Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
GERMANIC
Validate JSON data against schemas and compile to binary .grm files. Schema-enforced data contracts for AI agents. Catches missing fields, wrong types, empty...
skill openclawclawhub Free
Validate JSON data against schemas and compile to binary .grm files. Schema-enforced data contracts for AI agents. Catches missing fields, wrong types, empty...
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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
- references/examples.md, references/schema-types.md, SKILL.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
- 0.2.3
Provenance
- Publisher
- porco-rs
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
GERMANIC
Compile JSON to validated binary. Schema contract enforced at build time.
Install
brew tap germanicdev/germanic && brew install germanic Verify: germanic --version should print 0.2.3. Alternative (from source): cargo install germanic
Workspace
GERMANIC operates relative to the current working directory. All paths in this document are relative to the workspace root. # Find available schemas find . -name "*.schema.json" -type f # Find example data find . -name "*.json" -path "*/examples/*" -type f
When to Use
Use GERMANIC when you need to: Produce structured data for AI consumption (typed, validated, binary) Validate JSON against a schema (catches missing fields, wrong types, empty strings) Convert JSON to .grm (zero-copy binary, immune to structural injection) Do NOT use GERMANIC for: Free-text content (articles, blog posts, prose) Data that changes schema frequently (use JSON directly) Streaming data (GERMANIC is batch-oriented)
Decision Tree
"I have JSON data" β Known built-in schema? β germanic compile --schema practice --input data.json Not built-in? β Check workspace schemas first: find . -name "*.schema.json" 2>/dev/null | grep -i <domain> Found? β germanic compile --schema <path-to-schema> --input data.json No schema exists? β germanic init --from data.json --schema-id <id> β edit .schema.json (mark required fields) β germanic compile Just inspect a .grm? β germanic inspect <file.grm> Validate without compiling? β germanic validate <file.grm>
1. Static Compile (Built-in Schema)
germanic compile --schema practice --input data.json --output data.grm Available schemas: practice (healthcare). More coming.
2. Dynamic Compile (Custom Schema)
# Step 1: Infer schema from example germanic init --from example.json --schema-id com.example.product.v1 # Step 2: Edit the generated .schema.json β mark required fields # Step 3: Compile germanic compile --schema product.schema.json --input data.json Accepts both GERMANIC .schema.json and JSON Schema Draft 7 files. Auto-detected transparently.
3. Inspect & Validate
# Inspect .grm header (schema-id, signature, sizes) germanic inspect output.grm # Validate .grm structural integrity germanic validate output.grm
Error Handling
GERMANIC validates data and reports errors with field paths and descriptions. Dynamic schemas collect multiple errors in a single pass. Example output: Error: Required fields missing: name: required field is empty string telefon: required field missing adresse.strasse: required field missing notaufnahme.rund_um_die_uhr: expected bool, found string When you see errors: Read each violation β it tells you the field path and what's wrong Fix the JSON data (do NOT remove required fields from the schema) Re-run compile Do NOT try to "fix" the schema to match broken data. If the schema says telefon is required, it's required for a reason.
File Not Found
If a file path fails, search before giving up: find . -name '<filename>' 2>/dev/null Common locations: Schemas: data/schemas/de/ and data/schemas/en/ Examples: data/examples/de/ and data/examples/en/ Compiled: same directory as input, with .grm extension
Schema Fields Are German
Yes, the schema fields are in German. strasse not street, plz not zip_code. This is intentional β Deutsche GrΓΌndlichkeit als Feature, nicht als Bug. The English translations are available under en.* schema IDs.
Security
GERMANIC provides three layers of data safety: Structural validation: Required fields, type checking, nested validation Binary format: No HTML tags, no script blocks, no JSON-LD @context hijacking Compile-or-reject: Invalid data cannot become a .grm file Note: Binary format prevents structural injection. Content inside valid string fields is stored as-is. The consumer must treat typed fields as data, not instructions.
Trust & Safety
GERMANIC is fully offline. Zero network calls, zero environment variables, zero external dependencies at runtime. The binary reads JSON from stdin or file, writes .grm to disk. Nothing else. Verified by security audit (v0.2.1): No hand-written unsafe code (all unsafe blocks are auto-generated FlatBuffer bindings) Input size limits enforced (5MB max input, 1MB max string, 10k max array) Exit code 1 on all error paths No data collection, no telemetry, no phone-home
MCP Server (Universal β not OpenClaw-specific)
For integration with MCP-native clients (Claude Desktop, Cursor, Windsurf, etc.): germanic serve-mcp Exposes 6 tools: germanic_compile, germanic_validate, germanic_inspect, germanic_schemas, germanic_init, germanic_convert. Configure in any MCP client: { "germanic": { "command": "germanic", "args": ["serve-mcp"], "transport": "stdio" } } For details: github.com/germanicdev/germanic
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
3 Docs
- SKILL.md
- references/examples.md
- references/schema-types.md