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sumo-qa

by sumithr
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sumo_qa_register_known_good_test_data

Register or update reusable known-good test data in a local YAML catalogue, with duplicate detection by environment, domain, and scenario. Save validated fixtures for team reuse.

Instructions

Add or update a known-good test data entry in the local YAML catalogue.

Detects duplicates by environment + domain + product/SKU + scenario overlap. Writes to knowledge/test_data/<domain>/known_good.yaml.

Arg shape — pass entry as a literal dict, NOT a YAML string. Example:

sumo_qa_register_known_good_test_data(entry={
    "id": "billing-overdue-invoice-001",
    "environment": "staging",
    "domain": "billing",
    "scenario_tags": ["overdue_invoice", "dunning_eligible"],
    "known_valid_for": ["dunning workflow testing"],
    "constraints": ["Reset overdue flag after test."],
    "owner": "billing-platform",
    "last_validated_at": "2026-05-16T09:00:00Z",
    "confidence": "high",
    "source": "qa-curated",
    "notes": "Overdue invoice usable for dunning-flow testing.",
})

Common natural-language phrasings that map to this tool: "save this as known-good test data", "register this fixture so the team can reuse it", "promote this record to known-good", "update the validated timestamp on entry X", "add this record to the catalogue".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.42.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the description adds real value by disclosing duplicate detection (environment + domain + product/SKU + scenario overlap) and the exact write target path. It stops short of explaining what happens on an overwrite or what the return looks like.

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?

Front-loaded with purpose, then behavior, then usage phrasings, then the arg shape example. The example is long but earned given 0% schema coverage; a minor tightening of the phrasing list is possible but nothing is wasted.

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

Completeness4/5

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

For a single-param write tool with no output schema, the description supplies the operation, the dedup logic, the target file, and a full example payload — enough to call it correctly. Return-value behavior is the only real omission.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the single param is a free-form nested object, so the description carries the full burden — and it does so with a complete literal dict example plus the explicit warning to pass a dict rather than a YAML string. This is exactly the compensation the low coverage requires.

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?

States a specific verb+resource: 'Add or update a known-good test data entry in the local YAML catalogue.' It is clearly distinguishable from siblings like sumo_qa_find_test_data or sumo_qa_validate_test_data, and the write-vs-read distinction is immediate.

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?

Provides a list of natural-language phrasings that map to this tool ('save this as known-good test data', 'promote this record to known-good'), which meaningfully aids routing. It does not, however, name an alternative or state when NOT to use it (e.g., vs. load_catalogue_entry or validate_test_data).

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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