Competitive Intelligence → Research Brief

import os, requests, time

SL_TOKEN = os.environ["SLACK_BOT_TOKEN"]
SL_BASE = "https://slack.com/api"
SL_H = {"Authorization": f"Bearer {SL_TOKEN}"}
MV = os.environ["MAVERA_API_KEY"]
MV_BASE = "https://app.mavera.io/api/v1"
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

CHANNEL_ID = "C0123INTEL"
DAYS_BACK = 30

# 1. Fetch intel channel
oldest = str(int(time.time()) - DAYS_BACK * 86400)
messages = []
cursor = None
while True:
    params = {"channel": CHANNEL_ID, "limit": 200, "oldest": oldest}
    if cursor:
        params["cursor"] = cursor
    r = requests.get(f"{SL_BASE}/conversations.history", headers=SL_H, params=params)
    data = r.json()
    if not data.get("ok"):
        break
    messages.extend(data.get("messages", []))
    cursor = data.get("response_metadata", {}).get("next_cursor")
    if not cursor:
        break
    time.sleep(1)

intel = [m for m in messages if m.get("type") == "message" and len(m.get("text","")) > 20]
print(f"Intel input: {len(intel)} (past {DAYS_BACK} days)")

# 2. Build enriched corpus (include thread replies for context)
enriched = []
for m in sorted(intel, key=lambda x: float(x.get("ts",0)))[-50:]:
    entry = f"[{time.strftime('%Y-%m-%d', time.localtime(float(m.get('ts',0))))}] {m.get('text','')[:500]}"
    if m.get("reply_count", 0) > 0:
        replies = requests.get(f"{SL_BASE}/conversations.replies", headers=SL_H,
            params={"channel": CHANNEL_ID, "ts": m["ts"], "limit": 5}).json()
        if replies.get("ok"):
            for rep in replies.get("messages", [])[1:]:
                entry += f"\n  → Reply: {rep.get('text','')[:200]}"
        time.sleep(1)
    enriched.append(entry)

corpus = "\n\n".join(enriched)

# 3. Mave research brief
brief = requests.post(f"{MV_BASE}/mave/chat", headers=MV_H, json={
    "message": f"Competitive intelligence analyst. Synthesize {len(intel)} internal observations from our #competitive-intel channel.\n\n"
        f"RAW INTEL:\n{corpus[:8000]}\n\n"
        "Produce a COMPETITIVE RESEARCH BRIEF with:\n\n"
        "1. **Executive Summary** (3 sentences)\n"
        "2. **Competitor Activity Matrix** — What each competitor did, our assessment\n"
        "3. **Pricing Intelligence** — Any pricing changes detected\n"
        "4. **Feature Gap Analysis** — What competitors have that we don't\n"
        "5. **Customer Movement** — Any switching signals (theirs to us, ours to them)\n"
        "6. **Recommended Actions** for Product, Marketing, and Sales\n"
        "7. **Watch List** — Emerging threats to monitor next month\n\n"
        "Format as a brief that can be shared directly with leadership."
}).json()

print(f"\n{'='*60}\nCOMPETITIVE RESEARCH BRIEF — {DAYS_BACK}-day window\n{'='*60}")
print(brief.get("content", "")[:3000])

const SL_TOKEN = process.env.SLACK_BOT_TOKEN;
const SL_BASE = "https://slack.com/api";
const SL_H = { Authorization: `Bearer ${SL_TOKEN}` };
const MV = process.env.MAVERA_API_KEY;
const MV_BASE = "https://app.mavera.io/api/v1";
const MV_H = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

const CHANNEL_ID = "C0123INTEL";
const DAYS_BACK = 30;
const oldest = String(Math.floor(Date.now() / 1000) - DAYS_BACK * 86400);

// 1. Fetch
const messages = [];
let cursor;
do {
  const params = new URLSearchParams({ channel: CHANNEL_ID, limit: "200", oldest });
  if (cursor) params.set("cursor", cursor);
  const data = await (await fetch(`${SL_BASE}/conversations.history?${params}`, { headers: SL_H })).json();
  if (!data.ok) break;
  messages.push(...(data.messages || []));
  cursor = data.response_metadata?.next_cursor;
  await new Promise(r => setTimeout(r, 1000));
} while (cursor);

const intel = messages.filter(m => m.type === "message" && (m.text||"").length > 20);
console.log(`Intel messages: ${intel.length}`);

// 2. Enrich with replies
const enriched = [];
for (const m of intel.sort((a,b) => parseFloat(a.ts)-parseFloat(b.ts)).slice(-50)) {
  let entry = `[${new Date(parseFloat(m.ts)*1000).toISOString().slice(0,10)}] ${(m.text||"").slice(0,500)}`;
  if ((m.reply_count||0) > 0) {
    const replies = await (await fetch(
      `${SL_BASE}/conversations.replies?channel=${CHANNEL_ID}&ts=${m.ts}&limit=5`, { headers: SL_H })).json();
    if (replies.ok) for (const rep of (replies.messages||[]).slice(1))
      entry += `\n  → Reply: ${(rep.text||"").slice(0,200)}`;
    await new Promise(r => setTimeout(r, 1000));
  }
  enriched.push(entry);
}

// 3. Brief
const brief = await fetch(`${MV_BASE}/mave/chat`, { method: "POST", headers: MV_H,
  body: JSON.stringify({ message: `Competitive analyst. ${intel.length} observations from #competitive-intel.\n\n${enriched.join("\n\n").slice(0,8000)}\n\nBRIEF: Executive Summary, Competitor Activity Matrix, Pricing Intel, Feature Gaps, Customer Movement, Actions (Product/Marketing/Sales), Watch List. Leadership-ready.` }),
}).then(r => r.json());

console.log(`\n${"=".repeat(60)}\nCOMPETITIVE RESEARCH BRIEF`);
console.log((brief.content || "").slice(0, 3000));