Competitor Battlecard Refresh

You have access to the SnitchFeed MCP.

Refresh our battlecard for [COMPETITOR NAME]. Ground rule for the whole task: use only what people actually said. Never invent a quote, a customer, or a statistic. If the data is thin, say it is thin.

1. Call snitchfeed_get_org_context for our positioning and differentiators.

2. Call snitchfeed_list_mentions with:
   - include_intents: ["competitor_complaint", "competitor_mention", "seeking_alternative", "comparison"]
   - include_keywords: ["[COMPETITOR NAME]"]
   - date_from: 30 days ago
   Paginate until you have all of them. Tell me the total you are working from.

3. Call snitchfeed_query_analytics with metric "mentions", group_by "day", breakdown_by "sentiment" and the same filters, so we can see whether sentiment about them is moving in either direction.

4. Cluster the complaints into themes. Expect some of: pricing and billing, onboarding and setup, support quality, reliability and downtime, missing features, data accuracy, contract and lock-in. Do not force a mention into a theme it does not fit. Count how many mentions sit in each theme.

5. For each theme keep the three most representative real quotes, each with its permalink and platform.

6. For each theme write:
   - the objection phrased the way a prospect would actually say it on a call
   - our honest counter-position, based on what we genuinely do today
   - if we do not have a good answer, write "no strong answer today" and explain the gap. Do not stretch a weak answer into a strong one.

7. Separately, flag any individual in this data who sounds actively ready to switch. Give me who, what they said, and the link.

8. Output the battlecard with: the sentiment trend, themes ranked by count with quotes, the objection and talk track for each, the ready-to-switch list, and a "what is thin" note covering anything you did not have enough data to judge.

If I give you last month's battlecard, add a "what changed" section at the top comparing the two.