config_models_show

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

No annotations were provided, but the description fully discloses behavior: 'Takes no arguments. Read-only. Output is YAML.' It also clarifies that this tool returns only the embedded catalog, while the plain `show` merges overrides, providing important edge-case 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 compact and front-loaded, delivering all key information in three sentences. It covers purpose, usage, output format, read-only nature, and the differentiation from the override-merging variant without unnecessary detail.

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 simple read-only tool with no parameters and no output schema, the description is complete: it specifies what is returned, the format (YAML), the exact data fields, and how it relates to other tools. It also preempts confusion about overrides by mentioning the embedded-only distinction.

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?

The tool has 0 parameters and the input schema (empty object) already confirms this. The description redundantly states 'Takes no arguments,' which is harmless. Per the zero-parameter rule, a baseline of 4 is appropriate.

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 uses a specific verb ('Return') and identifies the exact resource ('embedded `models.yaml`') and its contents. It clearly distinguishes this tool from siblings by noting it discovers valid `model` values for `ai_chat` and git tools, and further differentiates it from the plain `show` command.

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?

It explicitly states 'Use this to discover the valid `model` values accepted by `ai_chat` and the git tools,' giving a clear purpose. It also contrasts with the non-embedded variant, which merges user/project overrides, providing when-to-use/not-use guidance.

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