Retrieve a detailed span waterfall for a specific AI trace, showing timing, parent-child relationships, and attributes such as model and cache hits.
Get the full span waterfall for one AI trace: every span with timing, parent relationships, and attributes (model, cache hit/miss, similarity scores). Use list_ai_traces to find trace IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| traceId | Yes | Trace ID from list_ai_traces |
Changes observed during successful MCP inspections.
v0.33.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description describes the output structure in detail (spans, timing, parent relationships, attributes). It is transparent about what the tool returns but does not mention additional traits like idempotency or rate limits, which are less critical for a read-only operation.
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?
Two sentences, no filler. The first sentence states purpose and output; the second provides usage context. All content earns its place.
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, the description sufficiently explains return values (spans with timing, parent relationships, attributes). The single parameter is fully described. The tool is simple, and the description covers all necessary context.
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 schema has 100% coverage for a single parameter, so baseline is 3. The description adds context by linking traceId to list_ai_traces, but the schema description already states 'Trace ID from list_ai_traces', so minimal added meaning.
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 verb 'Get' and the resource 'full span waterfall for one AI trace', specifying what is returned (spans with timing, parent relationships, attributes). It distinguishes from sibling tools like list_ai_traces and correlate_ai_trace by focusing on a single trace's detailed spans.
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 explicitly guides the user to 'Use list_ai_traces to find trace IDs', setting a clear prerequisite. However, it does not provide explicit when-to-use vs alternatives beyond this hint, which is acceptable for a straightforward retrieval tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.