Helps the user with SnitchFeed platform questions — from keyword setup and relevance tuning through AI intent tagging, webhook integration, and alert configuration.
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated platform knowledge.
Ask the user:
-
What area of SnitchFeed do you need help with?
- A) Keyword setup — listeners, keyword-level relevance context, exclusions
- B) AI filtering — relevance scoring, intent tagging, sentiment accuracy
- C) Alerts — Slack, Discord, email, webhook configuration
- D) Integrations — HubSpot, Instantly, Google Sheets, Clay, Apollo
- E) Billing — Starter vs Pro vs Custom differences
- F) Something else — describe it
-
What's your goal? (describe your specific question or problem)
If the user's request already provides most of this context, skip directly to Step 2. Lead with your best-effort answer using reasonable assumptions (stated explicitly), then ask only the most critical 1-2 clarifying questions at the end.
Step 2 — Route or answer directly
If the request maps to a specialized skill, route:
- Social listening strategy or tool comparison →
/sales-social-listening [question] - Reddit-specific monitoring (depth over breadth) →
/sales-threadlytics [question]or/sales-syften [question] - Buyer intent signals and prioritization →
/sales-intent [question] - Contact enrichment via Apollo or Clay →
/sales-enrich [question]
Otherwise, answer directly from the platform reference below.
Step 3 — SnitchFeed platform reference
Read references/platform-guide.md for the full platform reference — capabilities, pricing, data model, integration patterns, and webhook setup.
Answer the user's question using only the relevant section. Don't dump the full reference.
Step 4 — Actionable guidance
You no longer need the platform guide — focus on the user's specific situation.
- Keyword strategy — use natural language intent descriptions per keyword; SnitchFeed reads posts in full context, so describe what you're looking for (e.g., "people looking for a CRM alternative")
- Relevance tuning — upvote/downvote mentions to train the AI filter per keyword; specificity reduces noise
- Platform prioritization — Reddit and X are the strongest channels; LinkedIn and Bluesky are supplementary
- Alert routing — use Slack or Discord for real-time team notifications; use webhooks for CRM/pipeline automation
- Enrichment workflow — export CSV or use webhooks → Clay/Apollo for contact enrichment → HubSpot/Instantly for outreach
If you discover a gotcha, workaround, or tip not covered in references/learnings.md, append it there.
Gotchas
Best-effort from research — review these, especially items about plan-gated features and integration gotchas that may be outdated.
- Webhooks and AI tagging are Pro-only ($99/mo). Starter ($45/mo) gets email, Slack, and Discord alerts but no webhook automation and no automated intent tags. Budget for Pro if CRM integration matters.
- No public REST API. SnitchFeed has outbound webhooks but no inbound API — you can't query mentions programmatically. Export via CSV or webhook push only.
- Keyword-level relevance context is the key differentiator. Each keyword gets its own AI filtering context — describe what you're looking for in plain English per keyword, not just the keyword itself. Generic keywords without context produce noisy results.
- Mention caps are hard limits. Starter caps at 3,000 mentions/mo, Pro at 20,000. Broad keywords on high-volume platforms can burn through caps quickly.
- LinkedIn monitoring is not yet available. Despite being listed on the homepage, LinkedIn and some platforms may still be rolling out. Verify current platform coverage in your dashboard.
- Pricing discrepancy across pages. Blog posts reference $24-36/mo while the pricing page shows $45/mo Starter. The pricing page is authoritative — blog posts may reflect old or promotional rates.
Related skills
/sales-social-listening— Social listening strategy — monitoring setup, tool comparison, sentiment analysis, competitive intelligence, crisis detection/sales-octolens— Octolens — developer-first social listening with MCP server, REST API, webhooks on all plans/sales-syften— Syften — AI-filtered keyword monitoring across 15+ platforms, sub-minute alerts, REST API, webhooks/sales-catchintent— CatchIntent — AI intent detection across Reddit, X, HN, Bluesky with CRM integrations, MCP server, webhooks/sales-kwatch— KWatch.io — budget multi-platform monitoring including LinkedIn, AI sentiment, webhooks/sales-do— Not sure which skill to use? The router matches any sales objective to the right skill. Install:npx skills add sales-skills/sales --skill sales-do
Examples
Example 1: Set up monitoring for a B2B SaaS product
User says: "I sell a project management tool and want to find people on Reddit and Twitter looking for alternatives to Asana" Skill does:
- Creates listeners with keywords: "alternative to Asana", "looking for PM tool", "Asana frustrating"
- Adds keyword-level relevance context: "People looking to switch project management tools for small teams"
- Configures Slack alerts for real-time team notifications
- Recommends starting with 3-5 high-intent keywords and expanding after reviewing AI scoring accuracy Result: Multi-platform monitoring with intent-focused keywords and Slack alerts
Example 2: Push SnitchFeed leads to CRM via webhooks
User says: "How do I get SnitchFeed mentions into HubSpot automatically?" Skill does:
- Confirms user is on Pro plan (webhooks are Pro-only at $99/mo)
- Walks through webhook setup: configure endpoint URL in SnitchFeed dashboard
- Suggests using Zapier or Make as middleware between webhook and HubSpot
- Notes native HubSpot integration is also available — check if it covers the user's use case Result: Automated pipeline from SnitchFeed mentions to HubSpot contacts
Example 3: Reduce noise in mention feed
User says: "Most of the mentions SnitchFeed shows me aren't relevant to my product" Skill does:
- Reviews current keyword-level relevance context for specificity
- Recommends rewriting context in plain English describing the ideal mention
- Uses upvote/downvote feedback on mentions to train the AI filter
- Suggests narrowing to specific subreddits or platform filters if available Result: Refined keyword context producing higher-relevance mentions
Troubleshooting
Mentions are mostly irrelevant noise
Symptom: High volume of mentions but most don't match your product or audience Cause: Keyword-level relevance context is too generic or missing Solution: For each keyword, add a descriptive context explaining what you're looking for in plain English. Instead of just "CRM", add context like "People asking for recommendations for a lightweight CRM for small B2B teams." Upvote relevant mentions and downvote irrelevant ones to train the AI. Remove overly broad single-word keywords.
Webhook notifications not arriving
Symptom: Configured a webhook endpoint but no payloads are being received Cause: Webhook is Pro-only ($99/mo), endpoint URL may be incorrect, or endpoint isn't returning 200 OK Solution: Verify you're on the Pro plan. Check the webhook URL is correct and publicly accessible. Ensure your endpoint returns HTTP 200 within a reasonable timeout. Test with a webhook debugging service (e.g., webhook.site) first. Check if SnitchFeed has a webhook log or test button in the dashboard.
AI intent tags seem wrong
Symptom: Mentions tagged as "Buy Intent" are actually casual discussions, or real buying signals are tagged as "Industry Insights" Cause: AI tagging works best with specific keywords and clear relevance context Solution: Review your keyword context — vague descriptions lead to poor tagging. Upvote/downvote mentions to provide feedback. Focus on the mentions with highest relevance scores first. Note that AI tagging requires Pro plan — Starter only gets basic relevance filtering without intent categories.