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Turn sourced brand mentions into a verified, deduplicated view of reputation signals, customer needs, and response priorities.
$9.99
Brand Mention Radar
Example session with this skill installed
Review this supplied listening export for the last 14 days for Northstar Bikes. Identify relevant mentions, remove duplicates, separate lookalike-name false positives, summarize recurring praise and complaints, flag urgent reputation or support issues, and recommend responses and next monitoring queries. Do not claim this file represents all public conversation or invent reach, sentiment, sources, or trends.
- Read your context and instructions
- Compiled the brand mention radar
Northstar Bikes Mention Review — 14-Day Export
Coverage: User-supplied export only. This is not a complete view of public conversation. No live monitoring or reach data was provided. Mentions below should retain the source URL, timestamp, channel, and exact text in the working log.
Triage method
- Confirm each result refers to Northstar Bikes using product, location, and context; quarantine name-only matches.
- Deduplicate repeated URLs or copied text while retaining repost counts only when the export provides them.
- Label observation, interpretation, and confidence separately. Do not infer intent from a keyword alone.
- Prioritize safety, unresolved customer harm, press inquiries, and rapidly spreading misinformation for human review.
Summary
The supplied sample includes three relevant conversations after removing one apparent lookalike-name result and one duplicate URL. Two discuss delivery delays; one praises the repair guide. These are sample-level counts only, not market-wide totals. The dataset is too small to establish a sentiment trend, representative customer view, or change versus prior periods.
| Signal | Evidence in supplied sample | Priority | Suggested action |
|---|---|---|---|
| Delivery timing | Two distinct posts describe a delayed order; verify order details privately before responding | High | Support team to acknowledge publicly without exposing customer information, then move case to a private channel |
| Repair guidance | One post thanks the brand for a clear setup/repair guide | Medium | Thank the author; ask permission before reusing as a testimonial |
| Lookalike mention | One result refers to a different organization with a similar name | Exclude | Mark as false positive and refine query with product/location terms |
Response guidance
For the delivery issue, use a human-approved reply such as: “Sorry this has taken longer than expected. Please message our support team with your order reference so we can check the status.” Do not request private order information publicly or promise a resolution before verifying.
Next monitoring queries
Combine the exact brand name with product names, common misspellings, delivery terms, repair terms, and relevant locations. Review each result for entity fit. Keep a dated baseline and compare only equivalent channels and time windows. Escalate safety allegations or sensitive personal details through the established internal process; do not republish private information.
Limit: All observations above are illustrative summaries of the described export scenario. Confirm each record against the actual source before acting. No comprehensive monitoring, trend, reach, or sentiment claim is implied.
Connects securely to your tools. The creator never sees your data.
About this skill
Brand Mention Radar
Discover and interpret conversations about a brand, product, executive, campaign, competitor, or topic. Move beyond mention counts to explain what people are discussing, how relevant each result is, which signals need attention, and what to monitor next.
What it delivers
- A source-linked mention log with entity checks and deduplication
- Relevant themes, questions, praise, complaints, and potential opportunities
- Cautious trend and sentiment observations with evidence limits
- Response and escalation priorities based on impact and urgency
- Channel, market, language, and product comparisons when data supports them
- A repeatable monitoring query and reporting plan
Use only observable data. Separate verified posts from interpretation, label date ranges and coverage gaps, and preserve links or source references. Never invent counts, sentiment, reach, engagement, trending status, sources, or historical data. If live browsing or monitoring access is unavailable, say so and provide a query plan or analyze user-provided exports instead.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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