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sumo_qa_register_known_good_test_data

Register a known-good test data entry to the local YAML catalogue, preventing duplicates by environment, domain, product/SKU, and scenario.

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
Behavior4/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, consistent with the mutation described. The description adds that it writes to a specific YAML file and detects duplicates, but does not detail permissions, side effects, or error behavior. This adds moderate context beyond the annotations.

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?

Description is well-structured with a clear first sentence, details, an example, and common phrasings. It is front-loaded with the purpose. Slightly long but every part adds value; could be trimmed slightly but overall good.

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?

Tool has one complex parameter and no output schema. Description covers the parameter thoroughly and explains behavior (duplicate detection, file path). It does not mention return value or error cases, but the example implies success. Given constraints, it is fairly complete.

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?

Input schema has only one parameter 'entry' with no property descriptions and 0% schema coverage. The description compensates excellently by providing a full example dict with all common fields (id, environment, domain, etc.) and explicitly instructs to pass as a literal dict, not a YAML string. This adds crucial meaning beyond the schema.

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?

Description explicitly states 'Add or update a known-good test data entry in the local YAML catalogue', clearly indicating the action and resource. It also explains duplicate detection and file location, distinguishing it from sibling tools like sumo_qa_find_test_data and sumo_qa_validate_test_data.

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?

Description includes common natural language phrasings that map to this tool, helping the agent recognize when to use it. It also describes duplicate detection logic. However, it does not explicitly state when not to use this tool or provide alternatives among siblings, so usage guidance is good but not fully comprehensive.

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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