agent-routing
SolidDecide which model, effort level, and cascade shape each subagent gets, and how to keep improvement loops safe (evaluator-as-selector, stop on regression). Routes on measured cost-per-completed-task rather than per-token price, because a tier's token count varies more by task shape than price varies across tiers. Covers per-model effort semantics, the concision lever, cascade preconditions, context handoff, and watching a subagent fan-out live. Use when spawning subagents via the Agent or Workflow tools, when fanning out more than a handful of agents, or when asked which model or effort a task should get. Grounded in measured calibration (references/calibration-2026-07-15.md), a 2026-08 coding-cost study, and a 2026-09 agentic-repair battery that measured the cascade rungs directly; Managed Agents API specifics are operational, not calibrated.
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Quality Score: 84/100
Skill Content
Details
- Author
- oaustegard
- Repository
- oaustegard/claude-skills
- Created
- 10 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
route
Split the current task into chunks and delegate each to the cheapest capable model via subagents. Use when the user asks to route work cost-efficiently, says "route this", "use cheap models where possible", or hands over a multi-part task and mentions credits, cost, or model choice.
cost-lean-orchestration
Token-efficient model routing for complex engineering sessions. The main model (Opus / Fable, high reasoning) never bulk-reads or explores — it delegates all exploration, bulk file reading, codebase search, log scanning, dependency tracing, and documentation reading to Sonnet subagents that return compact structured findings, and it spends its own tokens only on synthesis, architecture, judgment, and final code. Use this skill in EVERY session that involves reading more than a couple of files, exploring or mapping a codebase, investigating a bug, auditing call sites, reviewing a large diff, digesting logs or docs, or any multi-step engineering task — even if the user never mentions cost, tokens, subagents, or delegation. This is a standing operating discipline, not an on-request feature.
delegate
Token-saving subagent routing. Use when facing token-heavy, read-heavy, conclusion-only work (reading Lark/Feishu in full or writing to it, wide code searches, log/long-document analysis) to decide whether to offload the work to a cheaper-model subagent and which tier to use.