Compress lengthy conversations to preserve essential context, reducing token usage for efficient processing. Adjust quality and reasoning effort to balance detail and cost.
Prepare conversation compression while preserving required context.
| Name | Required | Description | Default |
|---|---|---|---|
| quality | No | economy | |
| conversation | Yes | ||
| reasoning_effort | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.4.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'preserving required context' which hints at a key behavior, but doesn't explain what 'prepare' means operationally, whether this mutates anything, what side effects occur, or what the output looks like. The description is too thin to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no wasted words. It front-loads the action and constraint. However, it is under-specified rather than efficiently concise, so it doesn't earn a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema and only one required parameter, but with 0% schema description coverage, no annotations, and a vague description, an agent cannot confidently invoke it. The description doesn't explain the compression behavior, quality levels, or how the output relates to the input. It is not complete enough for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 for the three undocumented parameters. It doesn't explain what 'quality' values mean, what format 'conversation' should be in, or how 'reasoning_effort' affects behavior. The description adds no parameter-level meaning beyond the schema's bare names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description says 'Prepare conversation compression while preserving required context.' It identifies a specific action (prepare) and resource (conversation compression), and adds a constraint (preserving required context). However, it doesn't clearly distinguish this from sibling tools like prepare_task or optimize_prompt, and 'prepare' is somewhat vague about what the tool actually does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives. The description doesn't mention any conditions, prerequisites, or exclusions. With 38 sibling tools, an agent has no way to know when to choose compress_conversation over other preparation or optimization tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.