entire large files when you need one function
3. Compress — Reduce Tokens, Preserve Signal
Shrink context without losing the information that matters.
Compaction strategies:
Strategy
How
When
/compact with focus
/compact focus: auth module changes
Task boundaries
Microcompact
Ask Claude to summarize tool output inline
After large reads/searches
Head+tail
Read first 20 + last 20 lines of large output
Log analysis, test results
Tool result clearing
Subagent results auto-clear after reporting
Heavy exploration
Semantic selection
Summarize findings, discard raw data
Research phases
Compaction triggers:
After planning, before implementation
After completing a feature or milestone
When context exceeds 50% (set CLAUDE_AUTOCOMPACT_PCT_OVERRIDE=50)
Use this to ensure project rules, current task state, or architecture constraints survive every compaction.
4. Isolate — Partition Across Execution Spaces
Don't load everything into one context. Split work across independent execution spaces.
Method
Isolation Level
Use When
Subagents
Forked context
Heavy exploration, test runs, doc generation
Worktrees (claude -w)
Full repo copy
Parallel features, competing approaches
/btw (built-in Claude Code)
Temporary overlay
Quick questions without entering conversation history
Agent teams
Independent sessions
Cross-layer changes, parallel reviews
Fresh session (/resume)
Clean slate
Unrelated work, degraded context
Pattern — Subagent delegation:
Main session: planning, coordination, commits
Subagent 1: explore auth module, report findings
Subagent 2: run test suite, report failures
Subagent 3: generate migration script
Main context stays clean. Subagents handle the volume.
Context Budget Planning
Example baseline (calibrate with /context): a 200K window (Haiku 4.5; Fable 5.1, Opus 5.5, and Sonnet 5 carry 1M) with ~20K overhead (CLAUDE.md, tool definitions, MCP schemas) leaves ~180K usable. Quality still drops as context fills, so keep the same discipline on 1M tiers. Actual budgets vary by model and configuration.
Allocation
Budget
What Goes Here
Static context
20-30K
CLAUDE.md, tool schemas, MCP definitions
Dynamic context
150-180K
Code, conversation, tool results
Put static context first. CLAUDE.md and tool definitions load before conversation. Keeping them stable maximizes prompt cache hits — saves cost and latency.
Phase
Target Usage
Action If Over
Planning
< 20%
Keep plans concise, write to scratchpad
Implementation
< 50%
Compact between files, delegate reads
Testing
< 70%
Delegate test runs to subagents
Review
< 85%
Start fresh session if degraded
When to /clear vs /compact vs Subagent
Situation
Action
Task boundary, want to keep learnings
/compact with focus
Context degraded, Claude repeating itself
/compact, then /resume if still bad
Starting unrelated work
/clear or new session
Heavy read/search operation
Delegate to subagent
Quick side question
/btw (doesn't pollute main context)
Exploring multiple approaches
Worktrees or agent teams
Anti-Patterns
Loading entire files when you need one function
Keeping MCP tool results in context after extracting what you need
Running 15+ MCPs (each adds tool schema overhead to every request)
Vague prompts that force Claude to search broadly ("fix the code")
Never compacting until auto-compact triggers at 95%
Add to CLAUDE.md
## Context Engineering
Write to NOTES.md for working state that must survive compaction.
Select with precision — grep first, read specific lines, never dump whole files.
Compact at 50% or task boundaries. Set CLAUDE_AUTOCOMPACT_PCT_OVERRIDE=50.
Isolate heavy work to subagents. Main session stays for coordination and commits.
How do I install context-engineering?
Download skills/context-engineering/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does context-engineering live?
The publisher keeps it at https://github.com/rohitg00/pro-workflow.
Which agents can use context-engineering?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.