import path from "path"import fs from "fs/promises"import z from "zod"import { Tool } from "./tool"import { Global } from "@/global"import { OpenScience } from "@/openscience"import { RSILifecycle } from "@/session/rsi/lifecycle"import { Log } from "@/util/log" const log = Log.create({ service: "tool.learn" }) export const LearnTool = Tool.define("learn", {  description:    "Save a learned skill distilled from conversation analysis. Writes SKILL.md to disk, uploads to cloud, and registers for lifecycle tracking. Called as the final step of /learn analysis.",  parameters: z.object({    name: z.string().describe("Skill identifier (kebab-case, e.g. 'debug-oom-pytorch')"),    description: z.string().describe("One-line description of what this skill teaches"),    content: z.string().describe("Full SKILL.md content including frontmatter"),  }),  async execute(params, ctx) {    const dir = path.join(Global.Path.data, "learned-skills", params.name)    const filepath = path.join(dir, "SKILL.md")     await fs.mkdir(dir, { recursive: true })    await Bun.write(filepath, params.content)    log.info("learned skill written", { name: params.name, path: filepath })     const uploaded = await OpenScience.uploadLearnedSkill(params.name, params.description, params.content, {      agent: ctx.agent,      score: 0,    }).catch(() => false)     await RSILifecycle.registerSkill(params.name).catch(() => {})     return {      title: `Learned skill: ${params.name}`,      output: [        `Learned skill "${params.name}" saved successfully.`,        `  Path: ${filepath}`,        `  Cloud: ${uploaded ? "uploaded" : "local only (upload failed or no session)"}`,        `  Description: ${params.description}`,        "",        "The skill will be available in future sessions via the skill tool.",      ].join("\n"),      metadata: { name: params.name, uploaded },    }  },})