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coyvalyss1/model-matchmaker/context-monitor

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PublishedOctober 27, 2026 at 04:54 AM
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version: "1.0.1" name: context-monitor description: Monitor conversation context and prevent MAX mode by warning at token thresholds and generating handoff summaries. Use when context approaches 100K/150K/180K tokens or when working with high-cost files.


MAX Mode Prevention & Context Monitoring

The Problem

Cursor's MAX mode (Claude Opus 3.5, 200K token context) is expensive and should be reserved for truly complex tasks. Context can balloon quickly when:

  • Opening large files (e.g., a 9,378-line React component)
  • Loading chat transcripts or logs (1-10MB)
  • Accumulating tool calls and responses across long sessions
  • Reading multiple files speculatively

Once context exceeds 200K tokens, the conversation is forced into a new chat with a handoff summary. This wastes user time and disrupts flow.

The Solution

Monitor context throughout the conversation (not just at start). Warn at thresholds and proactively recommend starting a new chat with a clean handoff.

Token Thresholds

🟡 Yellow Alert (100K tokens)

Action: Note the context size internally. No user warning yet.

🟠 Orange Alert (150K tokens)

Action: Warn the user and suggest wrapping up current work or starting a new chat if the task is open-ended.

Warning format:

⚠️ Context approaching 150K tokens. Consider starting a new chat after this task to avoid MAX mode. I can generate a handoff summary.

🔴 Red Alert (180K tokens)

Action: Strongly recommend starting a new chat. Offer to generate a handoff summary immediately.

Warning format:

🚨 Context at 180K tokens (MAX mode limit: 200K). Recommend starting a new chat now. I can generate a handoff summary with:
- Task description
- Progress so far
- Next steps
- @file references

Automatic Triggers

Issue a warning automatically when:

  1. Large file opened (>3,000 lines):
  • Example: DashboardPage.jsx (9,378 lines) = ~70K tokens
  • Example: useChatManager.jsx (4,178 lines) = ~30K tokens
  • Any file >5,000 lines = likely >40K tokens
  1. Multiple large files in context (>5 files over 1,000 lines each)
  1. Long conversation (>50 tool calls in current chat)
  1. Transcript search (reading agent-transcripts/*.txt files)
  1. Plan file creation (plans are meta-work that inflate context)

High-Cost Files (Known)

Track your project's largest files and add them to your monitoring list. Common examples:

  • Main dashboard/app components (5,000-10,000 lines)
  • Complex state management hooks (3,000-5,000 lines)
  • Generated files (API clients, schema definitions)
  • Any .log file
  • Any agent transcript (.txt files in agent-transcripts/)

When opening these files, immediately note context cost and warn if already over 100K.

To find your largest files:

bash
find . -name "*.jsx" -o -name "*.tsx" -o -name "*.js" -o -name "*.ts" | \
xargs wc -l | sort -rn | head -20

Handoff Summary Format

When recommending a new chat, generate a concise handoff summary using this template:

markdown
## Handoff Summary for New Chat
**Task**: [One-line description]
**Progress**:
-[Bullet point 1]
-[Bullet point 2]
-[Bullet point 3]
**Next Steps**:
1.[Action item 1]
2.[Action item 2]
3.[Action item 3]
**Key Files**:
-@path/to/file1.jsx — [what was changed/what needs work]
-@path/to/file2.js — [what was changed/what needs work]
**Context**: [1-2 sentences of critical context that must be preserved]

Handoff example:

markdown
## Handoff Summary for New Chat
**Task**: Fix chat component falling back to short responses when user profile is empty
**Progress**:
-Identified root cause: validation guard blocking all saves when user data incomplete
-Removed guard from useChatManager.jsx (lines 2847-2863)
-Added fallback examples to API helper function
**Next Steps**:
1.Test save flow with empty profile
2.Verify data structure generation on first save
3.Deploy to production if test passes
**Key Files**:
-@src/hooks/useChatManager.jsx — Removed validation guard
-@server/helpers/apiHelper.js — Added fallback examples
**Context**: The short-response fallback was a symptom, not the root cause. Real issue was validation logic preventing data generation.

Implementation Guide

For Cursor AI

At the start of each response:

  1. Check conversation length (tool call count, file read count)
  2. Check if large files are in context (match against known high-cost files list)
  3. Estimate current token count (rough heuristic: 50 tool calls = ~100K tokens; one 9K line file = ~70K tokens)
  4. Issue warning if threshold crossed

Mid-Conversation Monitoring

After opening a large file:

📊 Context note: DashboardPage.jsx added (~70K tokens). Current context estimate: ~120K tokens.

After 30+ tool calls:

⚠️ Context approaching 150K tokens (30+ tool calls). Consider wrapping up or starting fresh chat.

Handoff Trigger Phrases

When the user says:

  • "This is taking forever"
  • "Start a new chat"
  • "Can we move to a new conversation?"
  • "Feels like we're dragging"
  • "MAX mode is too expensive"

Immediately generate a handoff summary without asking.

Cost Comparison

Typical scenario without monitoring:

  • Start chat: 20K tokens
  • Open DashboardPage.jsx: +70K = 90K
  • Open useChatManager.jsx: +30K = 120K
  • 20 tool calls: +40K = 160K
  • Read logs/transcripts: +30K = 190K
  • Triggers MAX mode (expensive, could have been avoided)

With monitoring:

  • Warning at 150K → user starts new chat
  • New chat: 20K tokens
  • Continue work efficiently
  • Savings: 170K tokens (stays under 200K limit)

When NOT to Warn

Don't warn if:

  • The task is nearly complete (1-2 steps remaining)
  • The user explicitly said "use MAX mode" or "I don't care about cost"
  • The conversation is already at the final deployment/verification stage

Testing the Skill

To verify this skill is working:

  1. Open a large file (>5,000 lines) → Should see context note
  2. Make 30+ tool calls → Should see 150K warning
  3. Request a new chat → Should get formatted handoff summary
  4. Open multiple large files → Should see cumulative context estimate

Integration with .cursorrules

This skill should be referenced in .cursorrules after the "Prior Session Context" section (around line 106):

markdown
## MAX Mode Prevention & Context Monitoring
Monitor conversation context to avoid triggering MAX mode (200K token limit). See `.cursor/skills/context-monitor/SKILL.md` for full logic.
**Quick reference:**
-🟡 100K tokens: Note internally
-🟠 150K tokens: Warn user, suggest wrapping up
-🔴 180K tokens: Recommend new chat with handoff summary
**High-cost files (auto-warn when opened):**
-Any file >5,000 lines (typically ~40-70K tokens)
-Any file >3,000 lines if other large files already in context
-Any agent transcript or log file
**When recommending new chat**, generate handoff summary with: task description, progress, next steps, @file references, critical context.

Why This Matters

  • Cost control: MAX mode is expensive. Staying under 200K tokens saves money.
  • Conversation efficiency: Handoff summaries preserve context without bloating the next chat.
  • User experience: Proactive warnings let users decide when to break vs. AI forcing it.
  • Strategic file loading: Knowing the cost of opening a file helps with decision-making.

This skill should be applied automatically throughout every conversation, not just when explicitly invoked.

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