claude-opus
Claude Opus — Frontier Reasoning Tier
Concept of the skill
What it is: claude-opus is the routing decision for a model provider's most capable, most expensive reasoning tier — the model you reach for when a task is hard enough that depth of reasoning, not throughput, is the binding constraint.
Mental model: A model roster is a tiered ladder: a deep-reasoning tier (slow, expensive, smartest), a balanced tier, and a fast/cheap tier. Routing is choosing the lowest rung that still clears the task's difficulty bar. The frontier tier is the top rung — correct only when the task genuinely needs its ceiling, because every task that could clear a lower rung but is sent here wastes the premium.
Why it exists: Sending every task to the smartest model is the lazy default and it is wrong twice over — it burns cost/latency on work a cheaper tier does identically, and it starves the budget so the genuinely hard tasks compete with trivia. Explicit frontier-tier routing makes the escalation decision deliberate: a task earns the top tier by clearing a difficulty bar, not by being next in the queue.
What it is NOT: It is not "the model to use when in doubt" — doubt routes down, not up, until the task proves it needs the ceiling. It is not a quality guarantee on its own (a frontier model on a vague prompt still underperforms a cheaper model on a sharp one), and it is not the loop, harness, or prompt the model runs inside — those are separate concerns.
Adjacent concepts: the balanced implementation tier (ordinary feature work, the default lane); the fast/cheap tier (mechanical slot-filling and high-volume work); loop architecture (the harness the model executes within); cost-aware delegation (the policy that routes mechanical work down and away from any model).
One-line analogy: The frontier tier is the senior specialist you book for the genuinely hard case — overkill and overpriced for the routine appointment a generalist handles, indispensable for the one that would defeat the generalist.
Common misconception: That the smartest model is always the safest choice. It is not — it is the safest only when the task needs it; for work a cheaper tier or a script handles deterministically, the frontier tier adds cost and latency with no quality gain, and the misallocation compounds across a workload.