#!/usr/bin/env bun /** * exam-readiness-check * Evaluates exam readiness using OpenAI. */ import { parseArgs } from "util"; import { existsSync, mkdirSync, appendFileSync, readFileSync } from "fs"; import { join, dirname, resolve } from "path"; import { randomUUID } from "crypto"; type OutputFormat = "markdown" | "json"; type ReadinessTemplate = Record; interface SkillOptions { data: string; exam?: string; level?: string; target?: string; format: OutputFormat; model: string; output?: string; template?: ReadinessTemplate; } interface OpenAIChatResponse { choices?: Array<{ message?: { content?: string | null; }; }>; error?: { message?: string; }; } const SKILL_SLUG = "exam-readiness-check"; const SESSION_ID = randomUUID().slice(0, 8); 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_${sessionStamp}_${SESSION_ID}.log`); function write(level: "info" | "success" | "error", message: string) { const timestamp = new Date().toISOString(); const entry = `[${timestamp}] [${level.toUpperCase()}] ${message}\n`; appendFileSync(logFile, entry); const prefix = level === "success" ? "✅" : level === "error" ? "❌" : "â„šī¸"; if (level === "error") { console.error(`${prefix} ${message}`); } else { console.log(`${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) || "exam-readiness"; } function parseJsonTemplate(content: string): ReadinessTemplate | undefined { try { const data = JSON.parse(content); if (typeof data === "object" && data !== null) { return data as ReadinessTemplate; } } catch (_error) { // treat as text when parsing fails } return undefined; } function parseOptions(): SkillOptions { const { values, positionals } = parseArgs({ args: Bun.argv.slice(2), options: { text: { type: "string" }, exam: { type: "string" }, level: { type: "string" }, target: { type: "string" }, format: { type: "string", default: "markdown" }, model: { type: "string", default: "gpt-4o-mini" }, output: { type: "string" }, help: { type: "boolean", short: "h" }, }, allowPositionals: true, }); if (values.help) { console.log(` Exam Readiness Check - Evaluates exam readiness Usage: skills run exam-readiness-check -- [options] Options: --text Practice data (or use positional arg) --exam Exam name --level Difficulty level --target Target score/goal --format Output format: markdown, json (default: markdown) --model OpenAI model to use (default: gpt-4o-mini) --output Save report to file --help, -h Show this help `); process.exit(0); } let data = values.text || ""; let template: ReadinessTemplate | undefined; if (!data && positionals[0]) { const filePath = resolve(positionals[0]); if (existsSync(filePath)) { const content = readFileSync(filePath, "utf-8"); template = parseJsonTemplate(content); data = template ? "" : content; } else { data = positionals.join(" "); } } if (!data.trim() && !template) { throw new Error("Provide practice data via positional text, file path, or --text."); } const format: OutputFormat = values.format === "json" ? "json" : values.format === "markdown" ? "markdown" : "markdown"; return { data, exam: values.exam as string, level: values.level as string, target: values.target as string, format, model: values.model as string, output: values.output as string, template, }; } function buildPrompt(options: SkillOptions) { const system = `You are an exam readiness analyst. Evaluate practice results, infer confidence, and recommend targeted preparation. Provide balanced feedback, caution on assumptions, and note when to validate with instructors.`; const instructions = options.format === "json" ? "Respond in JSON with keys: readiness_summary, strengths, focus_topics, timing_notes, recommended_practice, accountability. Include quantitative indicators where available." : "Respond in Markdown with sections for Readiness Summary, Strengths, Focus Topics, Timing Notes, Recommended Practice, and Accountability Plan. Include data references and caution notes."; const payload = { exam: options.exam || "upcoming exam", level: options.level || "general", target: options.target || "improvement", practice_data: options.data.substring(0, 6000), structured_template: options.template, }; const user = `${instructions}\n\nReadiness context:\n${JSON.stringify(payload, 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: 0.38, max_tokens: options.format === "json" ? 1900 : 1800, }; 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); } function buildExportPath(skillExportsDir: string, sessionStamp: string, options: SkillOptions) { if (options.output) { return resolve(options.output); } const descriptorParts = [options.exam || "exam", options.target || "goal"]; const base = slugify(descriptorParts.filter(Boolean).join("-")); const extension = options.format === "json" ? "json" : "md"; return join(skillExportsDir, `${base}_${sessionStamp}.${extension}`); } function preview(content: string) { const lines = content.split(/\r?\n/).slice(0, 8); lines.forEach(line => console.log(` ${line}`)); if (content.split(/\r?\n/).length > 8) { console.log(" ..."); } } async function main() { const { sessionStamp, skillExportsDir, skillLogsDir } = getPaths(); const logger = createLogger(skillLogsDir, sessionStamp); try { logger.info(`Starting ${SKILL_SLUG} session: ${SESSION_ID}`); const options = parseOptions(); logger.info("Parsed practice data and options."); const { system, user } = buildPrompt(options); logger.info("Constructed exam readiness prompt."); const content = await callOpenAI(options, system, user); logger.success("Received exam readiness report from OpenAI."); const exportPath = buildExportPath(skillExportsDir, sessionStamp, options); await writeExport(exportPath, content); logger.success(`Saved readiness report to ${exportPath}`); console.log("\nPreview:"); preview(content); } catch (error) { const message = error instanceof Error ? error.message : String(error); logger.error(message); process.exitCode = 1; } } main();