fusion_ask

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

With no annotations, the description carries the full burden and does well by disclosing the parallel panel behavior, web search, judge comparison, and single synthesized answer. It also surfaces the cost implications. It does not cover edge cases like failure modes or latency, but for the described functionality it is adequately transparent.

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 three sentences, front-loaded with the core purpose, and every sentence contributes (purpose, use cases, cost trade-off). There is no redundancy or filler, making it highly efficient.

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 absence of an output schema and annotations, the description covers the essential context: it explains what the tool does, when to use it, and its cost. It mentions the return value ('one synthesized answer is returned'). It lacks details on performance or error handling, but these are secondary for a tool of this complexity.

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 coverage is 100%, setting a baseline of 3. The description adds value by explaining the high-level process (panel of models, judge comparison), which clarifies the role of parameters like judge_model and analysis_models beyond their raw schema definitions. This contextual enrichment justifies a small uplift over the baseline.

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 purpose: 'Ask OpenRouter Fusion: a panel of models answers your prompt in parallel...' and explains the process (panel, judge, synthesized answer). It distinguishes itself from a single model call by emphasizing the multi-model synthesis, leaving no ambiguity about what the tool does.

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 provides explicit use cases: 'Use for research, expert critique, or any question where being wrong is costly.' It also implies a trade-off with cost: 'Costs more than a single call (panel + judge completions),' which serves as a when-not-to-use hint. However, it does not explicitly name alternative tools or provide a formal when-not-to-use list, so it falls just short of a 5.

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