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mshegolev

jaeger-mcp

by mshegolev

jaeger_list_operations

Read-onlyIdempotent

Discover operation names for a specific service in Jaeger tracing to filter trace searches effectively. Lists endpoints, methods, or functions traced for a given service.

Instructions

List all operation names Jaeger has seen for a given service.

Wraps GET /api/services/{service}/operations. Useful for discovering which operation names to pass as filters to jaeger_search_traces. Output is capped at 500 operations.

Examples: - Use when: "What HTTP endpoints does order-service expose in tracing?" → service='order-service'. - Use when: You want to search for a specific slow operation but need the exact name — list operations first, then pass it to jaeger_search_traces. - Use when: Auditing which gRPC methods a service traces. - Don't use when: You don't have a specific service — start with jaeger_list_services first. - Don't use when: You want to search traces immediately (skip this step if you already know the operation name).

Returns: dict with service / operations_count / truncated / operations (sorted alphabetically).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serviceYesService name exactly as returned by jaeger_list_services.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
serviceYes
operations_countYes
truncatedYes
operationsYes
Behavior4/5

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds valuable context beyond this: it mentions output capping at 500 operations, the wrapper around a specific API endpoint, and that operations are sorted alphabetically. This enhances transparency without contradicting annotations.

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 well-structured and front-loaded with the core purpose, followed by practical usage examples and return details. Every sentence adds value, such as clarifying the wrapper, use cases, and output structure, with no redundant information. It is appropriately sized for the tool's complexity.

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's low complexity (1 parameter), rich annotations, and presence of an output schema, the description is complete. It covers purpose, usage guidelines, behavioral details like capping and sorting, and references to sibling tools, providing all necessary context for an AI agent to use the tool effectively.

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?

Schema description coverage is 100%, with the parameter 'service' well-documented in the schema. The description does not add significant semantic details beyond what the schema provides, such as format or validation rules. However, it implies the service name must be known from jaeger_list_services, which slightly complements 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 clearly states the specific action ('List all operation names') and resource ('Jaeger has seen for a given service'), distinguishing it from siblings like jaeger_list_services (which lists services) and jaeger_search_traces (which searches traces). The purpose is precise and unambiguous.

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?

The description provides explicit guidance on when to use (e.g., discovering operation names for filtering, auditing gRPC methods) and when not to use (e.g., without a specific service, when already knowing operation names). It also references alternatives like jaeger_list_services as a prerequisite, making usage context clear.

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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