health
Check Zero Core Tools server status, uptime, and payment network configuration.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
zero-core-tools
TDQS
A4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. 'Check' strongly implies a read-only, non-destructive operation, but the description does not explicitly state that there are no side effects, nor does it disclose any potential errors or authorization requirements. It provides basic resource context but lacks deeper behavioral detail.
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, front-loaded sentence that directly states the tool's purpose without any fluff. Every word adds value and the structure is optimal for a simple health-check tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (zero params, no output schema), the description adequately covers the tool's scope by listing the three health aspects checked (status, uptime, payment network configuration). It does not go into return format or error behavior, but for a health check this is likely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline of 4 is appropriate. The description correctly implies that no input is needed, and there are no parameter semantics to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Check' and names the exact resource: 'Zero Core Tools server status, uptime, and payment network configuration.' This clearly distinguishes the tool from its siblings, none of which serve a health-check purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (check the server's health) but provides no explicit guidance on when to use this tool versus alternatives. Since no sibling tools are similar, the lack of explicit exclusions is acceptable, but the description could mention that it is a read-only diagnostic step.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
A3.9/5.0
Disambiguation5/5
Each tool has a clearly distinct purpose: sentiment analysis, structured data extraction, content generation, health check, tool listing, code review, web scraping, screenshot, and web search. There is minor overlap between scrape_url and extract_structured_data, but the different outputs (raw text vs. structured JSON) make them easily distinguishable.
Naming Consistency4/5
Most tool names follow the verb_noun snake_case pattern (e.g., analyze_sentiment, scrape_url). The only outlier is 'health', which is a single noun rather than a verb_noun like 'check_health'. This minor inconsistency slightly reduces coherence.
Tool Count5/5
With 9 tools, the server is well-scoped for a general-purpose utility toolkit. Each tool serves a useful function without redundancy, and the count is within the ideal range (3-15) for clarity and manageability.
Completeness4/5
The tool set covers a broad range of common AI/automation tasks such as text analysis, web scraping, content generation, search, and code review. While some potential utilities (e.g., translation or file conversion) are missing, the lack of a specific domain makes the set feel reasonably complete for a general-purpose toolkit.