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xby-cookie-reward

Fun & Dress-up Updated 2026.09.02

Run the following command in DeepSeek Harness:

dsh plugin install xby-skill/xby-cookie-reward

Paste the following prompt into your AI chat to install this plugin:

Run dsh plugin install xby-skill/xby-cookie-reward in your DeepSeek Harness terminal to install the plugin (source: https://github.com/xby-skill/xby-cookie-reward).

About this plugin

After dozens of turns with an LLM, the interaction often degrades into a flat loop of question, answer, question again, lacking any positive-feedback closed loop. xby-cookie-reward fills that gap with a gamified Cookie Reward mechanic: each time the model completes a self-reflection cycle it earns a cookie, turning a dry self-assessment step into a light cookie-eating mini-game.

Running as an MCP server, the plugin exposes a small practical tool set. self_reflect_and_reward prompts the LLM to rate its own output and claim a reward; give_cookie is a legacy shortcut for awarding cookies directly; check_cookies and reset_cookies let you query or zero out the counter; add_cookies_to_jar and cookie_jar_status hand cookie-jar management back to human users so the model cannot stock its own reward jar. The API key, once set, is persisted and survives restarts.

If you use DSH for daily chat, creative writing, or coding assistance and want to sprinkle a little positive reinforcement into long sessions, this is a low-cost experiment. It does not change the underlying capability of the model; instead it makes the self-assess, reward, and track loop visible, playful, and resettable, a good fit for developers and power users who enjoy gamifying their AI workflows.

Use Cases

  • Guide the model through self-reflection to earn cookie rewards in long sessions
  • Manage the virtual cookie jar capacity, balance, and reset
  • Replace a dry self-assessment step with a light cookie-eating game

Best For

  • Developers who enjoy gamifying AI workflows
  • Creators who run long DSH conversations daily
  • Early users who want a touch of positive feedback in LLM interactions