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model_route

Look up which model tier or backend to assign to a task class, ensuring correct routing when launching a subagent or autonomous agent.

Instructions

Look up which model tier/backend to use for a task class, per model-routing.json (Allternit's A:// tier policy). Only meaningful when explicitly spawning a subagent or an autonomous agent — an already-running interactive session stays on its own model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_classNoOne of: classification, draft_generation, client_coding_work, quote_routine, architecture_or_novel_judgment, quote_tier_c_scoping, creative_or_long_form, guardrail_check. Omit to list all task classes.
Behavior4/5

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

No annotations are provided, but the description indicates a read-only lookup operation. It does not mention side effects or edge cases, but for a simple lookup, it is sufficiently transparent.

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?

Two sentences, no wasted words. Purpose is front-loaded. Each 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 no output schema, the description does not specify return values. However, for a simple lookup, the agent can infer a model tier string. It is mostly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds 'per model-routing.json (Allternit's A:// tier policy)' but does not significantly enhance the parameter meaning beyond the schema's own description.

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 verb 'look up' and the resource 'model tier/backend for a task class' with reference to a specific policy file. It is distinct from sibling tools which are unrelated (Stripe, Cloudflare, brain).

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

Usage Guidelines5/5

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

The description explicitly states when the tool is meaningful (spawning subagents/autonomous agents) and when it is not (interactive sessions). This provides clear usage context.

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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