Install the Video Transcript Downloader as a skill (configured in ClawHub), provide authentication (OAuth or API key) and a secure webhook/REST endpoint that the OpenClaw agent calls to start a download job, run the actual transcript extraction outside the agent (a small web service or worker that uses a provider API or tools like yt-dlp), persist results in external storage, and return status/result URLs to the agent. Keep credentials and long-running or stateful work out of the agent runtime, validate all incoming requests, and debug by inspecting request/response logs, token scopes, and service logs.

 

Overview  

 

• What runs where: The OpenClaw agent invokes a skill endpoint (short-lived HTTP) to request a transcript. The heavy lifting—downloading video, running transcription, and storing transcripts—runs in an external service (web server + workers + storage).
• Authentication: Configure OAuth or API key in your skill configuration (ClawHub). The external service validates the invocation (shared secret, signed header, or bearer token). Third-party video providers use their own OAuth/API keys.
• Reliability: Use a queue for long jobs, durable storage (S3, database), and background workers. Do not rely on the agent runtime for long-running tasks or persistent storage.

 

Prerequisites  

 

• ClawHub access to register/install the skill (skill name, webhook URL, secrets).
• An HTTP endpoint you control (public or via tunneling for development) to accept skill calls.
• Credentials for the video provider or tools you’ll use (OAuth client_id/client_secret or API key). For direct downloads you can run yt-dlp on your server.
• Storage for transcripts (S3, GCS, database) and optional transcript search/indexing.

 

High-level integration steps  

 

• 1. Build an external service (webhook) that exposes a POST /transcript-start endpoint. The OpenClaw agent will call this to start a job.
• 2. Secure the endpoint with a verification mechanism (shared secret or bearer token). Store that secret in ClawHub skill configuration and in your service env.
• 3. Implement job processing by either invoking the video provider’s transcription API or running a downloader + local or remote transcription (e.g., yt-dlp to extract subtitles or audio, then AssemblyAI/Whisper for transcription).
• 4. Persist outputs and return a stable result URL or job ID to the agent. Use an asynchronous flow: accept the request, enqueue work, respond 202 with job\_id, and later send a callback or let the agent poll a /transcript-status endpoint.
• 5. Register the skill in ClawHub (point it at your /transcript-start endpoint, supply verification secrets and any OAuth redirect if your skill needs to sign into external accounts).

 

Example architecture (practical)

 

• Skill webhook (HTTPS) — accepts requests from OpenClaw
• Lightweight web service — validates request, enqueues job
• Worker(s) — run yt-dlp or call provider transcripts, save SRT/JSON to object storage
• Object storage (S3) + DB for job metadata
• Optional callback endpoint the agent can receive, or provide a status URL the agent can poll

 

Secure webhook: recommended checks  

 

• Require Authorization: Bearer <token> or a custom HMAC signature header that your service validates.
• Rotate tokens and least-privilege for any provider credentials.
• Validate payload shape and origin IP ranges if the agent platform publishes them (if not published, rely on signed tokens).

 

Node.js example: webhook + yt-dlp + upload to S3  

 

This is a minimal, realistic example. It assumes yt-dlp is installed on the host and reachable via PATH, and AWS credentials are configured.

``` // Simple Express service that accepts a request from the agent to start a transcript job const express = require('express'); const { execFile } = require('child_process'); const fs = require('fs'); const path = require('path'); const AWS = require('aws-sdk');

const S3_BUCKET = process.env.S3_BUCKET;
const PORT = process.env.PORT || 3000;
const VERIFY_TOKEN = process.env.SKILL_VERIFY_TOKEN; // shared secret configured in ClawHub
const YTDLP = process.env.YTDLP_PATH || 'yt-dlp';

const s3 = new AWS.S3();

const app = express();
app.use(express.json());

// // POST /transcript-start - invoked by OpenClaw agent
app.post('/transcript-start', async (req, res) => {
const auth = req.get('Authorization') || '';
if (auth !== Bearer ${VERIFY_TOKEN}) {
return res.status(401).json({ error: 'unauthorized' });
}

const { video_url, job_id } = req.body || {};
if (!video_url || !job_id) {
return res.status(400).json({ error: 'missing video_url or job_id' });
}

// // Enqueue job: here we run immediately (for demo). For production, push to a queue.
processTranscriptJob({ video_url, job_id })
.then((result) => {
// // Respond with a job accepted payload
res.status(202).json({ job_id, status: 'accepted', result_url: result.s3_url });
})
.catch((err) => {
console.error('job error', err);
res.status(500).json({ error: 'job failed to start' });
});
});

async function processTranscriptJob({ video_url, job_id }) {
return new Promise((resolve, reject) => {
const outDir = path.join('/tmp', job_id);
fs.mkdirSync(outDir, { recursive: true });

// <b>//</b> Use yt-dlp to download subtitles (auto-generated if available). Adjust flags for exact needs.
const args = [
  '--skip-download',
  '--write-auto-sub',
  '--sub-lang', 'en',
  '--convert-subs', 'srt',
  '-o', path.join(outDir, '%(id)s.%(ext)s'),
  video_url
];

execFile(YTDLP, args, { timeout: 5 * 60 * 1000 }, async (err, stdout, stderr) => {
  if (err) {
    console.error('yt-dlp error', err, stderr);
    return reject(err);
  }

  // <b>//</b> Find produced .srt file
  const files = fs.readdirSync(outDir);
  const srt = files.find(f => f.endsWith('.srt'));
  if (!srt) {
    return reject(new Error('no subtitles produced'));
  }

  const filePath = path.join(outDir, srt);
  const s3Key = `transcripts/${job_id}/${srt}`;
  const fileStream = fs.createReadStream(filePath);

  try {
    // <b>//</b> Upload to S3
    await s3.upload({
      Bucket: S3_BUCKET,
      Key: s3Key,
      Body: fileStream,
      ContentType: 'text/plain'
    }).promise();

    const s3Url = `s3://${S3_BUCKET}/${s3Key}`;
    resolve({ s3_url: s3Url });
  } catch (uploadErr) {
    reject(uploadErr);
  } finally {
    // <b>//</b> Cleanup local files
    fs.rmSync(outDir, { recursive: true, force: true });
  }
});

});
}

app.listen(PORT, () => {
console.log(transcript service listening on ${PORT});
});

 
<h3>Explanation of the example &nbsp;</h3>
&nbsp;
<ul>
<li><b>Authentication</b>: The incoming call must include Authorization: Bearer &lt;VERIFY_TOKEN&gt;. This token is stored both in ClawHub skill config and as SKILL_VERIFY\_TOKEN in the service env. That avoids trusting network origin alone.</li>
<li><b>Work model</b>: The example runs the job synchronously for simplicity. In production, put the job into a durable queue (SQS, RabbitMQ, etc.) and have workers process it. Respond 202 Accepted immediately with job\_id.</li>
<li><b>Transcription options</b>: For hosted providers that expose transcripts via API (YouTube Data API, video platform APIs, or transcription services), replace the yt-dlp step with authenticated API calls. Those APIs will require their own credentials and scopes.</li>
<li><b>Storage</b>: We upload final transcripts to S3. Provide a secure, time-limited HTTP(S) URL back to the agent instead of an S3 URI if the agent needs to fetch content.</li>
</ul>

&nbsp;
<h3>OAuth flows (when the skill needs user access) &nbsp;</h3>
&nbsp;
<ul>
<li><b>Register your skill</b> with the third-party provider, add the skill's redirect URI (pointing to your web service), and request minimal scopes (read:captions or transcription scope). Store client_id and client_secret securely (ClawHub or your secret manager).</li>
<li><b>In ClawHub</b> you will typically configure the skill to request OAuth on installation. The agent flow should be: agent starts OAuth, provider redirects to your service, you exchange code for access/refresh tokens, store tokens in your DB keyed to the agent/account, and use the access token when calling provider APIs for transcripts.</li>
<li><b>Token refresh</b>: Implement refresh logic on the external service and do not rely on the agent to refresh. Track token expiry and refresh proactively.</li>
</ul>

&nbsp;
<h3>Status reporting and callbacks &nbsp;</h3>
&nbsp;
<ul>
<li>Return an immediate 202 with job_id and a status URL (e.g., /transcript-status/:job_id) so the agent can poll.</li>
<li>Or implement a callback endpoint the agent exposes and, once the job is done, POST back the result (signed with the agent’s verification token). Choose callback vs poll based on the agent’s capabilities and ClawHub configuration.</li>
</ul>

&nbsp;
<h3>Debugging checklist &nbsp;</h3>
&nbsp;
<ul>
<li>Check the agent call: capture the exact HTTP request (headers, body) sent to your webhook. Confirm Authorization header matches your VERIFY\_TOKEN.</li>
<li>Check your service logs: did the request arrive? Did the job enqueue? Did yt-dlp or the provider API return errors? Save raw provider responses for inspection.</li>
<li>Check provider API responses: invalid_grant, insufficient_scope, quota errors are common. Verify client_id/client_secret and token scopes.</li>
<li>Check storage permissions: S3 PutObject permission errors indicate IAM misconfiguration.</li>
<li>If OAuth is involved, capture the redirect and token exchange logs; confirm redirect URI matches registered value and the server clock is in sync (clock skew can break token validation).</li>
</ul>

&nbsp;
<h3>Operational recommendations &nbsp;</h3>
&nbsp;
<ul>
<li>Use a job queue for long-running work and autoscale workers based on queue depth.</li>
<li>Persist job metadata in a database (timestamps, status, provider\_id, S3 URL). Agents can poll that status endpoint.</li>
<li>Limit public access: serve transcript download links via short-lived signed URLs (pre-signed S3 URLs).</li>
<li>Log request IDs and job IDs end-to-end to correlate agent requests with worker logs.</li>
<li>Rate-limit and retry: implement idempotency keys for repeated agent invocations and retry/backoff for transient errors.</li>
</ul>

&nbsp;
<h3>What to avoid &nbsp;</h3>
&nbsp;
<ul>
<li>Do not store long-lived provider secrets inside the agent runtime. Keep them in your external service or secret manager.</li>
<li>Do not process heavy work (full video download + transcription) synchronously inside the agent’s process—move it to external workers.</li>
<li>Do not expose raw S3 or credentials to the agent; provide signed URLs or a secure proxy.</li>
</ul>

&nbsp;
<h3>Example of a minimal REST contract between the agent and your service &nbsp;</h3>
&nbsp;
<ul>
<li>POST /transcript-start
  <ul>
    <li>Headers: Authorization: Bearer &lt;SKILL\_TOKEN&gt;</li>
    <li>Body: { "job_id": "uuid", "video_url": "https://..." }</li>
    <li>Response: 202 { "job_id": "uuid", "status_url": "https://.../status/uuid" }</li>
  </ul>
</li>
<li>GET /status/:job\_id
  <ul>
    <li>Response: 200 { "job_id": "uuid", "status": "queued|running|done|failed", "result_url": "https://..." }</li>
  </ul>
</li>
</ul>

&nbsp;
<h3>Final notes &nbsp;</h3>
&nbsp;
<ul>
<li>Design the skill as a thin, authenticated bridge between OpenClaw and your transcript pipeline. Keep state and heavy lifting outside the agent runtime. Use proven tools (yt-dlp, provider APIs, transcription services) and standard secure patterns (OAuth, API keys, signed webhooks, presigned storage URLs). When something breaks, inspect HTTP request/response pairs, service logs, and provider responses to find the failure point.</li>
</ul>