F
license-
qualityD
maintenanceAllows developers and AI Agents to query Google Cloud Logging using natural language, translating queries into Google Cloud Logging Query Language (LQL) with Vertex AI Gemini 2.5.
1
llm-orchestration-agent
Server Details
Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mikerawsonnz/gosce-agents
- GitHub Stars
- 1
- Server Listing
- A2A GOSCE Agents
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Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
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Usage analytics
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Tool Definition Quality
C2.9/5.0
Tool DescriptionsC
Average 2.9/5 across 1 of 1 tools scored.
Server CoherenceB
Disambiguation5/5
With only one tool, there is no risk of confusion. The single tool 'invoke' has a clear and distinct purpose.
Naming Consistency5/5
With a single tool, naming consistency is trivially maintained. The tool name 'invoke' is clear and follows a common verb pattern.
Tool Count1/5
A single tool for an 'orchestration agent' is far too few. Orchestration typically requires multiple tools for different steps and configurations.
Completeness1/5
The server provides only a basic prompt runner, lacking essential orchestration features like multi-step chains, conditional logic, or integration with other tools.
Available Tools
1 toolinvokeCInspect
Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith tracing.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | JSON request for this capability (the same body you'd send as an A2A message). |
Tool Definition Quality
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions optional LangSmith tracing but fails to disclose side effects, permissions, or whether the tool is read-only or destructive. For a prompt execution tool, this lack of detail is a gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It effectively communicates the core functionality without redundancy. Given the simplicity of the tool, this level of conciseness is appropriate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description should explain return values or outcomes, but it does not. It only describes the action and optional tracing. The parameter description hints at input format, but overall the description leaves the agent without critical information about what happens after running the prompt.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'input' has a schema description that states it is a JSON request like an A2A message. This adds some context beyond the schema's type definition, but the description does not elaborate on expected fields or structure. With 100% schema coverage, the baseline is 3, and the A2A reference provides minor added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a prompt through a LangChain chain over Gemini on Vertex AI. It specifies the verb 'Run a prompt' and the resource (LangChain chain over Gemini). Although there are no siblings to differentiate, the purpose is specific and not a tautology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Since there are no sibling tools, this is less critical, but the description does not indicate context or prerequisites. It merely describes the action without usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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