#!/usr/bin/env bun /** * proposal-redline-advisor * Evaluates proposals and recommends redlines using OpenAI. */ import { parseArgs } from "util"; import { existsSync, mkdirSync, appendFileSync, readFileSync } from "fs"; import { join, dirname, resolve } from "path"; type OutputFormat = "markdown" | "json"; type RiskProfile = "conservative" | "balanced" | "aggressive"; type ClauseTemplate = { clauses?: Array<{ title?: string; body?: string; notes?: string }>; metadata?: Record; }; interface SkillOptions { content: string; dealSize?: string; industry?: string; riskProfile: RiskProfile; mustKeep?: string[]; format: OutputFormat; model: string; output?: string; template?: ClauseTemplate; } interface OpenAIChatResponse { choices?: Array<{ message?: { content?: string | null; }; }>; error?: { message?: string; }; } const SKILL_SLUG = "proposal-redline-advisor"; 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()}] ${message}\n`; appendFileSync(logFile, entry); const prefix = level === "success" ? "✅" : level === "error" ? "❌" : "â„šī¸"; console.log(`${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) || "proposal"; } function parseJsonTemplate(content: string): ClauseTemplate | undefined { try { const data = JSON.parse(content); if (typeof data === "object" && data !== null) { return data as ClauseTemplate; } } catch (_error) { // treat as plain text if parsing fails } return undefined; } function parseMustKeep(value?: string): string[] | undefined { if (!value) return undefined; const items = value .split(",") .map(item => item.trim()) .filter(Boolean); return items.length ? items : undefined; } function showHelp(): void { console.log(` proposal-redline-advisor - Evaluate proposals and recommend redlines using AI Usage: skills run proposal-redline-advisor -- [options] skills run proposal-redline-advisor -- --text "" [options] Options: -h, --help Show this help message --text Inline proposal text --deal-size Deal size (default: unspecified) --industry Industry context (default: general) --risk-profile Risk profile: conservative | balanced | aggressive (default: balanced) --must-keep Comma-separated clauses to preserve --format Output format: markdown | json (default: markdown) --model OpenAI model (default: gpt-4o-mini) --output Custom output file path Output includes: - Executive summary - Risk exposures - Recommended redlines - Required approvals - Leverage talking points - Follow-up checklist Examples: skills run proposal-redline-advisor -- ./contract.txt --risk-profile "conservative" skills run proposal-redline-advisor -- --text "Vendor agreement..." --industry "Technology" 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" }, text: { type: "string" }, "deal-size": { type: "string" }, industry: { type: "string" }, "risk-profile": { type: "string", default: "balanced" }, "must-keep": { 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); } let content = values.text || ""; let template: ClauseTemplate | undefined; if (!content && positionals[0]) { const filePath = resolve(positionals[0]); const fileContent = readFileSync(filePath, "utf-8"); template = parseJsonTemplate(fileContent); content = template ? "" : fileContent; } if (!content.trim() && !template) { throw new Error("Provide proposal text via file path, JSON template, or --text."); } const format: OutputFormat = values.format === "json" ? "json" : values.format === "markdown" ? "markdown" : "markdown"; let riskProfile: RiskProfile = "balanced"; if (values["risk-profile"] === "conservative" || values["risk-profile"] === "balanced" || values["risk-profile"] === "aggressive") { riskProfile = values["risk-profile"]; } return { content, dealSize: values["deal-size"], industry: values.industry, riskProfile, mustKeep: parseMustKeep(values["must-keep"]), format, model: values.model, output: values.output, template, }; } function buildPrompt(options: SkillOptions) { const system = `You are a commercial counsel reviewing proposals. Identify risk exposures, propose redlines, and note when to escalate to legal or finance. Respect the stated negotiation posture and preserve any must-keep clauses.`; const instructions = options.format === "json" ? "Respond in JSON with keys: summary, risks, redlines, approvals, leverage, follow_up. Each redline should include clause_title, original_text, issue, recommended_change, fallback_option." : "Respond in polished Markdown. Start with an executive summary, include tables for high-risk clauses and recommended redlines, note required approvals, leverage talking points, and follow-up checklist."; const payload = { deal_size: options.dealSize || "unspecified", industry: options.industry || "general", risk_profile: options.riskProfile, must_keep: options.mustKeep, proposal_text: options.content.substring(0, 6000), structured_template: options.template, }; const user = `${instructions}\n\n${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: 0.33, max_tokens: options.format === "json" ? 2200 : 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); } function buildExportPath(skillExportsDir: string, sessionStamp: string, options: SkillOptions) { if (options.output) { return resolve(options.output); } const descriptorParts = [options.industry || "proposal", options.riskProfile]; 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 { const options = parseOptions(); logger.info("Parsed proposal data and options."); const { system, user } = buildPrompt(options); logger.info("Constructed redline review prompt."); const content = await callOpenAI(options, system, user); logger.success("Received redline recommendations from OpenAI."); const exportPath = buildExportPath(skillExportsDir, sessionStamp, options); await writeExport(exportPath, content); logger.success(`Saved redline 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();