get_metrics
Retrieve real-time metrics from the ASTRA bio-hybrid neuromorphic simulation pipeline, covering SNN and consciousness proxy data.
Instructions
Real-time Metrics
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve real-time metrics from the ASTRA bio-hybrid neuromorphic simulation pipeline, covering SNN and consciousness proxy data.
Real-time Metrics
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for disclosing behavioral traits, but it says nothing about side effects, latency, or the meaning of 'real-time'. The tool may be read-only, but this is not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two words), but it sacrifices clarity and usefulness. Conciseness without adequate information is under-specification, not efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no parameter details, the description fails to provide enough context for an agent to understand what metrics are returned or how to interpret the output. It is insufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so schema coverage is 100% trivially. The description adds no parameter-specific information, but the baseline for zero-parameter tools is 4, as no additional parameter semantics are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Real-time Metrics' is vague and does not specify what type of metrics (system, neural, performance, etc.) are returned. It barely clarifies beyond the tool name and does not distinguish it from sibling like 'tcai_metrics'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. There is no mention of context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/christophejlegros-lgtm/ASTRA-Unified-ResearchLab-MCP-v2.8'
If you have feedback or need assistance with the MCP directory API, please join our Discord server