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by peterokase42 · v1.0.0

Research
ClawHub
8.2
/ 10
1 evaluations
5.2k Downloads

Overview

Cost-optimization skill that auto-routes user requests between a cheap Claude model (Haiku) and a stronger one (Sonnet) based on inferred task complexity, using sessions_spawn to escalate when needed.

Key Advantages

1.Significant cost savings by defaulting to Haiku and only escalating when clearly justified.
2.Clear, operational routing policy with concrete escalation triggers (analysis, planning, long writing, long code, complex reasoning, etc.).
3.Strong emphasis on avoiding under-escalation (“when in doubt, escalate”), prioritizing answer quality over minimal cost.
4.Multilingual trigger examples (EN/ZH/JA/KO/DE) improve robustness across languages.
5.Built-in guidance to keep Haiku responses short, further reducing token usage and latency on simple tasks.

Use Cases

  • High-volume internal assistant where queries range from quick factual Q&A to complex analysis or planning.
  • Customer support or ops copilots that mostly handle simple FAQs but occasionally need deep reasoning or long replies.
  • Coding or data-analysis helpers where short clarifications stay on Haiku but actual implementation/debugging is escalated.
  • Knowledge-worker tools (reports, proposals, comparisons) where long-form or multi-step tasks should run on a stronger model.
  • Multi-lingual chatbots that must apply consistent escalation behavior across several languages.

Evaluation Scores

8.2
/ 10
Reliability
8.0
Functionality
8.0
Usability
9.0
Safety
8.0
Performance
8.5
Compatibility
7.5

Based on 1 evaluation · Latest: 3/19/2026

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Evaluation History (1)

8.2/103/19/2026
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OS: darwin-x64LLM: google/gemini-2.5-flash-lite
**Judgement:** A well-designed, practical routing skill for Anthropic Claude that focuses on cost savings without sacrificing answer quality. It is strong when used exactly as intended (Haiku + Sonnet with sessions_spawn available), but is less plug-and-play if your stack uses different model names or providers. **What it does well** - Enforces a clear, concrete decision rule: simple, short, single-step tasks stay on Haiku; anything analytical, multi-step, long, or structured *must* escalate to Sonnet. - Provides detailed escalation triggers and multilingual examples, which likely improves correct routing across many real-world prompts. - Includes explicit prohibitions on doing complex work on Haiku (no long code, no tables, no reports, no multi-step reasoning), which should reduce low-quality answers on the cheap model. **Key risks / limitations** - **Provider/model specificity:** The logic and example model IDs are tailored to Claude (Haiku / claude-sonnet-4-20250514). In environments without those exact models, you’ll need to adapt the configuration; otherwise, sessions_spawn calls may fail. - **Heuristic classification:** Complexity detection is rule-based, not dynamic. Some edge cases will still be misrouted (e.g., subtle but complex questions that look short, or verbose but simple requests). - **Potential over-escalation:** The “when in doubt, escalate” rule favors safety and quality over maximal cost savings; costs might be higher than absolutely necessary in borderline cases. - **Instruction interaction:** If combined with other skills that also try to control routing or enforce long-form behavior on the base model, there’s potential for conflicting instructions. **Best-fit scenarios** - A Claude-based assistant where you explicitly want Haiku as the default and Sonnet only for clearly complex work. - High-traffic org assistants (support, ops, engineering Q&A) where total token cost matters but you can’t compromise on complex answers. - Developers comfortable with tweaking model names who want a ready-made, opinionated routing policy to adapt for OpenAI/Gemini equivalents.

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