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Test spec

test_spec
Read-onlyIdempotent

Run a spec's embedded test cases (or ad-hoc given->expect cases) through the real reactive pipeline in a throwaway runtime, returning pass/fail plus per-field failures (path, expected, actual). Use this to certify domain behavior before create_model / promotion.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specYesThe ModelSpec whose tests to run.
testsNoOptional list of test cases (each with 'given' inputs and 'expect' outputs); omit to run the spec's own embedded 'tests'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalNoTotal test cases run.
failedNoCases that failed.
passedNoCases that passed.
resultsNoPer-case results (with per-field failures on failure).

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: tests run in a throwaway runtime through the real reactive pipeline, and the result includes pass/fail plus per-field path/expected/actual failures. No contradiction 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?

Two sentences, front-loaded with the core behavior and return value, then the usage context. Every clause earns its place with no fluff or schema repetition.

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 output schema exists, the annotations fully cover safety semantics, and the input schema documents the parameters, the description provides the missing behavioral framing: throwaway runtime, real pipeline, test certification purpose, and failure reporting shape. Nothing critical is omitted.

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 coverage is 100% and both parameters have descriptions, so the baseline is 3. The description's 'embedded test cases (or ad-hoc given->expect cases)' roughly restates what the schema already documents for spec.tests and the tests parameter, without adding meaningful parameter-level detail.

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 states a specific action — running embedded or ad-hoc test cases through the real reactive pipeline — and clearly identifies the tool as a certification step before create_model/promotion. This distinguishes it from validation and modeling tools, even without naming siblings.

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

Usage Guidelines4/5

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

The description gives explicit context: use this to certify domain behavior before create_model or promotion. It does not mention when not to use it or name alternative sibling tools, so it stops short of full exclusion guidance.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but get_audit explicitly subsumes get_history and explain, and get_state with paths overlaps get_field, creating minor selection ambiguity. The detailed descriptions help, but an agent could still reach for the wrong getter.

Naming Consistency4/5

Naming is overwhelmingly consistent: snake_case with verb_noun structure and coherent get_/create_/delete_ clusters. Minor deviations like bare verbs (mutate, explain, restore, snapshot) and eval instead of evaluate prevent a perfect score.

Tool Count3/5

27 tools is above the comfortable range and feels heavy, especially with several overlapping audit/state getters that could be consolidated. That said, the domain is broad enough that the count is defensible, so it is heavy but not chaotic.

Completeness4/5

The tool set covers the full model lifecycle well: create, validate, test, mutate, evolve, read, delete, plus snapshot/restore, audit, blobs, views, library, and expression evaluation. Minor gaps like explicit export/import or separate view-management tools are workable around.