token-optimization-mcp

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compress_prompt

Reduce token usage by compressing prompts with adjustable strategies. Returns compressed text and savings statistics.

Instructions

Compress a prompt to reduce token usage. strategy: 'trim' (whitespace/blanks), 'summarize_hint' (mark long sections), 'aggressive' (strip comments, examples, filler). Returns compressed text + savings stats.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "prompt": "<prompt>"
    },
    "name": "compress_prompt"
  }
}

Input Schema

Name	Required	Default
`model`	No	gpt-4o
`prompt`	Yes
`strategy`	No	trim
`target_tokens`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Jul 6, 2026

TDQS

B3.3/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries the full burden. It discloses that the tool returns compressed text and savings stats and outlines three strategies. However, it does not clarify side effects, reversibility, or behavior of parameters like model and target_tokens.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the primary purpose. It is concise, but a more structured format could improve readability for multiple strategies and parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters, no schema descriptions, no annotations, and sibling tools, the description covers strategies but lacks details for model and target_tokens. Output schema exists but is not provided; the description mentions return values sufficiently, but parameter explanations are incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the strategy parameter's values but fails to describe model (likely for summarization), prompt (the input), and target_tokens (target token count). This leaves key parameters underspecified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Compress a prompt to reduce token usage' and lists specific strategies (trim, summarize_hint, aggressive), making the purpose clear and distinct from sibling tools like estimate_tokens or cache_lookup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as estimate_tokens or deduplicate_messages. The description implies token reduction but does not specify prerequisites or conditions for choosing compression over other operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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