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Get Started Free →Registers external services with health checks, central config, and unified execution. Use when integrating multiple external services needing coordination.
.claude/skills/athola-service-registry/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -4% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -25% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 25% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 155% | 0% |
A registry pattern for managing connections to external services. Handles configuration, health checking, and execution across multiple service integrations.
python@dataclass class ServiceConfig: name: str command: str auth_method: str # "api_key", "oauth", "token" auth_env_var: str quota_limits: dict models: list[str] = field(default_factory=list)
Verification: Run the command with --help flag to verify availability.
python@dataclass class ExecutionResult: success: bool stdout: str stderr: str exit_code: int duration: float tokens_used: int
Verification: Run the command with --help flag to verify availability.
pythonfrom leyline.service_registry import ServiceRegistry registry = ServiceRegistry() registry.register( "gemini", ServiceConfig( name="gemini", command="gemini", auth_method="api_key", auth_env_var="GEMINI_API_KEY", quota_limits={"rpm": 60, "daily": 1000}, ), )
Verification: Run the command with --help flag to verify availability.
pythonresult = registry.execute( service="gemini", prompt="Analyze this code", files=["src/main.py"], model="gemini-3-pro", ) if result.success: print(result.stdout)
Verification: Run the command with --help flag to verify availability.
python# Check single service status = registry.health_check("gemini") # Check all services all_status = registry.health_check_all() for service, healthy in all_status.items(): print(f"{service}: {'OK' if healthy else 'FAILED'}")
Verification: Run the command with --help flag to verify availability.
python# Select best service for task service = registry.select_service( requirements={"large_context": True, "fast_response": False} )
Verification: Run the command with --help flag to verify availability.
pythondef execute_with_failover(prompt: str, files: list) -> ExecutionResult: for service in registry.get_healthy_services(): result = registry.execute(service, prompt, files) if result.success: return result raise AllServicesFailedError()
Verification: Run the command with --help flag to verify availability.
yaml# In your skill's frontmatter dependencies: [leyline:service-registry]
Verification: Run the command with --help flag to verify availability.
modules/service-config.md for configuration options.modules/execution-patterns.md for advanced usage.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 11,140 | 5,773 | -48% | 1 | 1 | 0% | 2,396 | 2,305 | -4% | 0 | 0 | — |
case-02 | fail→pass | 14,030 | 9,956 | -29% | 1 | 1 | 0% | 2,819 | 2,967 | +5% | 0 | 0 | — |
case-03 | fail→pass | 18,804 | 8,461 | -55% | 1 | 1 | 0% | 3,847 | 2,898 | -25% | 0 | 0 | — |
case-04 | pass→pass | 5,143 | 4,912 | -4% | 1 | 1 | 0% | 1,090 | 1,915 | +76% | 0 | 0 | — |
case-05 | pass→pass | 4,050 | 3,336 | -18% | 1 | 1 | 0% | 785 | 1,678 | +114% | 0 | 0 | — |
case-06 | pass→pass | 2,312 | 3,118 | +35% | 1 | 1 | 0% | 428 | 1,583 | +270% | 0 | 0 | — |
case-07 | fail→pass | 6,476 | 2,672 | -59% | 1 | 1 | 0% | 1,236 | 1,550 | +25% | 0 | 0 | — |
case-08 | fail→pass | 3,155 | 2,835 | -10% | 1 | 1 | 0% | 618 | 1,578 | +155% | 0 | 0 | — |
case-09 | fail→pass | 9,851 | 6,821 | -31% | 1 | 1 | 0% | 2,253 | 2,372 | +5% | 0 | 0 | — |
case-10 | pass→pass | 7,275 | 2,785 | -62% | 1 | 1 | 0% | 1,182 | 1,495 | +26% | 0 | 0 | — |
case-11 | fail→pass | 5,693 | 2,122 | -63% | 1 | 1 | 0% | 934 | 1,318 | +41% | 0 | 0 | — |
case-12 | fail→pass | 4,685 | 2,321 | -50% | 1 | 1 | 0% | 810 | 1,406 | +74% | 0 | 0 | — |
case-13 | pass→pass | 5,106 | 2,105 | -59% | 1 | 1 | 0% | 874 | 1,343 | +54% | 0 | 0 | — |
case-14 | fail→pass | 11,542 | 5,926 | -49% | 1 | 1 | 0% | 2,223 | 2,140 | -4% | 0 | 0 | — |
case-15 | fail→pass | 5,689 | 3,103 | -45% | 1 | 1 | 0% | 1,081 | 1,545 | +43% | 0 | 0 | — |
case-16 | fail→pass | 7,779 | 2,307 | -70% | 1 | 1 | 0% | 1,319 | 1,245 | -6% | 0 | 0 | — |
case-17 | fail→pass | 4,983 | 1,346 | -73% | 1 | 1 | 0% | 720 | 1,144 | +59% | 0 | 0 | — |
case-18 | fail→pass | 9,037 | 2,177 | -76% | 1 | 1 | 0% | 1,523 | 1,387 | -9% | 0 | 0 | — |
case-19 | pass→pass | 7,204 | 1,732 | -76% | 1 | 1 | 0% | 1,113 | 1,219 | +10% | 0 | 0 | — |
case-20 | fail→pass | 9,791 | 3,433 | -65% | 1 | 1 | 0% | 1,928 | 1,669 | -13% | 0 | 0 | — |
case-21 | pass→pass | 10,497 | 2,461 | -77% | 1 | 1 | 0% | 1,927 | 1,431 | -26% | 0 | 0 | — |
case-22 | fail→pass | 13,326 | 2,201 | -83% | 1 | 1 | 0% | 2,712 | 1,361 | -50% | 0 | 0 | — |
case-23 | pass→pass | 4,589 | 2,090 | -54% | 1 | 1 | 0% | 784 | 1,313 | +67% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +65 percentage points is the difference between those two pass rates over the 23 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.