Competitive intelligence agent that briefs reps from Gong calls

def list_all_calls(self, from_date_time, to_date_time, max_pages=20):
    calls, cursor = [], None
    for _ in range(max_pages):
        page = self.execute_tool(
            "gong_calls_list",
            from_date_time=from_date_time,
            to_date_time=to_date_time,
            **({"cursor": cursor} if cursor else {}),
        )
        calls.extend(page.get("calls") or [])
        cursor = page.get("cursor") or (page.get("records") or {}).get("cursor")
        if not cursor:
            break
    return calls

# Then enrich in batches of 20 -- tracker hits live in content.trackers
details = self.execute_tool("gong_calls_get", call_ids=batch)

# Primary signal: Gong tracker hits on the call
tracker_matches = detect_mentions_from_trackers(call_detail, competitor_names)

# Fallback: sentence-level transcript scan, whole-word match only
# ("Sales" never falsely matches "Salesforce")
if not tracker_matches:
    transcripts = self.execute_tool(
        "gong_calls_transcript_get", call_ids=calls_needing_fallback
    )
    for sentence in transcript_sentences:
        if _word_matches(sentence.get("text", ""), competitor):
            # capture ms offset so the DM can say "mention at 0:41"
            hits[competitor] = int(sentence.get("start"))

# gong_calls_get never returns parties data through this tool wrapper,
# so resolve each call's metaData.primaryUserId in one batch instead
primary_user_ids = sorted({
    str(c["metaData"]["primaryUserId"])
    for c in calls_with_details
    if (c.get("metaData") or {}).get("primaryUserId")
})
users = self.execute_tool("gong_users_get", user_ids=primary_user_ids)
user_lookup = {str(u["id"]): u for u in users.get("users", [])}

# One digest per rep, covering every call and competitor they touched
digests = build_rep_digests(
    calls_with_details, competitor_names, pmm_domain, user_lookup=user_lookup
)

# PRIMARY: fetch the known parent page -- immediate, no index lag
fetch_data = self.execute_tool("notionmcp_notion-fetch", id=parent_page_id)
children = _parse_child_pages(fetch_data.get("text", ""))

for child_id, child_url, title in children:
    if title.strip().casefold() == competitor_name.casefold():
        return {"id": child_id, "title": title, "url": child_url}

# FALLBACK: notion-search (its index is eventually consistent,
# verified live -- a just-created page can take minutes to appear)
search = self.execute_tool("notionmcp_notion-search", query=competitor_name)

# Idempotency: one key per (rep, call, competitor) ever DMed
new_mentions = [
    m for m in digest.mentions
    if not state.is_briefed(
        compute_mention_key(digest.rep_identifier, m.call_id, m.competitor)
    )
]
if not new_mentions:
    return "already_briefed", "all mentions already briefed in a prior run"

user_id = slack.resolve_user_id(digest.rep_identifier)  # email-exact match
slack.execute_tool(
    "slackmcp_slack_send_message",
    channel_id=user_id,  # a user ID as channel_id opens their DM
    message=render_digest_text(filtered_digest, battlecard_links),
)
state.mark_many_briefed(keys)