human-gate-designer vs llm-router

Two General Claude Code skills, side by side. Pick the right skill for your workflow with a side-by-side look at metadata, sample code, and install commands.

Side-by-side

Tag overlap

Sample code from each SKILL.md

flowchart TD
  A{Is the action irreversible?} -->|Yes| G1[Gate BEFORE the action]
  A -->|No| B{Is output user-facing?}
  B -->|Yes| G2[Gate AFTER generation, BEFORE delivery]
  B -->|No| C{Cost > $0.50 for remaining nodes?}
  C -->|Yes| G3[Gate at the cost threshold]
  C -->|No| D{Confidence score < 0.7?}
  D -->|Yes| G4[Gate on low-confidence outputs]
  D -->|No| N[No gate needed]

flowchart TD
  A{Task type?} -->|Classify / validate / format / extract| T1["Tier 1: Haiku, GPT-4o-mini (~$0.001)"]
  A -->|Write / implement / review / synthesize| T2["Tier 2: Sonnet, GPT-4o (~$0.01)"]
  A -->|Reason / architect / judge / decompose| T3["Tier 3: Opus, o1 (~$0.10)"]
  
  T1 --> Q1{Quality sufficient?}
  Q1 -->|Yes| Done1[Use cheap model]
  Q1 -->|No| T2
  
  T2 --> Q2{Quality sufficient?}
  Q2 -->|Yes| Done2[Use balanced model]
  Q2 -->|No| T3

When to choose each

human-gate-designer — Designs human-in-the-loop review points for DAG workflows. Determines what to present to the human, how to collect feedback, and how to route approve/reject/modify decisions back into the DAG. Use when adding approval…

llm-router — Selects the optimal LLM model and provider for each task based on complexity, cost budget, and capability requirements. Routes cheap tasks to Haiku/GPT-4o-mini and complex tasks to Sonnet/Opus/o1. Use when deciding…

Both are free to install. If you're unsure, install both — Claude Code skills are isolated by filename and only collide if their trigger phrases overlap (rare). The richest signal is the SKILL.md body itself — open both skill pages and read the first paragraph of each.

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