compress_context

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

The description adds significant details beyond annotations: raw messages are replaced and unrecoverable, compression uses client LLM via MCP sampling with fallback. It fully aligns with destructiveHint=true and provides useful behavioral context.

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 well-structured with a summary line followed by bullet points. It is concise but could be slightly more compact. No unnecessary content.

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?

Given the tool's low complexity and no output schema, the description covers the essential aspects: usage, behavior, fallback, and side effects. It is sufficiently complete for an agent to understand what the tool does and its consequences.

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?

With 0% schema description coverage, the description should explain the parameters but does not. 'target' and 'target_type' are not described, leaving the agent to infer their meaning from the tool's purpose. This is a clear gap.

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 clearly identifies the tool's purpose: compressing buffered messages into a summary to free space. It uses a specific verb-resource pair and distinguishes from related tools like get_recent_context.

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?

Explicitly states when to use ('after get_recent_context when you want to archive old conversations') and notes the destructive nature. However, it could more directly state when not to use it (e.g., when raw messages are needed).

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