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How to integrate Firecrawl Skills with OpenClaw

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How to integrate Firecrawl Skills with OpenClaw

 

Direct answer

To integrate Firecrawl Skills with OpenClaw, treat the Firecrawl Skill as an external service you register with OpenClaw’s skill registry, configure authentication (OAuth or API key) and webhooks, implement secure HTTP endpoints that the agent will call, and run any stateful or long-lived pieces (databases, schedulers, queues) outside the agent runtime. Configure the skill manifest or metadata in your OpenClaw management UI (ClawHub or similar), exchange and store credentials securely, validate inbound webhook signatures, and debug by inspecting logs, API responses, and credential scopes — everything explicit: no magic, only authenticated REST/GraphQL calls and properly provisioned secrets.

 

Overview and intent

  • This guide explains the concrete, vendor-neutral steps to connect a Firecrawl Skill (an external skill/service) to an OpenClaw agent runtime.
  • Focus areas: registration/installation, authentication, endpoint design, webhook handling, runtime invocation flow, security, observability, and where to host stateful components.
  • All integration points are explicit HTTP(S) API calls, OAuth flows, API keys, or signed webhooks — there is no undocumented “magic” channel.

 

Prerequisites

  • Access to your OpenClaw management UI or skill registry (your organization may call it ClawHub).
  • A Firecrawl Skill implementation reachable over HTTPS (publicly accessible or via secure tunnel for development).
  • Credentials for authentication: OAuth client ID/secret, API keys, or a service account/keypair as supported by Firecrawl and OpenClaw.
  • Server to host any stateful components (database, persistent queues, cron jobs) outside the agent runtime if needed.

 

High-level integration steps

  • Design the skill’s public API surface (endpoints the OpenClaw agent will call).
  • Decide authentication mode (OAuth 2.0 for delegated access, API key / service account for machine access).
  • Implement webhook endpoints and signing verification (for event-driven interactions from the platform to your skill).
  • Register the skill with OpenClaw via the skill registry/management UI, providing the manifest/metadata, authentication method, and webhook URLs.
  • Test end-to-end using a development agent and inspect logs, HTTP responses, and tokens.
  • Harden credentials, rotate secrets, enforce least privilege scopes, and instrument observability (metrics, logs, traces).

 

Skill manifest and registration (what to provide)

  • Skill name, description, and version.
  • Public base URL for the skill’s API (HTTPS required).
  • Authentication type and endpoints: OAuth authorization and token URLs if using delegated OAuth; or instructions to provision API keys/service accounts.
  • Webhook event URL(s) and the expected signature/verification method.
  • Permissions/scopes the skill requests (explain why each scope is needed).

 

Authentication patterns

  • OAuth 2.0 (recommended for user-delegated actions): OpenClaw or your runtime will direct the administrator/user to grant scopes to the skill. Implement a token exchange endpoint to accept authorization codes and store refresh/access tokens securely in your backend (not in the agent process unless you manage secure secrets there).
  • API key / service account (recommended for server-to-server): Generate a long-lived secret, store it encrypted in OpenClaw’s secret store or your own vault, and have the agent include it in an Authorization header when calling your API.
  • Signed webhooks: Sign events you send to the agent or to OpenClaw with an HMAC (SHA256) and share the small secret during registration; the receiver validates the signature on arrival.

 

Runtime invocation flow (what actually happens)

  • The agent executes a skill invocation by making an authenticated HTTPS request to the skill’s endpoint (REST or GraphQL). That request contains the input payload and context (user id, invocation id, etc.) as defined in the skill contract.
  • Your skill processes the request synchronously or enqueues work for async processing. If async, respond with a 202 and provide a follow-up mechanism (webhook callback or polling URL) so OpenClaw knows when the result is ready.
  • Any persistent data, long-running jobs, or scheduled tasks must be hosted outside the agent runtime in your own services.

 

Webhook handling and signature verification (example)

  • Always require HTTPS for webhook endpoints.
  • Have a shared secret used to compute an HMAC over the request body; the platform includes the signature header. On receipt, compute the HMAC and compare securely (constant-time compare).
  • Return 2xx for successful verification; respond with 4xx for bad signatures so the platform won’t treat the delivery as successful.

 

Example: webhook verification in Node.js (express)

const express = require('express');
const crypto = require('crypto');
const app = express();

// <b>//</b> Parse raw body for HMAC verification
app.use(express.json({
  verify: (req, res, buf) => {
    req.rawBody = buf; // <b>//</b> store raw buffer for signature check
  }
}));

const SHARED_SECRET = process.env.WEBHOOK_SECRET; // <b>//</b> set in environment or vault

app.post('/webhook', (req, res) => {
  const signature = req.get('x-signature'); // <b>//</b> platform-provided header
  const hmac = crypto.createHmac('sha256', SHARED_SECRET);
  hmac.update(req.rawBody);
  const expected = `sha256=${hmac.digest('hex')}`;

  // <b>//</b> constant-time compare
  const isValid = crypto.timingSafeEqual(Buffer.from(expected), Buffer.from(signature || ''));

  if (!isValid) {
    return res.status(401).send('invalid signature');
  }

  // <b>//</b> process event
  const event = req.body;
  console.log('Received webhook', event);
  res.status(200).send('ok');
});

app.listen(3000, () => console.log('webhook listening'));

 

Example: simple OAuth 2.0 token exchange (server-side)

# <b>//</b> Exchange authorization code for tokens (generic)
curl -X POST https://auth.example.com/oauth/token \
  -H "Content-Type: application/x-www-form-urlencoded" \
  -d "grant_type=authorization_code&code=AUTH_CODE&redirect_uri=https://your.skill/callback&client_id=CLIENT_ID&client_secret=CLIENT_SECRET"
// <b>//</b> Save tokens securely on your server (not in the agent process)
const tokens = await fetchTokenExchange(...);
await saveEncrypted(tokens); // <b>//</b> use your vault or encrypted DB

 

Example: agent calling your skill (generic REST request)

curl -X POST https://firecrawl-skill.example.com/invoke \
  -H "Authorization: Bearer <API_OR_OAUTH_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{ "input": "do-something", "context": { "user_id": "user-123" } }'

Your skill should validate the token, parse the input, and respond with a clear schema (result payload, error codes, or async status URL).

 

Error handling and retries

  • Return appropriate HTTP status codes: 200 for success, 202 for accepted/async, 4xx for client errors (bad request, unauthorized), 5xx for server errors.
  • Design idempotency for retryable operations (use an invocation ID) so the platform or agents can safely retry.
  • Use exponential backoff and a bounded retry policy on both sides (agent and skill) to avoid overload.

 

Observability and debugging

  • Log invocation IDs and correlate them between OpenClaw logs and your skill logs.
  • Expose metrics: request count, latency, error rates, token validation failures.
  • When something breaks: check agent logs, OpenClaw’s invocation logs, HTTP traces, and API responses. Verify tokens/scopes and webhook signature validation first.

 

Security best practices

  • Use HTTPS only; refuse plain HTTP.
  • Store credentials in a secrets manager (OpenClaw secret store or Vault). Rotate keys regularly.
  • Request minimal OAuth scopes and use short-lived access tokens with refresh tokens stored securely on your server.
  • Validate all inbound requests (auth, signatures, input schemas) and sanitize outputs.

 

Where to host stateful or long-running parts

  • Agent runtimes are typically ephemeral — move databases, job queues (Redis, SQS, RabbitMQ), cron/scheduler, and long-running workers to external services.
  • If the skill needs callbacks, ensure your external service can reach OpenClaw webhooks or vice versa (set up NAT, public endpoints, or a trusted tunnel for development).

 

Acceptance testing checklist

  • Skill registered in OpenClaw with correct URLs and secrets.
  • Agent can call skill endpoint and receive an expected response for a simple invocation.
  • OAuth flow completes and tokens are usable for authorized calls.
  • Webhooks are received and verified by the skill (and retries behave as expected).
  • Logs/metrics show correlated invocation IDs and no unexpected 401/403 errors.

 

Final implementation notes

  • Do not embed long-lived credentials in the agent process if the runtime cannot guarantee secret persistence — use a dedicated secrets store and fetch at runtime if needed.
  • Keep the contract (request/response schema, scopes, retry semantics) well-documented and versioned so OpenClaw admins can upgrade safely.
  • Treat the OpenClaw-to-skill interaction as a normal authenticated API integration: design for retries, idempotency, and observability; move heavy lifting outside the agent.

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Troubleshooting Firecrawl Skills and OpenClaw Integration

1

Why does a Firecrawl Skill fail Skill Manifest validation when registering with the OpenClaw Skill Router?

 

Direct Answer

 

A Firecrawl Skill fails Skill Manifest validation when its manifest doesn't match the Skill Router's expected schema or contains invalid values (missing required fields, wrong types, unreachable entrypoint, or incorrect auth/permission declarations).

 

Common causes

 
  • Malformed JSON/YAML or schema mismatch (missing id, version, entrypoint, permissions).
  • Unreachable/invalid entrypoint URL (TLS, redirects, host allowlist).
  • Auth or scopes misdeclared or not permitted by router policy.
  • Signature/checksum, content-type, or size limits.

 

How to fix

 
  • Validate manifest against the published schema from docs.
  • Fix required fields and types, ensure semver and HTTPS endpoint reachable.
  • Correct auth config and declared permissions; re-run router validation and inspect its error logs.

2

How to fix mismatched Intent Map entries that cause OpenClaw to dispatch Firecrawl intents to the wrong Action Handler?

Fix the mismatch by locating the Intent Map entry whose key or metadata differs from the Firecrawl intent name, correct the mapping so the intent key exactly matches the Action Handler registration, redeploy the skill/manifest, and verify with logs and test requests. Ensure permissions and runtime bindings are consistent so OpenClaw routes the intent to the intended handler.

 

Diagnose and Fix

 
  • Inspect the intent map and handler registry for exact key/case mismatches.
  • Update the skill manifest or ClawHub mapping to use the canonical intent name.
  • Redeploy the skill and run a test request while tailing runtime logs to confirm routing.
  • Validate permissions and any webhook/auth settings that gate handler execution.
const intentMap = {
  'Firecrawl.Start': startHandler, <b>//</b> correct key
  'firecrawl.start': wrongHandler <b>//</b> remove this entry
};

3

What steps resolve Invocation Token validation or signature verification errors when OpenClaw invokes Firecrawl Skill webhooks?

The quick answer: check that the Invocation Token header and the webhook signature are exactly what the skill platform expects, use the raw HTTP body to recompute the HMAC/signed value with the shared secret (stored in an environment variable), compare signatures with a constant-time compare, and ensure your web framework isn't altering the body or headers (body parsers and proxies are common causes).

 

Checklist

 
  • Confirm header names and token value set in your skill config and env vars.
  • Use raw request body when computing signature; middleware can break this.
  • Compute HMAC with the agreed algorithm (e.g. sha256) and the shared secret.
  • Use timingSafeEqual to compare signatures.
  • Log incoming headers, computed signature, and raw body (redact secrets) for debugging.

 

Express example

 
const express = require('express')
const crypto = require('crypto')
const app = express()
app.use(express.raw({type: '*/*'})) 
app.post('/webhook', (req, res) => {
  // <b>//</b> read headers and env
  const token = req.get('x-invocation-token')
  const sig = req.get('x-webhook-signature')
  const secret = process.env.WEBHOOK_SECRET
  // <b>//</b> quick token check
  if (!token || token !== process.env.INVOCATION_TOKEN) return res.sendStatus(401)
  // <b>//</b> compute HMAC on raw body
  const computed = 'sha256=' + crypto.createHmac('sha256', secret).update(req.body).digest('hex')
  const a = Buffer.from(computed)
  const b = Buffer.from(sig || '')
  if (a.length !== b.length || !crypto.timingSafeEqual(a,b)) return res.sendStatus(401)
  res.sendStatus(200)
})
app.listen(3000)

4

How to troubleshoot slot-filling and Entity Schema type errors that cause the Skill Execution Context to drop user slots during Firecrawl conversations?

Direct answer: Slot drops usually come from schema/type mismatches, validation failures, or runtime state loss — fix by confirming Entity Schema types match incoming values, coercing/parsing user values before setting slots, and using runtime logs to find validation errors so the Skill Execution Context accepts and persists slots.

 

Troubleshooting steps

 
  • Check schema vs values: ensure names/types (string, number, enum) align.
  • Inspect runtime logs: look for validation or serialization errors when slots are set.
  • Coerce before set: normalize dates/numbers/enums to schema format.
  • Persist state: if conversations span agents, store slots externally.
// Coerce slot to schema type before sending to skill
function coerce(value, type) {
  if (type==='number') return Number(value);
  if (type==='string') return String(value);
  if (type==='boolean') return value==='true';
  return value; // leave complex types validated by skill
}
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