#!/usr/bin/env bun /** * webinar-script-coach * Generates webinar run-of-show and scripting guidance using OpenAI. */ import { parseArgs } from "util"; import { existsSync, mkdirSync, appendFileSync } from "fs"; import { join, dirname } from "path"; type OutputFormat = "markdown" | "json"; interface SkillOptions { topic: string; duration: number; audience?: string; hosts?: string; goals?: string; format: OutputFormat; model: string; output?: string; } interface OpenAIChatResponse { choices?: Array<{ message?: { content?: string | null; }; }>; error?: { message?: string; }; } const SKILL_SLUG = "webinar-script-coach"; function ensureDir(path: string) { if (!existsSync(path)) { mkdirSync(path, { recursive: true }); } } function getPaths() { const sessionStamp = new Date().toISOString().replace(/[:.]/g, "_").replace(/-/g, "_"); const exportsRoot = process.env.SKILLS_EXPORTS_DIR || join(process.cwd(), ".skills", "exports"); const logsRoot = process.env.SKILLS_LOGS_DIR || join(process.cwd(), ".skills", "logs"); const skillExportsDir = join(exportsRoot, SKILL_SLUG); const skillLogsDir = join(logsRoot, SKILL_SLUG); ensureDir(skillExportsDir); ensureDir(skillLogsDir); return { sessionStamp, skillExportsDir, skillLogsDir, }; } function createLogger(logDir: string, sessionStamp: string) { const logFile = join(logDir, `log_${sessionStamp}.txt`); function write(level: "info" | "success" | "error", message: string) { const timestamp = new Date().toISOString(); const entry = `[${timestamp}] [${level.toUpperCase()}] ${message}\n`; appendFileSync(logFile, entry); const prefix = level === "success" ? "✅" : level === "error" ? "❌" : "ℹ️"; console.log(`${prefix} ${message}`); } return { info: (message: string) => write("info", message), success: (message: string) => write("success", message), error: (message: string) => write("error", message), logFile, }; } function slugify(value: string): string { return value .toLowerCase() .replace(/[^a-z0-9]+/g, "-") .replace(/^-+|-+$/g, "") .slice(0, 40) || "webinar"; } function showHelp(): void { console.log(` webinar-script-coach - Generate webinar run-of-show and scripting guidance using AI Usage: skills run webinar-script-coach -- "" [options] skills run webinar-script-coach -- --topic "" [options] Options: -h, --help Show this help message --topic Webinar topic/brief --duration Duration in minutes (default: 60, min: 15) --audience Target audience description --hosts Host/speaker names --goals Goals for the webinar --format Output format: markdown | json (default: markdown) --model OpenAI model (default: gpt-4o-mini) --output Custom output file path Output includes: - Run-of-show timeline with buffer - Segment breakdown (intro, value content, demo, interaction, outro) - Host/speaker scripts and bullet prompts - Interaction moments (polls, Q&A, chat prompts) - Slide/visual cues per segment - Technical checklist - Follow-up actions Examples: skills run webinar-script-coach -- "Customer onboarding webinar" --duration 45 skills run webinar-script-coach -- --topic "SaaS product demo" --audience "enterprise IT" Requirements: OPENAI_API_KEY environment variable must be set. `); } function parseOptions(): SkillOptions { const { values, positionals } = parseArgs({ args: Bun.argv.slice(2), options: { help: { type: "boolean", short: "h" }, topic: { type: "string" }, duration: { type: "string" }, audience: { type: "string" }, hosts: { type: "string" }, goals: { type: "string" }, format: { type: "string", default: "markdown" }, model: { type: "string", default: "gpt-4o-mini" }, output: { type: "string" }, }, allowPositionals: true, }); if (values.help) { showHelp(); process.exit(0); } const topic = values.topic || positionals.join(" ").trim(); if (!topic) { throw new Error( "Provide a webinar brief via positional text or --topic.\nExample: skills run webinar-script-coach -- \"Customer onboarding webinar\"" ); } const duration = values.duration ? parseInt(values.duration, 10) : 60; if (Number.isNaN(duration) || duration < 15) { throw new Error("--duration must be an integer >= 15."); } const format: OutputFormat = values.format === "json" ? "json" : values.format === "markdown" ? "markdown" : "markdown"; return { topic, duration, audience: values.audience, hosts: values.hosts, goals: values.goals, format, model: values.model, output: values.output, }; } function buildPrompt(options: SkillOptions) { const system = `You are a webinar producer and speaking coach. Create a comprehensive webinar plan including: - Run-of-show timeline that fits ${options.duration} minutes (with buffer). - Segment breakdown (intro, value content, demo, interaction, outro) with allocated times. - Host/speaker scripts or bullet prompts tailored to ${options.hosts || "the listed hosts"}. - Interaction moments (polls, Q&A, chat prompts) designed for ${options.audience || "the described audience"}. - Slide or visual cues per segment. - Technical checklist (rehearsal, audio/video, contingency plans). - Follow-up actions (emails, assets, CTA) aligned to goals (${options.goals || "educate, engage, convert"}). - Coaching tips for tone (${options.topic}).`; const instructions = options.format === "json" ? "Respond in JSON with keys: overview, timeline, segments, interactions, slides, checklist, followup, coaching. Timeline should be an ordered array with start_minute, end_minute, segment, description." : "Respond in polished Markdown. Start with an executive summary blockquote, include tables for timeline, bullet lists for interactions and checklist, and script excerpts per segment."; const userPayload = { topic: options.topic, duration_minutes: options.duration, audience: options.audience, hosts: options.hosts, goals: options.goals, format: options.format, }; const user = `${instructions}\n\n${JSON.stringify(userPayload, null, 2)}`; return { system, user }; } async function callOpenAI(options: SkillOptions, system: string, user: string): Promise { const apiKey = process.env.OPENAI_API_KEY; if (!apiKey) { throw new Error("OPENAI_API_KEY environment variable is required."); } const body = { model: options.model, messages: [ { role: "system", content: system }, { role: "user", content: user }, ], temperature: 0.58, max_tokens: options.format === "json" ? 2300 : 2000, }; const response = await fetch("https://api.openai.com/v1/chat/completions", { method: "POST", headers: { "Content-Type": "application/json", Authorization: `Bearer ${apiKey}`, }, body: JSON.stringify(body), }); const data: OpenAIChatResponse = await response.json(); if (!response.ok) { throw new Error(data.error?.message || `OpenAI API error (${response.status})`); } const content = data.choices?.[0]?.message?.content; if (!content) { throw new Error("OpenAI response did not include content."); } return content.trim(); } async function writeExport(path: string, content: string) { ensureDir(dirname(path)); await Bun.write(path, content); } async function run() { const options = parseOptions(); const { sessionStamp, skillExportsDir, skillLogsDir } = getPaths(); const logger = createLogger(skillLogsDir, sessionStamp); try { logger.info("Generating webinar script and run-of-show."); logger.info(`Format: ${options.format.toUpperCase()}, Model: ${options.model}`); const { system, user } = buildPrompt(options); const content = await callOpenAI(options, system, user); const slugBase = options.topic.split(/\s+/).slice(0, 4).join("-"); const planSlug = slugify(slugBase); const extension = options.format === "json" ? "json" : "md"; const defaultPath = join(skillExportsDir, `webinar-plan-${planSlug}-${sessionStamp}.${extension}`); const targetPath = options.output ? options.output : defaultPath; let finalContent = content; if (options.format === "json") { try { finalContent = JSON.stringify(JSON.parse(content), null, 2); } catch { logger.error("Model response was not valid JSON. Wrapping raw response."); finalContent = JSON.stringify({ raw: content }, null, 2); } } await writeExport(targetPath, finalContent); logger.success("Webinar plan generated successfully."); console.log("\n=== Webinar Plan Preview ===\n"); console.log(finalContent.slice(0, 1500)); if (finalContent.length > 1500) { console.log("\n… (truncated)"); } console.log(`\nExport saved to: ${targetPath}`); console.log(`Logs written to: ${skillLogsDir}`); } catch (error) { const message = error instanceof Error ? error.message : String(error); logger.error(message); process.exit(1); } } run();