ask_openrouter_council

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

With no annotations, the description carries the full disclosure burden, and it rises to the task. It discloses the billing cost (N billed calls plus synthesis), parallel fan-out, the adjudicator default ladder ('the local `codex` CLI when installed, else OpenRouter-hosted GPT-5.6 Sol, else Fable'), the models omission fallback (configured set or 3 featured catalog models), and the Grok/Kimi reroute to local CLIs. This is substantive behavioral context well beyond what the schema alone provides.

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 core action is front-loaded in the first sentence and subsequent sentences efficiently add cost, default, fallback, and routing context without fluff. However, the synthesizer ladder and `models` omission behavior are repeated nearly verbatim from the schema, so a couple of sententes are slightly redundant. Overall it is dense and well-organized, but not every sentence strictly 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?

For a 6-param tool with no output schema and no annotations, the description covers purpose, cost, defaults, fallbacks, and configuration entry points. It references the fan-out/synthesis contract and `consensus` signal indirectly through `ask_council` rather than defining the return format, and it does not explain failure behavior when OpenRouter is not configured or when no models resolve. These are modest gaps for a tool of this complexity, so a 4 is appropriate.

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 100% with already-rich parameter text, so the baseline is 3. The description mostly restates schema content for `models` and `synthesizer` ('omit it to use the configured set...', 'adjudicator defaults GPT-first...'), adding little parameter-level meaning beyond the schema. The genuinely new details (cross-lab diversity rationale, Grok/Kimi reroute) are behavioral rather than parameter-semantic, so the description does not raise the score above 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 opens with a specific verb and resource: 'Ask SEVERAL OpenRouter models the same question in parallel, then have an adjudicator reconcile their answers into one.' It clearly differentiates this tool from the sibling `ask_council` by naming it ('Same fan-out/synthesis contract and `consensus` signal as `ask_council`') and from single-model `ask_openrouter` by emphasizing cross-lab diversity on a single API key. The purpose is unambiguous and distinct from the large sibling set.

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 provides explicit use-case context and a cost-based gate: 'COST: this is N billed calls plus a synthesis — reserve it for a contentious, hard-to-reverse decision, exactly as with `ask_council`.' It also names the configuration alternative (`configure_openrouter_council`) and explains the fallback behavior when `models` is omitted. However, it does not explicitly state when NOT to use it (e.g., 'prefer `ask_openrouter` for a single quick answer'), so it stops short of a full 5.

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