---

name: Context Compression description: This skill should be used when the user asks about "token efficiency", "compress responses", "reduce token usage", "minimize context", "compact format", "token optimization", or discusses reducing token consumption in MCP responses while maintaining value. version: 0.1.0

Context Compression

Purpose

Maximize information value per token in MCP responses through abbreviation, schema optimization, selective field inclusion, and efficient formatting.

When to Use

Apply when:

• Token budgets are constrained
• Responses are repetitive or verbose
• Large datasets need representation
• Multiple tools share similar data structures
• Response size directly impacts performance

Compression Techniques

1. Abbreviate Field Names

Before compression:

Copy{
  "searchResults": [
    {
      "identifier": "a1b2",
      "symbolName": "authenticate",
      "fileLocation": "/src/models/user.ts",
      "lineNumber": 42,
      "confidenceScore": 0.95
    }
  ]
}

After compression:

Copy{
  "results": [
    {
      "id": "a1b2",
      "name": "authenticate",
      "file": "/src/models/user.ts",
      "line": 42,
      "conf": 0.95
    }
  ]
}

Savings: ~30% fewer tokens

2. Flatten Nested Structures

Before:

Copy{
  "response": {
    "data": {
      "results": {
        "items": [...]
      }
    }
  }
}

After:

Copy{
  "results": [...]
}

Savings: ~40% fewer tokens

3. Use Arrays for Uniform Data

Verbose (objects):

Copy[
  {"id": "a1", "name": "foo", "type": "fn"},
  {"id": "b2", "name": "bar", "type": "fn"},
  {"id": "c3", "name": "baz", "type": "fn"}
]

Compact (table):

Copy{
  "cols": ["id", "name", "type"],
  "rows": [
    ["a1", "foo", "fn"],
    ["b2", "bar", "fn"],
    ["c3", "baz", "fn"]
  ]
}

Savings: ~35% fewer tokens for 10+ rows

4. Selective Field Inclusion

Full response:

Copy{
  "id": "a1",
  "name": "authenticate",
  "type": "function",
  "file": "user.ts",
  "line": 42,
  "column": 5,
  "endLine": 48,
  "endColumn": 3,
  "signature": "...",
  "docs": "...",
  "created": "2024-01-15",
  "modified": "2024-02-10",
  "author": "...",
  "complexity": 7
}

Minimal response:

Copy{
  "id": "a1",
  "name": "authenticate",
  "type": "function",
  "file": "user.ts",
  "line": 42
}

Savings: ~70% fewer tokens (use get_details(id) for full version)

5. Reference-Based Compression

Without references:

Copy{
  "results": [
    {
      "name": "User.authenticate",
      "file": "/very/long/path/to/src/models/user.ts",
      "package": "com.example.userservice"
    },
    {
      "name": "User.validate",
      "file": "/very/long/path/to/src/models/user.ts",
      "package": "com.example.userservice"
    }
  ]
}

With references:

Copy{
  "refs": {
    "f1": "/very/long/path/to/src/models/user.ts",
    "p1": "com.example.userservice"
  },
  "results": [
    {"name": "User.authenticate", "file": "f1", "pkg": "p1"},
    {"name": "User.validate", "file": "f1", "pkg": "p1"}
  ]
}

Savings: ~50% for repeated values

Compression Patterns by Use Case

Search Results

Copy{
  "r": [  // results
    {"i": "a1", "n": "authenticate", "c": 0.95},  // id, name, confidence
    {"i": "b2", "n": "validate", "c": 0.70}
  ],
  "m": true,  // has_more
  "t": 127    // total
}

Status Checks

Copy{
  "p": "running",  // status
  "u": "2h15m",     // uptime
  "m": "245MB",     // memory
  "c": 15           // cpu_percent
}

Lists with Metadata

Copy{
  "items": ["a", "b", "c", "d", "e"],
  "t": 127,   // total
  "s": 5,     // showing
  "m": true   // more available
}

Token Budget Allocation

Allocate token budget by information value:

Example allocation (200 token budget):

• Results: 120 tokens (60%)
• Metadata: 50 tokens (25%)
• Guidance: 30 tokens (15%)

Abbreviation Dictionary

Standard abbreviations for consistency:

Copyid       → i
name     → n
type     → t
file     → f
line     → l
confidence → c
results  → r
total    → t
has_more → m
description → desc
reference → ref
function → fn
class    → cls
interface → ifc

Use in schemas:

Copy{
  "i": "id",
  "n": "name",
  "t": "type",
  "c": "confidence"
}

When NOT to Compress

Avoid over-compression for:

• Small responses (<100 tokens) - overhead not worth it
• Critical error messages - clarity over brevity
• Security-related fields - explicit is safer
• User-facing documentation - readability matters

Example - Don't compress:

Copy{
  "error": "Authentication failed",  // Keep clear
  "code": "AUTH_INVALID_CREDENTIALS",
  "message": "The provided credentials are invalid"
}

Compression + Readability Balance

Extreme compression (hard to read):

Copy{"r":[{"i":"a1","n":"auth","t":"fn","c":0.95}],"m":1,"t":127}

Balanced compression:

Copy{
  "results": [
    {"id": "a1", "name": "auth", "type": "fn", "conf": 0.95}
  ],
  "has_more": true,
  "total": 127
}

Recommendation: Compress field names moderately, keep structure clear.

Quick Reference

Compression checklist:

• Abbreviate verbose field names
• Flatten unnecessary nesting
• Use reference system for repeated values
• Select only needed fields by default
• Provide full version via get_details(id)
• Balance compression with readability
• Don't compress critical errors/security
• Document abbreviations in schema

Token savings hierarchy:

1. ID references - 70-90% savings (biggest win)
2. Selective fields - 50-70% savings
3. Flattening - 30-50% savings
4. Abbreviation - 20-35% savings
5. Table format - 25-40% savings for lists

Focus on ID references and selective fields first for maximum impact.