smart-model-routing
Dynamic model selection based on task complexity scoring. Replaces static model mappings with a weighted signal system that picks Opus, Sonnet, or Haiku-class speed per task. Works with agent-assignment-matrix.md.
Profile →npx skills add vibeeval/vibecosystem --skill smart-model-routing --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Smart Model Routing Dynamic model selection based on task complexity. Never use a sledgehammer where a scalpel will do — and never use a scalpel where you need a sledgehammer. ## Core Philosophy Static model assignments ("always use Sonnet for code") waste money on trivial tasks and produce poor results on complex ones. This skill scores every task across three signal categories and routes it to the appropriate model tier automatically. **Default rule: inherit parent model.** Only override when the score clearly warrants a different tier. Never specify a model without a scoring reason. --- ## Signal Categories Three weighted categories are evaluated. Their scores combine into a single complexity score (0-20 typical range, can exceed). ### Category 1: Lexical Signals (weight: 0.3) Analyze the raw text of the request. #### Architecture Keywords (+3 each) Trigger words that indicate high-stakes design work: - "redesign", "overhaul", "new system", "migrate", "refactor entire", "rewrite" - "architecture", "from scratch", "greenfield", "new service", "platform" Example: "Redesign the authentication system" → +3 #### Risk Keywords (+2 each) Domains where mistakes are expensive or irreve
- Core Philosophy
- Signal Categories
- Category 1: Lexical Signals (weight: 0.3)
- Category 2: Structural Signals (weight: 0.4)
- Category 3: Context Signals (weight: 0.3)
- Tier Thresholds
- Confidence Calculation
- Escalation on Low Confidence
- Hard Rules (Override Score)
- Never Use Haiku For:
- Always Use Opus For:
- Application Rules
- For Agent Spawns
- For Inline Decisions
cd ~/.claude && PYTHONPATH=scripts python3 scripts/core/recall_learnings.py \
What does the smart-model-routing skill do?
Dynamic model selection based on task complexity scoring. Replaces static model mappings with a weighted signal system that picks Opus, Sonnet, or Haiku-class speed per task. Works with agent-assignment-matrix.md.
How do I install it?
Run `npx skills add vibeeval/vibecosystem --skill smart-model-routing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From vibeeval/vibecosystem, a repository with 521 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.