Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Skeall audit fixes: instruction-based framing, decision table, code block tags, dir/name match, references section
What This Skill Does
ZeroAPI routes tasks to the optimal AI model across your active subscriptions using a 9-step classification algorithm. Each task type maps to the model with the strongest benchmark: Codex for code and math, Gemini Pro for large context and research, Kimi for multi-agent orchestration, Opus for reasoning and judgment.
Using one model for everything leaves benchmark advantages unused; ZeroAPI picks the specialist with the strongest score for each task type.
When to use it
- Automatically routing a math proof to Codex instead of Opus
- Analyzing a 200-page PDF using Gemini Pro's 1M context window
- Splitting code writing to Codex and code review to Opus in one session
- Running low-latency health checks with Flash-Lite's 0.23s TTFT
- Coordinating a 3-agent research, write, and review pipeline via Kimi
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Analyze this 200-page PDF and write a Python parser for its data format
- 1Estimate token count: a 200-page PDF exceeds 100k tokens, Step 1 matches
- 2Delegate to RESEARCH tier: /agent gemini-researcher Analyze the attached PDF and identify the data format structure
- 3Receive structured analysis identifying the format fields and layout
- 4Delegate to CODE tier: /agent codex Write a Python parser for the format described: <summary from previous step>
- 5Merge sub-agent outputs into a single response with analysis and working parser code
Structured format analysis from Gemini Pro plus a working Python parser from Codex, combined into one response
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.