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config_models_show

Lists all AI models known to the CLI, showing identifiers, token budgets, and providers in YAML format.

Instructions

Return the embedded models.yaml listing every AI model the CLI knows about (identifiers, token budgets, provider). Output is YAML. Mirrors omni-dev config models show.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description must carry the full burden. It describes the output content and format but does not mention potential side effects, authentication needs, or rate limits. For a read-only config dump, it is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description consists of two concise sentences that front-load the key information: what is returned and its format. No extra words, every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema) and lack of annotations, the description covers the essential aspects: source of data, content, and output format. It is complete enough for an agent to use correctly.

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?

The input schema has zero parameters, so no parameter information is needed. The description does not add parameter details, but the baseline for 0 parameters is 4.

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

Purpose5/5

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

The description clearly states the tool returns the embedded models.yaml listing all AI models with identifiers, token budgets, provider, and output format YAML. It also mentions it mirrors a specific CLI command, distinguishing it from any sibling tools.

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

Usage Guidelines4/5

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

The description provides context by noting it mirrors 'omni-dev config models show', giving a clear reference for when to use this tool. No explicit when-not-to-use or alternatives are needed given the tool's simplicity and lack of overlapping siblings.

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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