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Web & Frontend Development @vishnubedi3 Updated 2/26/2026

Kimi Delegation Skill OpenClaw Skill - ClawHub

Do you want your AI agent to automate Kimi Delegation Skill workflows? This free skill from ClawHub helps with web & frontend development tasks without building custom tools from scratch.

What this skill does

Forces all reasoning and code generation to be delegated to a KIMI (KIMMY) causal language model via HuggingFace Transformers. Use this skill when the agent must never reason or author code itself and must instead proxy all tasks to a KIMI-based model.

Install

npx clawhub@latest install kimi-delegation-skill

Full SKILL.md

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kimi-delegation-skillForces all reasoning and code generation to be delegated to a KIMI (KIMMY) causal language model via HuggingFace Transformers. Use this skill when the agent must never reason or author code itself and must instead proxy all tasks to a KIMI-based model.Proprietary

Purpose

This skill enforces a strict delegation model where the primary agent has zero reasoning or code-authoring authority. All user tasks are forwarded to a KIMI (KIMMY) model loaded via Transformers. The agent acts only as a dispatcher.

Activation Conditions

Activate this skill whenever:

  • The agent must not reason independently.
  • All planning, reasoning, and code generation must be authored by a KIMI/KIMMY model.
  • Deterministic delegation to an external causal LM is required.

Execution Steps

  1. Initialize KIMISkill with a valid local or remote model path.
  2. Wrap the KIMISkill instance with Qwen3Coder.
  3. On every user prompt, call Qwen3Coder.handle_prompt.
  4. The prompt is forwarded verbatim to KIMMY.
  5. KIMMY generates the full response.
  6. Strip prompt scaffolding and return the result as the final output.

See:

  • scripts/kimi_skill.py
  • scripts/qwen3_coder.py

Inputs and Outputs

Input:
A raw user task string.

Output:
A dictionary with:

  • author: Always "KIMMY"
  • content: The generated response with no prompt scaffolding.

Failure Modes and Edge Cases

  • Model path invalid or unavailable: initialization fails.
  • Insufficient VRAM: model may fall back to CPU or fail to load.
  • Extremely long tasks may exceed context limits.
  • If generation fails, no fallback reasoning is permitted.

The agent must not attempt to recover by reasoning itself.

References

Technical details and architectural rationale are in:

  • references/REFERENCE.md
Original URL: https://github.com/openclaw/skills/blob/main/skills/vishnubedi3/kimi-delegation-skill

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