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compress_context

Compress buffered messages into summaries to free up space and archive old conversation history for QQ chats.

Instructions

Compress all buffered messages for a target into a summary.

This replaces raw messages with a compressed summary, freeing up the buffer. Use this after reading context when you want to archive old messages.

Args: target: Group ID or friend QQ ID. target_type: "group" (default) or "private".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes
target_typeNogroup
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It states the tool 'replaces raw messages with a compressed summary, freeing up the buffer,' which implies a destructive mutation (replacement) and buffer clearing. However, it lacks details on permissions, rate limits, or what happens if compression fails, making it insufficient for a mutation tool with zero annotation coverage.

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 front-loaded with the core purpose, followed by usage guidance and parameter details in a structured 'Args:' section. It's efficient with minimal fluff, though the parameter explanations could be slightly more integrated into the main text.

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 no annotations, no output schema, and a mutation tool with 2 parameters, the description is moderately complete. It covers purpose, basic usage, and parameter meanings but lacks behavioral details like error handling or output format, leaving gaps for an agent to invoke it safely.

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

Parameters4/5

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 'target' as 'Group ID or friend QQ ID' and 'target_type' as '"group" (default) or "private",' adding meaningful context beyond the schema's basic types. This covers both parameters adequately, though it doesn't detail format constraints (e.g., ID structure).

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

Purpose4/5

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

The description clearly states the tool compresses buffered messages into a summary for a target, specifying the action (compress) and resource (buffered messages). It distinguishes from siblings like 'get_recent_context' (reads) or 'send_message' (sends), but doesn't explicitly contrast with them.

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

Usage Guidelines3/5

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

It provides some context: 'Use this after reading context when you want to archive old messages,' implying timing and purpose. However, it doesn't specify when NOT to use it or mention alternatives like 'batch_get_recent_context' for reading without compression, leaving usage guidance incomplete.

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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