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.
Compresses MCP responses when users request token efficiency or reduced usage. Applies abbreviation, flattening, and selective fields to maximize information value per token while maintaining clarity.
/plugin marketplace add standardbeagle/standardbeagle-tools/plugin install mcp-architect@standardbeagle-toolsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Maximize information value per token in MCP responses through abbreviation, schema optimization, selective field inclusion, and efficient formatting.
Apply when:
Before compression:
{
"searchResults": [
{
"identifier": "a1b2",
"symbolName": "authenticate",
"fileLocation": "/src/models/user.ts",
"lineNumber": 42,
"confidenceScore": 0.95
}
]
}
After compression:
{
"results": [
{
"id": "a1b2",
"name": "authenticate",
"file": "/src/models/user.ts",
"line": 42,
"conf": 0.95
}
]
}
Savings: ~30% fewer tokens
Before:
{
"response": {
"data": {
"results": {
"items": [...]
}
}
}
}
After:
{
"results": [...]
}
Savings: ~40% fewer tokens
Verbose (objects):
[
{"id": "a1", "name": "foo", "type": "fn"},
{"id": "b2", "name": "bar", "type": "fn"},
{"id": "c3", "name": "baz", "type": "fn"}
]
Compact (table):
{
"cols": ["id", "name", "type"],
"rows": [
["a1", "foo", "fn"],
["b2", "bar", "fn"],
["c3", "baz", "fn"]
]
}
Savings: ~35% fewer tokens for 10+ rows
Full response:
{
"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:
{
"id": "a1",
"name": "authenticate",
"type": "function",
"file": "user.ts",
"line": 42
}
Savings: ~70% fewer tokens (use get_details(id) for full version)
Without references:
{
"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:
{
"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
{
"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
}
{
"p": "running", // status
"u": "2h15m", // uptime
"m": "245MB", // memory
"c": 15 // cpu_percent
}
{
"items": ["a", "b", "c", "d", "e"],
"t": 127, // total
"s": 5, // showing
"m": true // more available
}
Allocate token budget by information value:
| Information | Priority | Budget % | Example |
|---|---|---|---|
| Core data | High | 60% | Search results, IDs |
| Metadata | Medium | 25% | Counts, flags |
| Help text | Low | 15% | Next steps, tips |
Example allocation (200 token budget):
Standard abbreviations for consistency:
id → 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:
{
"i": "id",
"n": "name",
"t": "type",
"c": "confidence"
}
Avoid over-compression for:
Example - Don't compress:
{
"error": "Authentication failed", // Keep clear
"code": "AUTH_INVALID_CREDENTIALS",
"message": "The provided credentials are invalid"
}
Extreme compression (hard to read):
{"r":[{"i":"a1","n":"auth","t":"fn","c":0.95}],"m":1,"t":127}
Balanced compression:
{
"results": [
{"id": "a1", "name": "auth", "type": "fn", "conf": 0.95}
],
"has_more": true,
"total": 127
}
Recommendation: Compress field names moderately, keep structure clear.
Compression checklist:
Token savings hierarchy:
Focus on ID references and selective fields first for maximum impact.
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