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principia

principia.measures.list

Read-only

List Measure rows. entity_kind filter selects scientific_construct vs operational_metric.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
entity_kindNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
measuresYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds minimal behavioral context beyond the filtering semantics, but this is acceptable for a simple read-only list operation with 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 two short sentences with no filler or repetition. The core operation is front-loaded, and the entity_kind clarification earns its place.

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?

The tool is simple, has an output schema, and annotations cover safety. However, the description omits default behavior when entity_kind is absent and gives no guidance relative to sibling tools, leaving minor gaps for an agent deciding how to invoke it.

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 0%, and the description does compensate for entity_kind by explaining that it selects between scientific_construct and operational_metric. However, it does not add any meaning for limit or offset, although those are fairly self-explanatory from their names and schema bounds.

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 the specific verb 'List' with the resource 'Measure rows' and clarifies the entity_kind filter's two possible values. It is clear, but it does not explicitly distinguish itself from sibling tools such as principia.measures.lookup or principia.constructs.list.

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

Usage Guidelines2/5

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

No explicit when-to-use or alternative routing guidance is provided. The entity_kind hint explains filtering options but does not state when to use this list endpoint instead of a lookup/search sibling, nor what happens if no filter is supplied.

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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