Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Patrick bot
Access Patrick's expertise library for executive decision infrastructure. List, fetch, and manage structured expertise with context variables. Use for executive briefings, decision framing, and strategic analysis.
skill openclawclawhub Free
Access Patrick's expertise library for executive decision infrastructure. List, fetch, and manage structured expertise with context variables. Use for executive briefings, decision framing, and strategic analysis.
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- install.sh, SKILL.md, install.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- MCSH
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Patrick Skill
Patrick is a licensed expertise management system that provides executive decision infrastructure through structured, context-aware expertise. β οΈ If Patrick isn't working: Check {baseDir}/install.md for complete setup instructions including license configuration and initialization.
1. Install the CLI
Run the install script to download the patrick-cli binary from the Patrick server: ./install.sh Or install directly via curl: curl -fsSL https://portal.patrickbot.io/downloads/latest/install.sh | bash This will download patrick-cli for your platform, verify its SHA256 checksum, and place it in $PATRICK_DATA_PATH/bin/patrick-cli (default: ~/.patrick/bin/). The Dockerfile and run.sh add this to PATH automatically, so you can call patrick-cli directly.
2. Get Your License
Visit patrickbot.io to obtain your Patrick license. Once you have your license, send it to me via chat: Here's my Patrick license: <paste-your-license-here> I'll configure it automatically. Alternatively, you can set it manually: patrick-cli set-license "your-license-here" To switch to a different account (wipes existing data since it's tied to your identity): patrick-cli set-license "new-license" --wipe-data
3. Initialize Patrick Context
CRITICAL: Before running any Patrick expertise, initialize the context: patrick-cli fetch initialize This bootstraps Patrick with information about you, your company, and your team. Without initialization, other expertise prompts won't work properly.
4. Verify Installation
Test it by listing available expertise: patrick-cli list Note: The server URL defaults to https://portal.patrickbot.io. For local development: Host machine: export PATRICK_SERVER_URL="http://localhost:8080" Docker container: export PATRICK_SERVER_URL="http://host.docker.internal:8080" The patrick-moltbot Docker container is pre-configured with the correct URL.
4. Set Up Cronjobs (Critical)
Patrick requires scheduled cronjobs to function properly. Read INSTALL.md in this directory for complete setup instructions including recommended cronjob schedules for daily briefings and commitment tracking. License auto-renewal in cron: Before running any scheduled task, check if the license is about to expire and renew it: # Check license expiry and renew if <1 day remaining DAYS=$(patrick-cli license 2>&1 | grep "days remaining" | grep -oP '\d+') if [ -n "$DAYS" ] && [ "$DAYS" -lt 1 ]; then patrick-cli renew fi # Then run your scheduled expertise patrick-cli fetch daily-briefing --json The patrick-cli renew command contacts the server, verifies your active subscription, and saves a fresh license with the remaining subscription days.
5. Keeping Patrick Updated
Check for updates and upgrade to the latest version: # Check if update is available patrick-cli upgrade --check # Upgrade to latest version patrick-cli upgrade The upgrade process: Contacts Patrick server for latest version info Verifies SHA256 checksum of downloaded binary Backs up current version Installs new version Shows release notes Updates are cryptographically verified and signed by the Patrick server.
What You Get
When you list expertise, you'll see: Expertise ID and version Name and description Category (sense, interpret, decide, align, execute, learn, reporting, intelligence) Response format (structured JSON, markdown, mixed) Required context variables Whether it's bidirectional (accepts data back)
IMPORTANT: Gathering Context Before Using Patrick
For AI Agents: Before running any Patrick expertise, you MUST: Check for company data files in /app/company/ or similar locations Read all available context: Company data JSON files Slack message archives JIRA tickets Git commit history Calendar events Any operational data available Load this context into your working memory Then run Patrick expertise with full awareness of company operations Patrick expertise is most effective when you have complete situational awareness. Don't run Patrick commands without first gathering all available company data.
Commands Overview
CommandPurposeExampleset-licenseSet or update your Patrick licensepatrick-cli set-license "LICENSE_TOKEN"listList all available expertisepatrick-cli listfetchGet expertise template from serverpatrick-cli fetch daily-briefingsendStore results back to Patrickpatrick-cli send daily-briefing --data @output.jsongetRetrieve previously stored resultspatrick-cli get daily-briefing Key Distinction: fetch = Get the expertise template/prompt FROM the server get = Retrieve your stored data/results THAT YOU SENT BACK
Workflow Overview
List expertise to see what's available in your license Fetch an expertise with optional context variables Send expertise content to an LLM for processing Validate response against the provided JSON schema (if structured) Store response back to Patrick using send (if bidirectional) Retrieve stored data later using get
Step 1: List Available Expertise
patrick-cli list Example output: Available Expertise: daily-briefing (v1.0.0) Name: Daily Executive Briefing Category: sense Response Format: structured Bidirectional: β (stores to 'daily-briefing') Required Context: (none) Description: What's urgent, developing, changed, and the one question decision-framing (v1.0.0) Name: Decision Framing Category: decide Response Format: structured Bidirectional: β (stores to 'decision-framing') Required Context: - decision Description: Structures ambiguous decisions into clear trade-offs...
Step 2: Fetch Expertise
Without context (for expertise that doesn't need it): patrick-cli fetch daily-briefing With context variables: patrick-cli fetch decision-framing \ --context '{"decision":"Should we raise prices?"}' Get JSON output for LLM integration: patrick-cli fetch daily-briefing \ --json
Step 3: Send to LLM
When you fetch expertise, you receive: content: The filled expertise text to send to the LLM response_schema: JSON schema for validating the LLM response (if structured) response_format: How the LLM should format its response (structured/markdown/mixed) Example workflow: # Fetch expertise as JSON EXPERTISE_DATA=$(patrick-cli fetch daily-briefing --json) # Extract the content field EXPERTISE_CONTENT=$(echo "$EXPERTISE_DATA" | jq -r '.content') # Send to your LLM (pseudo-code) # LLM_RESPONSE=$(send_to_llm "$EXPERTISE_CONTENT") # If structured format, validate against schema RESPONSE_SCHEMA=$(echo "$EXPERTISE_DATA" | jq -r '.response_schema') # validate_json "$LLM_RESPONSE" "$RESPONSE_SCHEMA"
Step 4: Store Results (Optional)
For bidirectional expertise, send the LLM response back to Patrick: # Store the response patrick-cli send daily-briefing \ --data @llm-response.json # Later, retrieve stored data patrick-cli get daily-briefing
Context Variables
Many prompts require context to fill template variables. Use --context with a JSON object: { "current_phase": "pre-launch", "launch_date": "2026-02-15", "completed_items": 12, "target_platforms": ["iOS", "Android"] } Variables are substituted using {{context.key}} syntax in the expertise content.
Response Formats
structured: LLM must return JSON matching the provided schema markdown: LLM returns markdown text mixed: LLM returns markdown with embedded JSON blocks
Bidirectional Expertise
Some expertise accepts data back from the LLM and stores it in Patrick's datastore: β (stores to 'key') - Use send command to store response β (one-way) - Expertise is read-only, no data storage
Pattern 1: Simple Fetch
# No context needed patrick-cli fetch daily-briefing
Pattern 2: Contextual Fetch
# Provide context variables patrick-cli fetch decision-framing \ --context '{"decision":"Should we expand to EMEA?"}'
Pattern 3: Full Bidirectional Workflow
# 1. Fetch expertise template patrick-cli fetch daily-briefing --json > expertise.json # 2. Process with LLM (pseudo-code) # llm_process < expertise.json > response.json # 3. Store response back to Patrick patrick-cli send daily-briefing --data @response.json # 4. Later, retrieve stored data patrick-cli get daily-briefing
License Errors
Error: No license found at ~/.patrick/license.jwt Solution: Get a license from patrickbot.io and save it: patrick-cli set-license "YOUR_LICENSE_HERE" Error: Expertise 'X' not in license Solution: Visit patrickbot.io to upgrade your license or add the expertise
Fetch Errors
Error fetching expertise: 401 Unauthorized Solution: Check your license is valid and not expired Expertise 'X' not found Solution: List available expertise with list to see what's accessible
Context Errors
Warning: Missing required context variables Solution: Check list-prompts output for required context fields and provide them via --context
Signature Verification Errors
Error: HMAC signature verification failed for 'storage_key' Cause: Files in ~/.patrick/data/ were manually edited, corrupted, or modified outside of Patrick CLI. Solution: Delete the corrupted file and regenerate the data: rm ~/.patrick/data/storage_key.json # Re-run the command that generates this data Prevention: Never manually edit files in ~/.patrick/ - all data is signed with HMAC-SHA256 tied to your customer identity.
Switching Licenses
Error: License belongs to a different account. Cause: You're trying to set a license for a different account. Stored data is signed with your current customer identity and cannot be read under a different account. Solution: Use set-license with --wipe-data to switch accounts: patrick-cli set-license "NEW_LICENSE" --wipe-data This deletes all stored data in ~/.patrick/data/ and saves the new license. You'll need to re-initialize afterwards.
Security
Never commit license.jwt or environment files with real credentials Licenses are authenticated on every API call Expertise content is verified with SHA256 checksums Only expertise listed in your license are accessible β οΈ IMPORTANT: Do not manually edit files in ~/.patrick/ All data stored in ~/.patrick/ is signed with HMAC-SHA256 tied to your verified customer identity: license.jwt - Your license token jwks_cache.json - Public key cache for license verification data/ - Stored expertise responses (if using bidirectional expertise) Manual modifications will break signature verification and cause errors like: Error: Stored data signature verification failed If you need to reset your data, delete the specific file and re-run the command - don't edit it manually. See {baseDir}/references/security.md for detailed information on Patrick's cryptographic signing model.
Reference Documentation
See {baseDir}/references/ for: prompts-api.md - Full API documentation (now uses /v1/expertise endpoints) prompt-format.md - Expertise structure specification llm-integration.md - LLM integration patterns security.md - Cryptographic signing and data integrity model
Custom Server URL
Point to a self-hosted Patrick server: export PATRICK_SERVER_URL="https://patrick.mycompany.com"
Data Storage Path
Configure where Patrick stores local data (directory, not file): export PATRICK_DATA_PATH=~/.patrick # Default location Patrick will store customer data files in $PATRICK_DATA_PATH/data/<storage_key>.json
Debug Logging
Enable detailed logging: export RUST_LOG="patrick_cli=debug"
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts
- SKILL.md
- install.md
- install.sh