octolensQuery and analyze brand mentions from Octolens API. Use when the user wants to fetch mentions, track keywords, filter by source platforms (Twitter, Reddit, GitHub, LinkedIn, etc.), sentiment analysis, or analyze social media engagement. Supports complex filtering with AND/OR logic, date ranges, follower counts, and bookmarks.
Install via ClawdBot CLI:
clawdbot install garrrikkotua/octolensUse this skill when the user needs to:
The Octolens API requires a Bearer token for authentication. The user should provide their API key, which you'll use in the Authorization header:
Authorization: Bearer YOUR_API_KEY
Important: Always ask the user for their API key before making any API calls. Store it in a variable for subsequent requests.
All API endpoints use the base URL: https://app.octolens.com/api/v1
X-RateLimit-* headers indicate current usageFetch mentions matching keywords with optional filtering. Returns posts sorted by timestamp (newest first).
Key Parameters:
limit (number, 1-100): Maximum results to return (default: 20)cursor (string): Pagination cursor from previous responseincludeAll (boolean): Include low-relevance posts (default: false)view (number): View ID to use for filteringfilters (object): Filter criteria (see filtering section)Example Response:
{
"data": [
{
"id": "abc123",
"url": "https://twitter.com/user/status/123",
"body": "Just discovered @YourProduct - this is exactly what I needed!",
"source": "twitter",
"timestamp": "2024-01-15T10:30:00Z",
"author": "user123",
"authorName": "John Doe",
"authorFollowers": 5420,
"relevance": "relevant",
"sentiment": "positive",
"language": "en",
"tags": ["feature-request"],
"keywords": [{ "id": 1, "keyword": "YourProduct" }],
"bookmarked": false,
"engaged": false
}
],
"cursor": "eyJsYXN0SWQiOiAiYWJjMTIzIn0="
}
List all keywords configured for the organization.
Example Response:
{
"data": [
{
"id": 1,
"keyword": "YourProduct",
"platforms": ["twitter", "reddit", "github"],
"color": "#6366f1",
"paused": false,
"context": "Our main product name"
}
]
}
List all saved views (pre-configured filters).
Example Response:
{
"data": [
{
"id": 1,
"name": "High Priority",
"icon": "star",
"filters": {
"sentiment": ["positive", "negative"],
"source": ["twitter"]
},
"createdAt": "2024-01-01T00:00:00Z"
}
]
}
The /mentions endpoint supports powerful filtering with two modes:
Put fields directly in filters. All conditions are ANDed together.
{
"filters": {
"source": ["twitter", "linkedin"],
"sentiment": ["positive"],
"minXFollowers": 1000
}
}
ā source IN (twitter, linkedin) AND sentiment = positive AND followers ā„ 1000
Prefix any array field with ! to exclude values:
{
"filters": {
"source": ["twitter"],
"!keyword": [5, 6]
}
}
ā source = twitter AND keyword NOT IN (5, 6)
Use operator and groups for complex logic:
{
"filters": {
"operator": "AND",
"groups": [
{
"operator": "OR",
"conditions": [
{ "source": ["twitter"] },
{ "source": ["linkedin"] }
]
},
{
"operator": "AND",
"conditions": [
{ "sentiment": ["positive"] },
{ "!tag": ["spam"] }
]
}
]
}
}
ā (source = twitter OR source = linkedin) AND (sentiment = positive AND tag ā spam)
| Field | Type | Description |
|-------|------|-------------|
| source | string[] | Platforms: twitter, reddit, github, linkedin, youtube, hackernews, devto, stackoverflow, bluesky, newsletter, podcast |
| sentiment | string[] | Values: positive, neutral, negative |
| keyword | string[] | Keyword IDs (get from /keywords endpoint) |
| language | string[] | ISO 639-1 codes: en, es, fr, de, pt, it, nl, ja, ko, zh |
| tag | string[] | Tag names |
| bookmarked | boolean | Filter bookmarked (true) or non-bookmarked (false) posts |
| engaged | boolean | Filter engaged (true) or non-engaged (false) posts |
| minXFollowers | number | Minimum Twitter follower count |
| maxXFollowers | number | Maximum Twitter follower count |
| startDate | string | ISO 8601 format (e.g., "2024-01-15T00:00:00Z") |
| endDate | string | ISO 8601 format |
This skill includes helper scripts for common operations. Use them to quickly interact with the API:
node scripts/fetch-mentions.js YOUR_API_KEY [limit] [includeAll]
node scripts/list-keywords.js YOUR_API_KEY
node scripts/list-views.js YOUR_API_KEY
node scripts/query-mentions.js YOUR_API_KEY '{"source": ["twitter"], "sentiment": ["positive"]}' [limit]
node scripts/advanced-query.js YOUR_API_KEY [limit]
X-RateLimit-*)/keywords endpoint before filtering by keyword{
"limit": 20,
"filters": {
"source": ["twitter"],
"sentiment": ["positive"],
"minXFollowers": 1000
}
}
{
"limit": 50,
"filters": {
"source": ["reddit", "github"],
"!tag": ["spam", "irrelevant"]
}
}
{
"limit": 30,
"filters": {
"operator": "AND",
"groups": [
{
"operator": "OR",
"conditions": [
{ "source": ["twitter"] },
{ "source": ["linkedin"] }
]
},
{
"operator": "AND",
"conditions": [
{ "sentiment": ["positive"] },
{ "startDate": "2024-01-20T00:00:00Z" }
]
}
]
}
}
| Status | Error | Description |
|--------|-------|-------------|
| 401 | unauthorized | Missing or invalid API key |
| 403 | forbidden | Valid key but no permission |
| 404 | not_found | Resource (e.g., view ID) not found |
| 429 | rate_limit_exceeded | Too many requests |
| 400 | invalid_request | Malformed request body |
| 500 | internal_error | Server error, retry later |
When a user asks to query Octolens data:
User: "Show me positive mentions from Twitter in the last 7 days"
Action (using bundled script):
node scripts/query-mentions.js YOUR_API_KEY '{"source": ["twitter"], "sentiment": ["positive"], "startDate": "2024-01-20T00:00:00Z"}'
Alternative (using fetch API directly):
const response = await fetch('https://app.octolens.com/api/v1/mentions', {
method: 'POST',
headers: {
'Authorization': `Bearer ${API_KEY}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
limit: 20,
filters: {
source: ['twitter'],
sentiment: ['positive'],
startDate: '2024-01-20T00:00:00Z',
},
}),
});
const data = await response.json();
User: "Find mentions from Reddit or GitHub, exclude spam tag, with positive or neutral sentiment"
Action (using bundled script):
node scripts/query-mentions.js YOUR_API_KEY '{"operator": "AND", "groups": [{"operator": "OR", "conditions": [{"source": ["reddit"]}, {"source": ["github"]}]}, {"operator": "OR", "conditions": [{"sentiment": ["positive"]}, {"sentiment": ["neutral"]}]}, {"operator": "AND", "conditions": [{"!tag": ["spam"]}]}]}'
Alternative (using fetch API directly):
const response = await fetch('https://app.octolens.com/api/v1/mentions', {
method: 'POST',
headers: {
'Authorization': `Bearer ${API_KEY}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
limit: 30,
filters: {
operator: 'AND',
groups: [
{
operator: 'OR',
conditions: [
{ source: ['reddit'] },
{ source: ['github'] },
],
},
{
operator: 'OR',
conditions: [
{ sentiment: ['positive'] },
{ sentiment: ['neutral'] },
],
},
{
operator: 'AND',
conditions: [
{ '!tag': ['spam'] },
],
},
],
},
}),
});
const data = await response.json();
User: "Show mentions for our main product keyword"
Actions:
node scripts/list-keywords.js YOUR_API_KEY
node scripts/query-mentions.js YOUR_API_KEY '{"keyword": [1]}'
Generated Mar 1, 2026
A marketing team tracks mentions of their brand across social media to gauge public sentiment and respond to customer feedback. They filter by positive and negative sentiment on Twitter and LinkedIn, focusing on posts with high follower counts to prioritize influential voices. This helps them manage brand perception and address issues promptly.
A tech startup monitors mentions of competitors' products on platforms like GitHub and HackerNews to identify feature gaps and user pain points. They use complex filters to exclude spam and focus on recent posts with neutral or negative sentiment, enabling data-driven product development decisions.
A SaaS company uses Octolens to filter mentions by keywords related to bugs or feature requests on Reddit and StackOverflow. They analyze sentiment trends over specific date ranges to identify recurring issues and improve support documentation, enhancing customer satisfaction and reducing support tickets.
A media agency tracks engagement on YouTube and newsletters for specific topics or tags to measure content performance. They filter by high-engagement posts and positive sentiment to identify successful content formats, informing future editorial calendars and boosting audience growth.
A publicly traded company monitors mentions on LinkedIn and podcasts for financial news or analyst discussions. They use advanced filtering with AND/OR logic to exclude irrelevant sources and focus on posts with high follower counts, providing insights for investor communications and market positioning.
Octolens offers tiered subscription plans based on API request limits and advanced features like sentiment analysis or historical data access. Revenue is generated through monthly or annual fees from businesses needing continuous brand monitoring, with higher tiers for enterprises requiring more data and customization.
A free tier provides basic mention tracking with limited filters and lower rate limits, attracting small businesses or individual users. Premium upgrades unlock advanced filtering, higher request quotas, and priority support, driving conversion through value-added features for growing companies.
Octolens licenses its API and analytics dashboard to marketing or PR agencies as a white-label service. Agencies rebrand the tool for their clients, paying a flat fee or per-client usage, enabling them to offer sophisticated monitoring without developing in-house technology.
š¬ Integration Tip
Always prompt users for their API key before making requests and store it securely for reuse. Use the bundled scripts for quick testing and familiarize yourself with filter syntax to handle complex queries efficiently.
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