ai-chat

GitHub

指导优化 Windmill AI 聊天组件,重点规范系统提示词、工具定义及上下文窗口管理。要求变更前后进行 A/B 测试,严格控制 Token 消耗,精简工具参数与返回结果,确保行为可度量。

.agents/skills/ai-chat/SKILL.md windmill-labs/windmill

Trigger Scenarios

编辑聊天工具或系统提示词 修改上下文窗口管理逻辑

Install

npx skills add windmill-labs/windmill --skill ai-chat -g -y
More Options

Non-standard path

npx skills add https://github.com/windmill-labs/windmill/tree/main/.agents/skills/ai-chat -g -y

Use without installing

npx skills use windmill-labs/windmill@ai-chat

指定 Agent (Claude Code)

npx skills add windmill-labs/windmill --skill ai-chat -a claude-code -g -y

安装 repo 全部 skill

npx skills add windmill-labs/windmill --all -g -y

预览 repo 内 skill

npx skills add windmill-labs/windmill --list

SKILL.md

Frontmatter
{
    "name": "ai-chat",
    "description": "Guidance for improving the Windmill AI chat (copilot), especially global mode — tools, prompts, and context-window discipline. Use when editing chat tools, system prompts, or tool-result shapes under frontend\/src\/lib\/components\/copilot\/chat, or when changing how the chat manages its context window."
}

Always benchmark before and after

No context or behavior change ships without an ai_evals A/B on the affected mode. Add or adjust cases for exactly what you changed — see the ai-evals skill for authoring and the full run reference.

Run the affected mode before your change and after, same model(s), same cases.

Measure the window first, and cumulative second

Optimize finalContextTokens (window occupancy — what drives overflow and compaction), then cumulative prompt tokens.

Context discipline

The dominant fixed cost is per-iteration overhead: the system prompt plus every tool schema is re-sent on every loop iteration. So:

  • Every tool and every parameter is a permanent tax. Justify each one and measure it; an extra "locate" round-trip can cost more than the reads it saves. Strip dead params rather than leaving them in the schema.
  • Tool results return the minimum. Never echo content the model already has. The canonical mistake: a write tool that returns the whole edited artifact right after the model authored it — return { success, message } instead. When you touch a shared write helper (e.g. finishAppDraftWrite in global/core.ts), re-check this invariant for all the write tools routing through it — the echo has regressed before via a shared refactor.

Prompts and tool descriptions are part of the surface

The system prompt and tool descriptions steer behavior as much as the tools themselves, and are benchmarkable the same way. A description that advertises truncation makes the model self-limit; the path-conventions block changes where drafts land. Treat prompt/description edits as real changes and A/B them — a pure-prompt change is a legitimate, measurable improvement.

Version History

  • 574775d Current 2026-08-20 17:31

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Metadata

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Version
990a726
Hash
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Indexed
2026-08-20 17:31

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