Telemetry Machine

Run surface

run_surface

Read-only

Find the field values most over-represented in a selection of spans or logs compared with the rest. Kubernetes pod and node metrics compare too: each event gets what its pod and node reported in the minute it happened, such as the pod's CPU or memory against its limit.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "run_surface"
  }
}

Input Schema

Name	Required	Description
`slo`	No	An SLO id or name: explains its failing events.
`since`	No	Start. Default: 1h.
`until`	No	End: a duration ago or ISO 8601. Default: now.
`where`	No	A SQL condition that narrows both the selection and the baseline, e.g. to one service.
`fields`	No	Only compare these fields.
`dataset`	No	Required unless you pass `slo`.
`selection`	No	A SQL condition picking the events to explain, e.g. "status_code = 2" or "duration_ns > 1e9". Give this or slo.
`max_fields`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 7, 2026

changedInput schema / properties / slo / description

Previous value: -"An SLO id or name, from get_slos: explains its failing events."New value: +"An SLO id or name: explains its failing events."

First observedOct 30, 2026

TDQS

B3.4/5.0

Behavior3/5

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

The readOnlyHint and openWorldHint annotations already establish the safety profile. The description adds useful non-obvious behavior about Kubernetes pod/node metric enrichment, but it does not describe result shape, statistical method, computational limits, or other operational constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose is front-loaded in the first sentence, and the second sentence adds useful Kubernetes-specific context without excess prose. The phrase 'compare too' is slightly compressed/awkward, but overall the description is efficient.

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

Completeness3/5

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

For an 8-parameter analytical tool with conditional dataset/slo requirements and no output schema, the description covers the core purpose and metric enrichment but omits return format, defaults, and clearer parameter routing. It is adequate but leaves notable gaps.

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 high at 88%, so most parameters are already documented in the schema. The description adds conceptual context about selection versus baseline and Kubernetes enrichment, but it does not clarify parameter syntax, defaults, or the undocumented max_fields parameter beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb, 'Find,' and a specific resource, 'field values most over-represented,' with the comparison group (selection vs. rest) and supported data types. It is substantively distinguishable from generic siblings like run_query or get_field_values, although it does not explicitly name an alternative.

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?

It implies the tool is used to explain a selected subset relative to a baseline, including Kubernetes metric cases, but it gives no explicit when-to-use/when-not guidance or routing to alternatives such as run_query or get_field_values. The agent must infer the intended usage context.

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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