ypollak2/llm-router

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

No annotations provided, so description carries full disclosure burden. Successfully clarifies execution mode ('non-interactively'), cost model ('uses the user's OpenAI subscription'), and locality ('local Codex desktop agent'). However, misses critical operational context for a code-agent tool: no disclosure of potential file system side effects, sandbox status, error conditions (e.g., Codex not installed), or timeout behavior.

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?

Well-structured and front-loaded with core purpose. Information flows logically from mechanism to cost model to available options. The 'Args:' section introduces slight redundancy with the schema structure, but is justified given the complete lack of schema descriptions (0% coverage).

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?

Appropriately complete for a 2-parameter tool with existing output schema (no return value explanation needed). Covers parameter semantics, purpose, and sibling differentiation adequately. Minor gap regarding side-effect disclosure for a potentially destructive code-agent tool, but sufficient for basic invocation decisions.

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%, requiring full compensation. Description comprehensively documents both parameters ('prompt' as 'task or question', 'model' as 'OpenAI model to use') and crucially provides the enum list of available models (gpt-5.4, o3, etc.) entirely missing from the schema.

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?

Specific verb+resource combination ('Route a task to the local Codex desktop agent') clearly identifies the tool's function. Explicitly distinguishes from siblings by specifying OpenAI/Codex brand, local desktop agent nature, and OpenAI subscription usage versus Claude quota.

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?

Provides explicit when-to-use guidance ('ideal as a fallback when Claude limits are tight, or for tasks that benefit from OpenAI's models'), establishing clear context for selection. Lacks explicit when-not-to-use or named sibling alternatives, though the Claude vs OpenAI distinction effectively differentiates from the broader llm_* toolset.

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