_mcp_generate_inference_config

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

With no annotations, the description carries full burden. It does disclose one behavioral trait: 'no secrets embedded', which is valuable for security awareness. However, it does not mention other aspects like whether the config is written to disk, returned, or if it requires network access. Given the lack of annotation support, a 3 is appropriate—minimal but not completely absent.

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 sentence with no wasted words. It is front-loaded with the core verb. However, it could be slightly more structured (e.g., listing parameters explicitly) without adding much length. Still, it is well within acceptable conciseness, earning a 4.

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 complexity (7 parameters, no schema descriptions, no annotations), the description is too sparse. It does not explain the purpose of engine, project_id, extra_params, or how the output is returned. While an output schema exists, the input side is under-documented for an agent to make informed decisions about parameter overrides. The tool's simplicity doesn't fully excuse the lack of detail.

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. It mentions 'port, api key NAME ref, context, limits', mapping partially to parameters (port, api_key_env_name, context_length, max_concurrent). But it omits engine, project_id, and extra_params. It adds some meaning beyond the schema (e.g., 'api key NAME ref' clarifies that the parameter is an environment variable name, not the key itself), but coverage is incomplete, resulting in a mid-range score.

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 function: 'Produce inference server config' with specific elements (port, api key NAME ref, context, limits). It also adds a safety note about no secrets embedded, which distinguishes it from potentially similar tools that might handle secrets. This is a specific verb+resource with added context, earning a top score.

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 provided on when to use this tool versus alternatives. While many siblings exist (e.g., _mcp_generate_deployment_guide), the description does not indicate any conditions, prerequisites, or exclusions. The agent is left to infer context from the name alone.

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