context_use

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description discloses a significant behavioral quirk: the long-lived docker-py client is unaffected by this tool. It also specifies the return format (dict with returncode, stdout, stderr, truncated), giving the agent a clear picture of the tool's side effects and output.

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 and front-loaded with the core purpose, followed by a crucial caveat and then related tool pointers. Every sentence adds value, and the args/returns section is compact and clear. No unnecessary wording.

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?

For a single-parameter tool with no output schema, this description is remarkably complete. It explains the tool's effect, its limitation regarding SDK tools, how to work around that limitation, and what the return value looks like. The complexity is low, and the description fully covers it.

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?

Although the schema only specifies 'name' as a required string with no description, the tool description adds critical meaning: it must be an 'existing context name' used to 'set as default'. This adequately compensates for the 0% schema description coverage, though it could have been even more explicit about error cases.

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 states the tool's purpose with a specific verb ('Set the active Docker context for the CLI'), identifies the resource ('Docker context'), and clarifies scope ('on the host running this MCP server'). It also distinguishes itself from related sibling tools like context_create and context_list.

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?

The description gives explicit usage context: it sets the active context for CLI-based tools, and it explicitly warns that SDK-backed tools are not retargeted, recommending a server restart instead. It also names sibling tools for creating and listing contexts, providing clear alternatives.

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