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ThoTischner

observability-mcp

list_services

List all discovered services with their sources and available signal types. Use this to get the exact service names required for querying metrics, logs, or health.

Instructions

Discover the service names that can be queried, aggregated across every connected backend. When to use: call this before query_metrics, query_logs, or get_service_health to obtain the exact, case-sensitive service name those tools require. Behavior: read-only, no side effects. Returns one entry per service with the service name, the source(s) it was discovered in, and which signals are available for it (metrics, logs, or both). Related: list_sources for backend health; get_service_health for a per-service overview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoOptional case-insensitive substring to narrow the result to matching service names (e.g. 'payment'). Omit to list every discovered service.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description fully bears the burden of disclosing behavior. It explicitly states 'read-only, no side effects' and describes return content (service name, source(s), available signals). This goes beyond what annotations would typically provide.

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 three sentences, front-loaded with purpose, and uses a clear line break for usage guidance. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has one optional parameter and no output schema, the description adequately explains return values (service name, source, available signals) and related tools. It is complete for an agent to decide when and how to use it.

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 only parameter 'filter' has 100% schema description coverage, baseline 3. The description adds value by clarifying it's optional, case-insensitive, and providing an example ('payment'), which helps the agent understand usage beyond the schema.

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 ('Discover') and resource ('service names'), and clearly states it lists services that can be queried. It distinguishes from siblings by mentioning related tools like query_metrics, query_logs, and get_service_health.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use this tool ('call this before query_metrics, query_logs, or get_service_health') and provides context for obtaining exact case-sensitive names. Also suggests alternatives (list_sources, get_service_health) for different purposes.

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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