Brand Monitor logo

Brand Monitor

Organization
OpenClaudia
brand-monitor

Brand monitoring and mention tracking via the Brand.dev API. Use when asked to monitor brand mentions, track sentiment, find PR opportunities, detect logo usage, or analyze brand presence online. Trigger phrases: "brand monitoring", "mention tracking", "brand sentiment", "PR opportunities", "logo detection", "brand.dev", "brand mentions", "media monitoring".

Overview

PublisherOpenClaudia
Repositoryopenclaudia-skills
Skill namebrand-monitor
Stars
714
Forks
60
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by OpenClaudia on GitHub. Read the source before you install it.

Installation

Install the Brand Monitor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/OpenClaudia/openclaudia-skills/tree/main/skills/brand-monitor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/OpenClaudia/openclaudia-skills.git /tmp/openclaudia-skills
mkdir -p .claude/skills
cp -r /tmp/openclaudia-skills/skills/brand-monitor .claude/skills/brand-monitor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Brand Monitor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Brand Monitor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Brand Monitor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Brand Monitor

Track brand mentions, analyze sentiment, and discover PR opportunities using the Brand.dev API.

Prerequisites

Requires BRANDDEV_API_KEY set in .env, .env.local, or ~/.claude/.env.global.

bash
echo "BRANDDEV_API_KEY is ${BRANDDEV_API_KEY:+set}"

If the key is not set, instruct the user:

You need a Brand.dev API key. Get one at https://brand.dev/ Then add BRANDDEV_API_KEY=your_key to your .env file.

API Base

All requests go to https://api.brand.dev/v1/ with the header Authorization: Bearer {BRANDDEV_API_KEY}.


1. Brand Search

Search for mentions of a brand name across the web.

Endpoint

GET https://api.brand.dev/v1/brand/search

Parameters

ParamTypeDescription
querystringBrand name or phrase to search
limitintNumber of results (default 20, max 100)
offsetintPagination offset
sortstringrelevance or date
from_datestringStart date (YYYY-MM-DD)
to_datestringEnd date (YYYY-MM-DD)

Example curl

bash
curl -s -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
  "https://api.brand.dev/v1/brand/search?query=YourBrand&limit=20&sort=date"

Response Parsing

bash
curl -s -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
  "https://api.brand.dev/v1/brand/search?query=YourBrand&limit=20" \
  | python3 -c "
import json, sys
data = json.load(sys.stdin)
for m in data.get('results', []):
    print(f\"Source: {m.get('source','')}  |  Title: {m.get('title','')}  |  Sentiment: {m.get('sentiment','n/a')}  |  Date: {m.get('published_at','')}\")
    print(f\"  URL: {m.get('url','')}\")
    print()
"

2. Brand Info Lookup

Get structured brand information for any company or product.

Endpoint

GET https://api.brand.dev/v1/brand/info

Parameters

ParamTypeDescription
domainstringCompany domain (e.g., stripe.com)
namestringBrand name (alternative to domain)

Example curl

bash
curl -s -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
  "https://api.brand.dev/v1/brand/info?domain=stripe.com"

Response Fields

  • name: Official brand name
  • domain: Primary domain
  • description: Brand description
  • industry: Industry classification
  • founded: Year founded
  • headquarters: Location
  • social_profiles: Links to social media
  • logos: Brand logo URLs
  • colors: Brand color palette
  • employees_range: Company size estimate

3. Logo Detection

Detect brand logos in images across the web.

Endpoint

GET https://api.brand.dev/v1/logo/search

Parameters

ParamTypeDescription
brandstringBrand name to search for
domainstringFilter to specific domain
limitintNumber of results

Example curl

bash
curl -s -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
  "https://api.brand.dev/v1/logo/search?brand=YourBrand&limit=20"

Use logo detection to find:

  • Unauthorized logo usage
  • Partner and sponsor visibility
  • Event coverage and media placements
  • Counterfeit product listings

4. Mention Tracking

Set up ongoing tracking for brand mentions.

Create a Monitor

POST https://api.brand.dev/v1/monitors

Body

json
{
  "name": "My Brand Monitor",
  "keywords": ["YourBrand", "Your Brand", "yourbrand.com"],
  "exclude_keywords": ["unrelated term"],
  "sources": ["news", "blogs", "social", "forums", "reviews"],
  "languages": ["en"],
  "notify_email": "alerts@yourdomain.com"
}

Example curl

bash
curl -s -X POST -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
  -H "Content-Type: application/json" \
  "https://api.brand.dev/v1/monitors" \
  -d '{
    "name": "Brand Alert",
    "keywords": ["YourBrand"],
    "sources": ["news", "blogs", "social"],
    "languages": ["en"]
  }'

List Monitors

bash
curl -s -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
  "https://api.brand.dev/v1/monitors"

Get Monitor Results

bash
curl -s -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
  "https://api.brand.dev/v1/monitors/{monitor_id}/mentions?limit=50&sort=date"

5. Sentiment Analysis

Analyze sentiment of brand mentions.

Endpoint

GET https://api.brand.dev/v1/brand/sentiment

Parameters

ParamTypeDescription
querystringBrand name
from_datestringStart date
to_datestringEnd date
granularitystringday, week, or month

Example curl

bash
curl -s -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
  "https://api.brand.dev/v1/brand/sentiment?query=YourBrand&from_date=2024-01-01&to_date=2024-03-31&granularity=week"

Sentiment Scores

  • Positive (> 0.3): Praise, recommendations, positive reviews
  • Neutral (-0.3 to 0.3): Factual mentions, news coverage
  • Negative (< -0.3): Complaints, criticism, negative reviews

6. Competitor Mention Comparison

Compare brand mention volume and sentiment against competitors.

Workflow

  1. Search mentions for your brand and each competitor
  2. Compare mention counts over the same time period
  3. Compare sentiment distributions
  4. Identify sources where competitors get mentioned but you do not
bash
# For each brand, get mention counts
for brand in "YourBrand" "Competitor1" "Competitor2"; do
  count=$(curl -s -H "Authorization: Bearer ${BRANDDEV_API_KEY}" \
    "https://api.brand.dev/v1/brand/search?query=${brand}&limit=1" \
    | python3 -c "import json,sys; print(json.load(sys.stdin).get('total',0))")
  echo "${brand}: ${count} mentions"
done

Workflow: Full Brand Audit

When asked for a comprehensive brand monitoring report:

Step 1: Brand Info

Pull structured brand data for context.

Step 2: Mention Volume

Search for brand mentions over the last 30/90 days. Count total mentions and break down by source type.

Step 3: Sentiment Analysis

Get sentiment trends. Flag any negative spikes and investigate root causes.

Step 4: PR Opportunities

From mention data, identify:

  • High-authority sites that mention competitors but not you
  • Journalists who cover your industry
  • Trending topics where your brand could contribute
  • Unanswered questions about your brand on forums

Step 5: Logo/Visual Presence

Search for logo appearances. Flag unauthorized usage.

Step 6: Report

Present findings as:

## Brand Monitoring Report: {Brand}

### Overview
- Total mentions (last 30 days): X
- Sentiment breakdown: X% positive, X% neutral, X% negative
- Top sources: ...

### Sentiment Trend
[Weekly trend data]

### Top Positive Mentions
1. [Source] - [Title] - [URL]
2. ...

### Negative Mentions Requiring Attention
1. [Source] - [Title] - [URL] - [Issue summary]
2. ...

### PR Opportunities
1. [Publication] covers [topic] - pitch angle: ...
2. [Journalist] recently wrote about [topic] - pitch angle: ...

### Competitor Comparison
| Metric | Your Brand | Competitor A | Competitor B |
|--------|-----------|-------------|-------------|
| Mentions | ... | ... | ... |
| Positive % | ... | ... | ... |
| Top Source | ... | ... | ... |

### Action Items
- [ ] Respond to [negative mention]
- [ ] Pitch [publication] about [topic]
- [ ] Update brand listing on [platform]

Error Handling

StatusMeaning
401Invalid or expired API key
403Insufficient permissions for this endpoint
404Resource not found (check monitor ID)
429Rate limit exceeded - wait and retry
500Server error - retry after a few seconds

Tips

  • Use exact brand name + common misspellings as keywords
  • Exclude your own domain to avoid self-mentions
  • Set up monitors for competitor brands too
  • Check mentions weekly at minimum; daily during launches or crises
  • Export negative mentions to a spreadsheet for customer support follow-up

Frequently asked questions

What does the Brand Monitor AI skill do?

Brand monitoring and mention tracking via the Brand.dev API. Use when asked to monitor brand mentions, track sentiment, find PR opportunities, detect logo usage, or analyze brand presence online. Trigger phrases: "brand monitoring", "mention tracking", "brand sentiment", "PR opportunities", "logo detection", "brand.dev", "brand mentions", "media monitoring".

Why use Brand Monitor on TypingMind?

Because you install it once and use it with any model. Brand Monitor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Brand Monitor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OpenClaudia/openclaudia-skills/tree/main/skills/brand-monitor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Brand Monitor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Brand Monitor?

As many as you like. As long as a model supports skills, you can use Brand Monitor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Brand Monitor AI skill free?

Yes. It is published on GitHub by OpenClaudia under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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