brand-monitor: Workflow Automation for AI Agents | OpenAgentSkill

Overview

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".

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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.

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

Param	Type	Description
`query`	string	Brand name or phrase to search
`limit`	int	Number of results (default 20, max 100)
`offset`	int	Pagination offset
`sort`	string	`relevance` or `date`
`from_date`	string	Start date (YYYY-MM-DD)
`to_date`	string	End date (YYYY-MM-DD)

Example curl

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

Response Parsing

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

Param	Type	Description
`domain`	string	Company domain (e.g., `stripe.com`)
`name`	string	Brand name (alternative to domain)

Example curl

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

Param	Type	Description
`brand`	string	Brand name to search for
`domain`	string	Filter to specific domain
`limit`	int	Number of results

Example curl

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

{
  "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

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

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

Get Monitor Results

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

Param	Type	Description
`query`	string	Brand name
`from_date`	string	Start date
`to_date`	string	End date
`granularity`	string	`day`, `week`, or `month`

Example curl

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

Search mentions for your brand and each competitor
Compare mention counts over the same time period
Compare sentiment distributions
Identify sources where competitors get mentioned but you do not

# 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

Status	Meaning
401	Invalid or expired API key
403	Insufficient permissions for this endpoint
404	Resource not found (check monitor ID)
429	Rate limit exceeded - wait and retry
500	Server 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

View source ↗

File metadata

name: brand-monitor
description: >
  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".

View original text

---
name: brand-monitor
description: >
  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".
---

# 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

| Param | Type | Description |
|-------|------|-------------|
| `query` | string | Brand name or phrase to search |
| `limit` | int | Number of results (default 20, max 100) |
| `offset` | int | Pagination offset |
| `sort` | string | `relevance` or `date` |
| `from_date` | string | Start date (YYYY-MM-DD) |
| `to_date` | string | End 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

| Param | Type | Description |
|-------|------|-------------|
| `domain` | string | Company domain (e.g., `stripe.com`) |
| `name` | string | Brand 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

| Param | Type | Description |
|-------|------|-------------|
| `brand` | string | Brand name to search for |
| `domain` | string | Filter to specific domain |
| `limit` | int | Number 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

| Param | Type | Description |
|-------|------|-------------|
| `query` | string | Brand name |
| `from_date` | string | Start date |
| `to_date` | string | End date |
| `granularity` | string | `day`, `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

| Status | Meaning |
|--------|---------|
| 401 | Invalid or expired API key |
| 403 | Insufficient permissions for this endpoint |
| 404 | Resource not found (check monitor ID) |
| 429 | Rate limit exceeded - wait and retry |
| 500 | Server 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

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Sentiment analysis section appears incomplete in the provided excerpt (missing to_date parameter description).
No explicit error handling or rate limit guidance for the Brand.dev API.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Open full audit

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Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
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3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Source & usage notes

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: OpenClaudia/openclaudia-skills
License: MIT
Version: 1.0.0
Last GitHub push: Aug 25, 2026
Registry updated: Sep 5, 2026
Instruction path: skills/brand-monitor/SKILL.md @ 221b37d7ab95

Version reported in registry metadata; check source releases before relying on it.

Quality

75/100

Strong

Trust

60/100

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "automation",
      "agent-skill"
    ],
    "known_risks": [
      "Sentiment analysis section appears incomplete in the provided excerpt (missing to_date parameter description).",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 78,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Sentiment analysis section appears incomplete in the provided excerpt (missing to_date parameter description).",
      "No explicit error handling or rate limit guidance for the Brand.dev API.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 75,
    "label": "Strong"
  },
  "supply": {
    "track": "Design and creative production",
    "scenario": "Multimodal media",
    "maintenance": "22d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Sentiment analysis section appears incomplete in the provided excerpt (missing to_date parameter description).",
    "No OpenAgentSkill engagement data yet",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "No explicit error handling or rate limit guidance for the Brand.dev API."
  ],
  "agent_contract": {
    "task_input": "Use brand-monitor in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 68/100 Manual review",
      "Audit: 78/100 Needs review",
      "Safety: 34/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "openclaudia-brand-monitor (brand-monitor)",
      "install_command": "npx skills add OpenClaudia/openclaudia-skills --skill brand-monitor",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "openclaudia-brand-monitor",
      "task": "Use brand-monitor in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/openclaudia-brand-monitor",
    "api": "https://www.openagentskill.com/api/agent/skills/openclaudia-brand-monitor",
    "audit": "https://www.openagentskill.com/skills/openclaudia-brand-monitor/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=openclaudia-brand-monitor&task=Use%20brand-monitor%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20brand-monitor%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20brand-monitor%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/openclaudia-brand-monitor/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/openclaudia-brand-monitor"
  }
}

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Creator: OpenClaudia
Source: OpenClaudia/openclaudia-skills
Indexed by: OpenAgentSkill community index

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Overview

Brand Monitor

Prerequisites

API Base

1. Brand Search

Endpoint

Parameters

Example curl

Response Parsing

2. Brand Info Lookup

Endpoint

Parameters

Example curl

Response Fields

3. Logo Detection

Endpoint

Parameters

Example curl

4. Mention Tracking

Create a Monitor

Body

Example curl

List Monitors

Get Monitor Results

5. Sentiment Analysis

Endpoint

Parameters

Example curl

Sentiment Scores

6. Competitor Mention Comparison

Workflow

Workflow: Full Brand Audit

Step 1: Brand Info

Step 2: Mention Volume

Step 3: Sentiment Analysis

Step 4: PR Opportunities

Step 5: Logo/Visual Presence

Step 6: Report

Error Handling

Tips

Review the source

Start with one small task

Source & usage notes

Agent access

Related skills

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