Find leads in public conversations
Catch people publicly shopping for an alternative to your competitors, qualify them against your ICP, and get drafted openers for each.
Set it up
1. Connect the Octolens MCP — add the server URL in your client and sign in. OAuth, no API key. Per-client instructions · docs
https://app.octolens.com/api/mcp/v22. Hand your agent the playbook — hit Copy below (it grabs the instruction plus the full playbook), fill in the placeholders, and paste it into your agent. Pasting the playbook instead of describing the idea makes the agent run this exact workflow rather than improvise its own.
Set up a daily recurring task using the playbook below. Product: "{PRODUCT_NAME}". Competitors: {COMPETITORS}. ICP: {ICP_DESCRIPTION}.What it does
- ✓Scans competitor and category mentions from the past 24 hours
- ✓Ranks buying intent: active alternative-seeking is hot, competitor pain is warm, spam is skipped
- ✓Qualifies each lead against your ICP before it reaches you
- ✓Dedupes against authors and threads already surfaced
- ✓Drafts an in-thread reply or DM opener grounded in the buyer's actual words
- ✓Posts a digest with hot leads first
Delivers: A daily lead digest: every public buying conversation quoted, linked, ICP-qualified, and paired with a drafted opener — for a human to review and send.
Inputs
| Placeholder | Required | Description | Example |
|---|---|---|---|
| {PRODUCT_NAME} | Required | Your product — used to frame the suggested angle | Acme |
| {COMPETITORS} | Required | Competitor names tracked as keywords in Octolens | CompetitorOne, CompetitorTwo |
| {ICP_DESCRIPTION} | Required | One line describing who a qualified buyer is | Heads of growth at product-led B2B SaaS companies with active communities |
How your agent runs it
- 1
Check tracked keywords — The agent confirms your competitors are tracked and notes any that aren't — it never adds keywords unasked.
list_keywords - 2
Pull intent-heavy mentions — Fetches the last 24 hours of competitor and category mentions, prioritizing buy-intent AI tags.
list_tagslist_mentions - 3
Rank buying intent — “Alternative to X” and “any recommendations?” rank hot; competitor pain ranks warm; vendors and jokes get skipped.
- 4
Qualify against your ICP — Authors clearly outside your ICP are dropped before they cost you attention.
- 5
Dedupe — Authors and threads surfaced in previous runs are skipped.
- 6
Draft openers and report — Each lead gets context, a suggested angle, and a 2–3 sentence opener draft — delivered as a digest, hot first.
Tools used
list_keywordsOctolens MCPConfirm competitor and category keywords are trackedlist_tagsOctolens MCPDiscover buy-intent and competitor tags available for filteringlist_mentionsOctolens MCPFetch competitor and category mentions from the past 24 hours
All 23 Octolens MCP tools are documented on the MCP page and in the docs.
The full playbook
Replace the placeholders, then paste this into your agent as a recurring task.
Every day, do the following:
1. Call list_keywords to check what's tracked in Octolens. You need:
- the competitor keywords: {COMPETITORS}
- ideally category/pain-point keywords too, if the workspace has them
If a competitor from the list isn't tracked, note it in the final summary — don't add keywords without being asked.
2. Call list_tags to see which AI tags exist in this workspace, then call list_mentions for the past 24 hours across those keywords, prioritizing mentions tagged with buy-intent-adjacent tags (e.g. buy_intent, competitor_mention).
3. For each mention, classify buying intent into exactly one bucket:
- hot — actively looking: "alternative to {competitor}", "recommendations for", "switching from", "does anyone know a tool that", pricing complaints paired with a search
- warm — clear pain with a competitor or the category, but not explicitly shopping
- skip — competitor marketing, employees, students, jokes, vendor spam, anything not from a plausible buyer
4. Drop everything classified as "skip". Then qualify what's left against our ICP: {ICP_DESCRIPTION}. If the author is clearly outside the ICP, move them to skip.
5. Dedupe: skip any author or source URL already surfaced in a previous run.
6. For each remaining lead, produce an entry:
**Intent:** hot | warm
**Quote:** > {original quote, trim to ~300 chars}
**Source:** {url} ({source}, {timestamp})
**Author:** {authorName} (@{author})
**Context:** one line — what they're trying to solve and which competitor they mentioned
**Suggested angle:** one line on how {PRODUCT_NAME} fits their stated problem
**Draft opener:** 2–3 sentences replying in-thread or via DM. Reference their actual problem. Helpful first, product second. No "Hope this finds you well", no feature dumps.
7. Post the digest in chat, hot leads first:
- Conversations scanned: N
- Leads: N (X hot, Y warm)
- Already surfaced: N
- The entries from step 6
If there are no new leads, say "No new buying conversations today" and exit cleanly.
Do not contact anyone or post replies. Drafts are for a human to review, edit, and send.More skills
Surface early churn signals
Flag negative mentions with switching language or blocked workflows the day they're posted — with a drafted reply ready for human review.
Weekly share-of-voice report
A weekly report on your share of voice vs competitors — counts, sentiment, and what actually drove the changes, with linked evidence.
Turn mentions into Linear issues
Catch bug reports and feature requests posted in public — on Reddit, X, LinkedIn, Hacker News, GitHub — and file them as Linear issues automatically.
Give your agents context on what happens online
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