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token-optimization-mcp

token-optimization-mcp

by DCx7C5
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

deduplicate_messages

Remove duplicate messages from a conversation, keeping only the last occurrence, to save tokens and reduce redundancy.

Instructions

Remove duplicate messages from a conversation (keeps last occurrence). Returns deduplicated list + tokens saved.

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": {
      "messages": "<messages>"
    },
    "name": "deduplicate_messages"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNogpt-4o
messagesYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It discloses key behavior (keeps last occurrence, returns deduplicated list + tokens saved) but does not clarify whether the original messages array is modified or if there are any side effects or permission requirements.

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

Conciseness5/5

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

The description is extremely concise (two sentences) and front-loaded with the core action. No irrelevant details or fluff.

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?

For a simple tool with two parameters and an output schema, the description covers the basic purpose and return format, but omits parameter descriptions and usage context. It is adequate but not comprehensive.

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 explain parameters. It only vaguely references 'messages from a conversation' but does not detail the 'model' parameter or the expected format of the messages array, leaving the agent with insufficient guidance.

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 explicitly states the tool removes duplicate messages from a conversation and specifies the deduplication strategy ('keeps last occurrence'), which clearly distinguishes it from sibling tools like compress_prompt 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. For example, there is no mention of typical scenarios or comparisons to compress_prompt or savings_report.

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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