kimi-delegation-skill

name	kimi-delegation-skill
description	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.
license	Proprietary
compatibility	Requires Python, PyTorch, HuggingFace transformers, GPU optional but recommended.
allowed-tools	Python(Read Write)
metadata	{"author":"internal","version":"1.0"}

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