Octolens

What it does

When your agent uses it

• The user wants to fetch mentions
• Filter by source platforms (Twitter
• Sentiment analysis
• Analyze social media engagement

Example prompts

• “/octolens”

Requirements

• Node.js
• A credential in YOUR_API_KEY
• A credential in API_KEY
• Compatibility (from SKILL.md): Requires Node.js 18+ (for fetch API) and access to the internet
• Pre-approved tools (allowed-tools): Node, Read

Workflow steps

3 steps, taken from the step headings in SKILL.md.

1. 1POST /mentions
2. 2GET /keywords
3. 3GET /views

What it can do on your machine

Read from SKILL.md and the folder at commit b80cde2. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Node
  • Read

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 6 files in scripts/ (JavaScript), which the agent can run.

  Shell commands in SKILL.md call:

  • node

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • twitter.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • API_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Requires Node.js 18+ (for fetch API) and access to the internet

  From compatibility in the SKILL.md frontmatter.

Context cost

Octolens loads about 2.9k tokens when it runs, and up to ~9.5k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 843 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~84

When it runs · the whole SKILL.md, loaded when a task matches

~2.9k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~9.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from sundial-org/awesome-openclaw-skills at commit b80cde2, republished under its MIT licence (© sundial-org). 843 words, ~2,904 tokens.

name

octolens

description

Query 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.

allowed-tools

Node, Read

compatibility

Requires Node.js 18+ (for fetch API) and access to the internet

license

MIT

metadata.author

octolens

metadata.version

1.0

Authorization: Bearer YOUR_API_KEY

{
  "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="
}

{
  "data": [
    {
      "id": 1,
      "keyword": "YourProduct",
      "platforms": ["twitter", "reddit", "github"],
      "color": "#6366f1",
      "paused": false,
      "context": "Our main product name"
    }
  ]
}

{
  "data": [
    {
      "id": 1,
      "name": "High Priority",
      "icon": "star",
      "filters": {
        "sentiment": ["positive", "negative"],
        "source": ["twitter"]
      },
      "createdAt": "2024-01-01T00:00:00Z"
    }
  ]
}

{
  "filters": {
    "source": ["twitter", "linkedin"],
    "sentiment": ["positive"],
    "minXFollowers": 1000
  }
}

{
  "filters": {
    "source": ["twitter"],
    "!keyword": [5, 6]
  }
}

{
  "filters": {
    "operator": "AND",
    "groups": [
      {
        "operator": "OR",
        "conditions": [
          { "source": ["twitter"] },
          { "source": ["linkedin"] }
        ]
      },
      {
        "operator": "AND",
        "conditions": [
          { "sentiment": ["positive"] },
          { "!tag": ["spam"] }
        ]
      }
    ]
  }
}

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]

{
  "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" }
        ]
      }
    ]
  }
}

node scripts/query-mentions.js YOUR_API_KEY '{"source": ["twitter"], "sentiment": ["positive"], "startDate": "2024-01-20T00:00:00Z"}'

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();

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"]}]}]}'

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();

node scripts/list-keywords.js YOUR_API_KEY

node scripts/query-mentions.js YOUR_API_KEY '{"keyword": [1]}'

© sundial-org, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (scripts, references) in skills/octolens of sundial-org/awesome-openclaw-skills.

• SKILL.md
• references/EXAMPLES.md
• references/FILTERS.md
• scripts/README.md
• scripts/advanced-query.js
• scripts/fetch-mentions.js
• scripts/list-keywords.js
• scripts/list-views.js
• scripts/query-mentions.js

Open the folder on GitHubat commit b80cde2