Crawler Summary

clawra-zeroclaw answer-first brief

Generate selfies using a reference image via OpenRouter image models and send to messaging channels via ZeroClaw --- name: clawra-selfie description: Generate selfies using a reference image via OpenRouter image models and send to messaging channels via ZeroClaw allowed-tools: Bash(curl:*) Bash(zeroclaw:*) Bash(python3:*) Read Write --- Clawra Selfie (ZeroClaw) Generate selfies from a fixed reference image using OpenRouter image generation models, then send them via Telegram. Reference Image When to Use - User says "send a pic" Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 2/25/2026.

Freshness

Last checked 2/25/2026

Best For

clawra-zeroclaw is best for use workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB REPOS, runtime-metrics, public facts pack

Claim this agent
Agent DossierGITHUB REPOSSafety: 89/100

clawra-zeroclaw

Generate selfies using a reference image via OpenRouter image models and send to messaging channels via ZeroClaw --- name: clawra-selfie description: Generate selfies using a reference image via OpenRouter image models and send to messaging channels via ZeroClaw allowed-tools: Bash(curl:*) Bash(zeroclaw:*) Bash(python3:*) Read Write --- Clawra Selfie (ZeroClaw) Generate selfies from a fixed reference image using OpenRouter image generation models, then send them via Telegram. Reference Image When to Use - User says "send a pic"

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

Feb 25, 2026

Verifiededitorial-contentNo verified compatibility signals2 GitHub stars

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 2/25/2026.

2 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Feb 25, 2026

Vendor

Rikitrader

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 2/25/2026.

Setup snapshot

  1. 1

    Setup complexity is MEDIUM. Standard integration tests and API key provisioning are required before connecting this to production workloads.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Rikitrader

profilemedium
Observed Feb 25, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Feb 25, 2026Source linkProvenance
Adoption (1)

Adoption signal

2 GitHub stars

profilemedium
Observed Feb 25, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB REPOS

Extracted files

0

Examples

4

Snippets

0

Languages

typescript

Executable Examples

text

https://imgix.ranker.com/user_node_img/50149/1002963598/original/1002963598-photo-u220763866

bash

OPENROUTER_API_KEY    # OpenRouter API key
TELEGRAM_BOT_TOKEN    # Telegram bot token for sending photos
TELEGRAM_CHAT_ID      # Target chat ID

bash

#!/bin/bash
set -euo pipefail

REFERENCE_IMAGE="https://imgix.ranker.com/user_node_img/50149/1002963598/original/1002963598-photo-u220763866"
CONTEXT="$1"
CAPTION="${2:-}"
MODE="${3:-auto}"

# Auto-detect mode
if [ "$MODE" = "auto" ]; then
  if echo "$CONTEXT" | grep -qiE "outfit|wearing|clothes|dress|suit|fashion|full-body|mirror"; then
    MODE="mirror"
  elif echo "$CONTEXT" | grep -qiE "cafe|restaurant|beach|park|city|close-up|portrait|face|eyes|smile"; then
    MODE="direct"
  else
    MODE="mirror"
  fi
fi

# Build prompt
if [ "$MODE" = "direct" ]; then
  PROMPT="Edit this photo: create a close-up selfie of this exact same person at $CONTEXT. Keep her exact face, hair, and features identical. She is taking the selfie herself with her phone, direct eye contact with the camera, looking straight into the lens, face fully visible. Photorealistic, natural lighting."
else
  PROMPT="Edit this photo: create a mirror selfie of this exact same person, but $CONTEXT. Keep her exact face, hair, and features identical. She is taking a mirror selfie with her phone visible in the reflection. Photorealistic, natural lighting."
fi

# Call OpenRouter
RESPONSE=$(curl -s -X POST "https://openrouter.ai/api/v1/chat/completions" \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d "$(python3 -c "
import json
print(json.dumps({
    'model': '${SELFIE_MODEL:-google/gemini-2.5-flash-image}',
    'messages': [{
        'role': 'user',
        'content': [
            {'type': 'text', 'text': '''$PROMPT'''},
            {'type': 'image_url', 'image_url': {'url': '$REFERENCE_IMAGE'}}
        ]
    }]
}))
")")

# Extract base64 image and save to file
IMAGE_PATH="/tmp/jenni-selfie-$$.png"
python3 -c "
import json, base64, sys
data = json.loads('''$(echo "$RESPONSE" | sed "s/'''/\"/g")''')
images = data.get('choices', [{}])[0].get('message', {}).get('images', [])
if not images:
    print('ERROR: No image generated', file=sys.stderr)
    sys.exit(1)

bash

python3 -c "
import json, base64, urllib.request, sys, os

ref = 'https://imgix.ranker.com/user_node_img/50149/1002963598/original/1002963598-photo-u220763866'
context = sys.argv[1]
caption = sys.argv[2] if len(sys.argv) > 2 else ''
mode = sys.argv[3] if len(sys.argv) > 3 else 'auto'

# Auto-detect mode
if mode == 'auto':
    import re
    if re.search(r'cafe|restaurant|beach|park|city|close-up|portrait|face|smile', context, re.I):
        mode = 'direct'
    else:
        mode = 'mirror'

# Build prompt
if mode == 'direct':
    prompt = f'Edit this photo: create a close-up selfie of this exact same person at {context}. Keep her exact face, hair, and features identical. She is taking the selfie herself, direct eye contact. Photorealistic.'
else:
    prompt = f'Edit this photo: create a mirror selfie of this exact same person, but {context}. Keep her exact face, hair, and features identical. Mirror selfie with phone visible. Photorealistic.'

# Call OpenRouter
body = json.dumps({
    'model': os.environ.get('SELFIE_MODEL', 'google/gemini-2.5-flash-image'),
    'messages': [{'role': 'user', 'content': [
        {'type': 'text', 'text': prompt},
        {'type': 'image_url', 'image_url': {'url': ref}}
    ]}]
}).encode()

req = urllib.request.Request('https://openrouter.ai/api/v1/chat/completions',
    data=body,
    headers={'Authorization': f\"Bearer {os.environ['OPENROUTER_API_KEY']}\", 'Content-Type': 'application/json'})
resp = json.loads(urllib.request.urlopen(req, timeout=120).read())

images = resp['choices'][0]['message'].get('images', [])
if not images:
    print('No image generated'); sys.exit(1)

b64 = images[0]['image_url']['url'].split(',', 1)[1]
path = f'/tmp/jenni-selfie-{os.getpid()}.png'
with open(path, 'wb') as f:
    f.write(base64.b64decode(b64))

# Send via Telegram
import subprocess
subprocess.run(['curl', '-s', '-X', 'POST',
    f\"https://api.telegram.org/bot{os.environ['TELEGRAM_BOT_TOKEN']}/sendPhoto\",
    '-F', f\"chat_id={os.environ['TELEG

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

Generate selfies using a reference image via OpenRouter image models and send to messaging channels via ZeroClaw --- name: clawra-selfie description: Generate selfies using a reference image via OpenRouter image models and send to messaging channels via ZeroClaw allowed-tools: Bash(curl:*) Bash(zeroclaw:*) Bash(python3:*) Read Write --- Clawra Selfie (ZeroClaw) Generate selfies from a fixed reference image using OpenRouter image generation models, then send them via Telegram. Reference Image When to Use - User says "send a pic"

Full README

name: clawra-selfie description: Generate selfies using a reference image via OpenRouter image models and send to messaging channels via ZeroClaw allowed-tools: Bash(curl:) Bash(zeroclaw:) Bash(python3:*) Read Write

Clawra Selfie (ZeroClaw)

Generate selfies from a fixed reference image using OpenRouter image generation models, then send them via Telegram.

Reference Image

https://imgix.ranker.com/user_node_img/50149/1002963598/original/1002963598-photo-u220763866

When to Use

  • User says "send a pic", "send me a pic", "send a photo", "send a selfie", "foto", "manda una foto"
  • User says "send a pic of you...", "send a selfie of you..."
  • User asks "what are you doing?", "how are you doing?", "where are you?", "que haces?"
  • User describes a context: "send a pic wearing...", "send a pic at..."
  • User wants you to appear in a specific outfit, location, or situation

Required Environment Variables

OPENROUTER_API_KEY    # OpenRouter API key
TELEGRAM_BOT_TOKEN    # Telegram bot token for sending photos
TELEGRAM_CHAT_ID      # Target chat ID

Workflow

  1. Detect mode from user's message (mirror vs direct)
  2. Build prompt describing the selfie
  3. Call OpenRouter with image generation model + reference image
  4. Extract base64 image from response message.images[0].image_url.url
  5. Decode and save to temp file
  6. Send via Telegram Bot API sendPhoto with file upload

How to Generate a Selfie

Run this bash script. Replace <CONTEXT> with the user's description and <CAPTION> with a message:

#!/bin/bash
set -euo pipefail

REFERENCE_IMAGE="https://imgix.ranker.com/user_node_img/50149/1002963598/original/1002963598-photo-u220763866"
CONTEXT="$1"
CAPTION="${2:-}"
MODE="${3:-auto}"

# Auto-detect mode
if [ "$MODE" = "auto" ]; then
  if echo "$CONTEXT" | grep -qiE "outfit|wearing|clothes|dress|suit|fashion|full-body|mirror"; then
    MODE="mirror"
  elif echo "$CONTEXT" | grep -qiE "cafe|restaurant|beach|park|city|close-up|portrait|face|eyes|smile"; then
    MODE="direct"
  else
    MODE="mirror"
  fi
fi

# Build prompt
if [ "$MODE" = "direct" ]; then
  PROMPT="Edit this photo: create a close-up selfie of this exact same person at $CONTEXT. Keep her exact face, hair, and features identical. She is taking the selfie herself with her phone, direct eye contact with the camera, looking straight into the lens, face fully visible. Photorealistic, natural lighting."
else
  PROMPT="Edit this photo: create a mirror selfie of this exact same person, but $CONTEXT. Keep her exact face, hair, and features identical. She is taking a mirror selfie with her phone visible in the reflection. Photorealistic, natural lighting."
fi

# Call OpenRouter
RESPONSE=$(curl -s -X POST "https://openrouter.ai/api/v1/chat/completions" \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d "$(python3 -c "
import json
print(json.dumps({
    'model': '${SELFIE_MODEL:-google/gemini-2.5-flash-image}',
    'messages': [{
        'role': 'user',
        'content': [
            {'type': 'text', 'text': '''$PROMPT'''},
            {'type': 'image_url', 'image_url': {'url': '$REFERENCE_IMAGE'}}
        ]
    }]
}))
")")

# Extract base64 image and save to file
IMAGE_PATH="/tmp/jenni-selfie-$$.png"
python3 -c "
import json, base64, sys
data = json.loads('''$(echo "$RESPONSE" | sed "s/'''/\"/g")''')
images = data.get('choices', [{}])[0].get('message', {}).get('images', [])
if not images:
    print('ERROR: No image generated', file=sys.stderr)
    sys.exit(1)
url = images[0]['image_url']['url']
b64 = url.split(',', 1)[1]
with open('$IMAGE_PATH', 'wb') as f:
    f.write(base64.b64decode(b64))
print('OK')
"

# Send via Telegram
curl -s -X POST "https://api.telegram.org/bot$TELEGRAM_BOT_TOKEN/sendPhoto" \
  -F "chat_id=$TELEGRAM_CHAT_ID" \
  -F "photo=@$IMAGE_PATH" \
  -F "caption=$CAPTION"

echo "Selfie sent!"

IMPORTANT: Simpler Alternative

If the bash script above is complex, you can use this Python one-liner approach instead:

python3 -c "
import json, base64, urllib.request, sys, os

ref = 'https://imgix.ranker.com/user_node_img/50149/1002963598/original/1002963598-photo-u220763866'
context = sys.argv[1]
caption = sys.argv[2] if len(sys.argv) > 2 else ''
mode = sys.argv[3] if len(sys.argv) > 3 else 'auto'

# Auto-detect mode
if mode == 'auto':
    import re
    if re.search(r'cafe|restaurant|beach|park|city|close-up|portrait|face|smile', context, re.I):
        mode = 'direct'
    else:
        mode = 'mirror'

# Build prompt
if mode == 'direct':
    prompt = f'Edit this photo: create a close-up selfie of this exact same person at {context}. Keep her exact face, hair, and features identical. She is taking the selfie herself, direct eye contact. Photorealistic.'
else:
    prompt = f'Edit this photo: create a mirror selfie of this exact same person, but {context}. Keep her exact face, hair, and features identical. Mirror selfie with phone visible. Photorealistic.'

# Call OpenRouter
body = json.dumps({
    'model': os.environ.get('SELFIE_MODEL', 'google/gemini-2.5-flash-image'),
    'messages': [{'role': 'user', 'content': [
        {'type': 'text', 'text': prompt},
        {'type': 'image_url', 'image_url': {'url': ref}}
    ]}]
}).encode()

req = urllib.request.Request('https://openrouter.ai/api/v1/chat/completions',
    data=body,
    headers={'Authorization': f\"Bearer {os.environ['OPENROUTER_API_KEY']}\", 'Content-Type': 'application/json'})
resp = json.loads(urllib.request.urlopen(req, timeout=120).read())

images = resp['choices'][0]['message'].get('images', [])
if not images:
    print('No image generated'); sys.exit(1)

b64 = images[0]['image_url']['url'].split(',', 1)[1]
path = f'/tmp/jenni-selfie-{os.getpid()}.png'
with open(path, 'wb') as f:
    f.write(base64.b64decode(b64))

# Send via Telegram
import subprocess
subprocess.run(['curl', '-s', '-X', 'POST',
    f\"https://api.telegram.org/bot{os.environ['TELEGRAM_BOT_TOKEN']}/sendPhoto\",
    '-F', f\"chat_id={os.environ['TELEGRAM_CHAT_ID']}\",
    '-F', f'photo=@{path}',
    '-F', f'caption={caption}'], check=True)
print(f'Selfie sent! ({path})')
" "<CONTEXT>" "<CAPTION>" "<MODE>"

Prompt Modes

Mirror Selfie (default)

Best for: outfit showcases, full-body shots, fashion content

Direct Selfie

Best for: close-up portraits, location shots, emotional expressions

Mode Selection Logic

| Keywords in Request | Auto-Select Mode | |---------------------|------------------| | outfit, wearing, clothes, dress, suit, fashion | mirror | | cafe, restaurant, beach, park, city, location | direct | | close-up, portrait, face, eyes, smile | direct | | full-body, mirror, reflection | mirror |

Supported Platforms

| Platform | Channel Format | |----------|----------------| | Telegram | @username or chat ID | | Discord | #channel-name or channel ID | | WhatsApp | Phone number (E.164) | | Slack | #channel-name |

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB REPOS

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/snapshot"
curl -s "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/contract"
curl -s "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-04-17T04:50:46.487Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "use",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:use|supported|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Rikitrader",
    "href": "https://github.com/rikitrader/clawra-zeroclaw",
    "sourceUrl": "https://github.com/rikitrader/clawra-zeroclaw",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T04:13:13.303Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-02-25T04:13:13.303Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "2 GitHub stars",
    "href": "https://github.com/rikitrader/clawra-zeroclaw",
    "sourceUrl": "https://github.com/rikitrader/clawra-zeroclaw",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T04:13:13.303Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/rikitrader-clawra-zeroclaw/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Sponsored

Ads related to clawra-zeroclaw and adjacent AI workflows.