sales-mentiondrop

What this skill does

# MentionDrop Platform Help

## Step 1 — Gather context

If `references/learnings.md` exists, read it first for accumulated platform knowledge.

Ask the user:

1. **What do you need help with?**
   - A) Setting up keyword monitoring (choosing keywords, adding context)
   - B) Reducing noise / too many irrelevant mentions
   - C) Understanding AI summaries, sentiment, or relevance scores
   - D) Webhook or Slack integration setup
   - E) Using the API to pull mentions into another tool
   - F) Plan limits and upgrade decision
   - G) Something else — describe it

2. **Which plan are you on?**
   - A) Free (1 keyword)
   - B) Starter ($29/mo — 5 keywords)
   - C) Pro ($59/mo — 20 keywords)
   - D) Not sure / haven't signed up yet

3. **What's your goal?**
   - A) Brand monitoring (track what people say about us)
   - B) Competitor monitoring (track competitor mentions)
   - C) Lead generation (find people asking for solutions like mine)
   - D) PR / crisis detection (catch negative mentions fast)

**If the user's request already provides context, skip to Step 2.**

## Step 2 — Route or answer directly

- Social listening strategy or tool comparison → `/sales-social-listening [question]`
- Developer-first monitoring with MCP + API on all plans → `/sales-octolens [question]`
- Free Reddit/HN monitoring with more keywords → `/sales-f5bot [question]`
- Multi-platform monitoring with AI filtering → `/sales-syften [question]`
- Audience intelligence (where audiences spend attention) → `/sales-sparktoro [question]`
- Reddit lead generation with intent scoring → `/sales-buska [question]`

Otherwise, answer directly from the platform reference below.

## Step 3 — MentionDrop platform reference

**Read `references/platform-guide.md`** for the full platform reference — capabilities, pricing, data model, API details, integration recipes, and workflow examples.

Answer the user's question using only the relevant section. Don't dump the full reference.

## Step 4 — Actionable guidance

Focus on the user's specific situation:

1. **Noise reduction** — add keyword context to help MentionDrop distinguish your brand from common words, use sentiment filters to focus on negative or positive mentions, adjust relevance scoring thresholds
2. **Keyword strategy** — use exact brand name, product names, and competitor names; add context descriptions so the AI understands what you mean by ambiguous terms
3. **Alert routing** — use Slack for real-time team awareness, webhooks for CRM/automation pipelines, email digests for daily review
4. **API integration** — the API is read-only; use it to pull processed mentions into dashboards or data pipelines; filter by keyword, sentiment, content_type, and date range
5. **Plan selection** — Free is fine for testing; $29/mo covers most solo founders (5 keywords); $59/mo for teams monitoring multiple brands/competitors

If you discover a gotcha 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 pricing that may change.*

- **API is read-only.** You can pull mentions but can't create keywords or manage settings via API. Use the dashboard for configuration.
- **Free plan is extremely limited.** Only 1 keyword — useful for testing but not for real monitoring. Upgrade to $29/mo for 5 keywords.
- **Keyword context is critical for noise reduction.** MentionDrop uses AI to filter relevance, but ambiguous brand names (e.g., "Mercury", "Notion") need explicit context like "Mercury is a banking app for startups" to avoid false positives.
- **Web monitoring depends on Ahrefs Firehose.** Coverage is broad but not exhaustive — niche forums or gated communities may not appear. Reddit coverage is direct.
- **Webhook payload format is not fully documented.** Test with webhook.site first to see the actual payload structure before building integrations.
- **No native Zapier/Make app.** Use webhooks to trigger Zapier/Make/n8n workflows. For iPaaS-native monitoring, consider Brand24 or Octolens.
- **Detection time averages ~4 minutes.** Faster than Google Alerts (2-3 days) but not truly real-time. For sub-minute alerts, consider Syften or Octolens.
- **No historical data backfill.** Monitoring starts from when you add a keyword — no retroactive mention discovery.

## Related skills

- `/sales-social-listening` — Social listening strategy across all platforms — tool comparison, monitoring setup, competitive intel, crisis detection
- `/sales-octolens` — Octolens — developer-first social listening with API/MCP on all plans from $25/mo
- `/sales-f5bot` — F5Bot — free Reddit/HN/Lobsters keyword monitoring with 200 free keywords
- `/sales-syften` — Syften — AI-filtered keyword monitoring across Reddit, HN, X, Bluesky, GitHub, sub-minute alerts
- `/sales-buska` — Buska — AI social listening for lead gen across 30+ platforms, intent scoring, MCP server
- `/sales-brand24` — Brand24 — affordable social listening with Storm Alerts and MCP server
- `/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 brand monitoring for a SaaS product
**User says**: "I just launched a project management tool called TaskFlow and want to know when people mention it online"
**Skill does**:
1. Reads platform guide for keyword setup and context configuration
2. Creates keyword "TaskFlow" with context: "TaskFlow is a project management SaaS tool for remote teams"
3. Adds competitor keywords: "Asana", "Monday.com", "ClickUp" for competitive monitoring
4. Configures Slack for real-time alerts and email for daily digests
5. Recommends $29/mo plan for 5 keywords covering brand + top competitors
**Result**: Brand monitoring live within minutes, AI-summarized alerts with sentiment

### Example 2: Pull MentionDrop mentions into a dashboard via API
**User says**: "How do I get my MentionDrop mentions into a Google Sheet or dashboard?"
**Skill does**:
1. Reads API reference for authentication and endpoint details
2. Shows how to create an API key in the dashboard Settings
3. Provides cURL example: `GET /api/v1/mentions?sentiment=negative&limit=50`
4. Builds a Python script to fetch mentions and write to Google Sheets via gspread
5. Sets up a cron job or n8n workflow to run the script hourly
**Result**: Automated pipeline from MentionDrop mentions to spreadsheet dashboard

### Example 3: Too many irrelevant mentions
**User says**: "I'm monitoring 'Mercury' but getting tons of mentions about the planet and the car brand"
**Skill does**:
1. Explains keyword context feature — add a description like "Mercury is a banking platform for startups"
2. Recommends using sentiment filter to focus on relevant business mentions
3. Suggests adding more specific keywords: "Mercury banking", "Mercury startup bank"
4. Notes that the AI relevance scoring should deprioritize off-topic mentions over time
**Result**: Cleaner mention feed focused on the actual brand

## Troubleshooting

### Mentions arriving late or missing
**Symptom**: You see a Reddit post about your brand but MentionDrop didn't catch it, or it appeared hours later
**Cause**: Average detection time is ~4 minutes for indexed sources, but niche forums or low-traffic subreddits may take longer. Some web sources depend on Ahrefs Firehose crawl frequency.
**Solution**: Check if the source is within MentionDrop's coverage (web via Ahrefs + Reddit). For niche forums, consider adding ForumScout or Syften as supplementary monitoring. For Reddit-specific speed, Syften offers sub-minute alerts.

### Webhook not delivering payloads
**Symptom**: Webhook URL is configured but your endpoint never receives data
**Cause**: Endpoint may be returning non-2xx status, URL may be incorrect, or no new mentions match your filters
**Solution**: Test with webhook.site first to verify MentionDrop sends payloads. Check tha