source_health
Retrieve configuration and availability status for each data provider to identify operational issues and verify source health.
Instructions
각 데이터 Provider의 설정 및 가용 상태를 반환합니다.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve configuration and availability status for each data provider to identify operational issues and verify source health.
각 데이터 Provider의 설정 및 가용 상태를 반환합니다.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds the return content (configuration and availability), but it does not disclose behavior such as freshness, failure modes, or how availability is determined.
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 a single concise sentence that front-loads the action ('returns') and the resource ('configuration and availability status of each data provider'). There is no redundancy or filler.
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?
For a no-parameter read-only status tool, the description is mostly complete and the annotations cover safety. However, there is no output schema and the description only vaguely names 'configuration and availability status' without specifying the exact response shape or fields.
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 tool has zero parameters, so the description is not expected to explain parameter semantics. The schema and description are consistent, with 100% coverage of an empty parameter set.
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 clearly states the tool returns the configuration and availability status of each data provider, giving a specific verb and resource. It is distinct from the legal-focused sibling tools, though it does not explicitly contrast itself with them.
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?
The description implies a health/status-check use case but provides no explicit guidance on when to use this tool versus alternatives or any exclusions. An agent would need to infer applicability from the tool name and general context.
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/ai-studying-man/DAPA-MCP'
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