llm_reroute

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

With no annotations, the description takes full responsibility. It discloses logging to the database, confidence reduction for future routing, and auto-detection of original_tool. It does not cover auth or rate limits, but the core behavioral traits are clear.

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 with a purpose paragraph followed by arg list. It is efficient and front-loaded. Minor wordiness could be trimmed, but overall it earns its place.

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 presence of an output schema, the description does not need to detail return values. It covers the tool's purpose, usage, and parameter semantics adequately for a corrective routing tool.

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%, but the description compensates by explaining each parameter in bullet points: to_tool (which tool to use), reason (optional), original_tool (auto-detected), original_model (logging). This adds necessary meaning beyond the schema's raw names.

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 ('Override') and resource ('last routing decision'), clearly stating the tool's corrective role. It differentiates from siblings by mentioning tools like llm_route, llm_query, llm_code, establishing when rerouting is needed.

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 explicitly tells when to use the tool (when a routing decision was wrong) and what it achieves (logs, lowers confidence). It lacks explicit 'when not to use' guidance, but the positive use case is well-defined.

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