Data & Technical specialist
Default Kona assistant
SQL Analyst
Translates questions into robust, reviewable SQL and result interpretation.
When to use it
A focused role with a visible finish line.
Best for: technical and analytics teams that need reproducible analysis, implementation, or quality work.
Expected outcome: an inspectable technical deliverable with assumptions, tests, and reproducible steps.
- A focused sql, database, data task where the expected decision or deliverable is clear.
- Recurring work that benefits from the same answer, assumptions, risks structure each time.
- A team that wants SQL Analyst available in direct chat, inline @mentions, and bounded Workspace tasks.
Configured instruction
“Write dialect-aware, readable SQL with explicit assumptions, joins, time zones, null handling, deduplication, and performance considerations. Explain how to validate the result.”
This instruction is part of the shipped default profile—not a generic prompt assembled for this page.
Workflow
How SQL Analyst approaches the work
Frame the outcome
State the decision, audience, deadline, constraints, and what a useful an inspectable technical deliverable with assumptions, tests, and reproducible steps looks like.
Ground the work
Provide relevant schemas, code, logs, event definitions, environments, constraints, and expected behavior. Label supplied facts, working assumptions, and unresolved unknowns.
Build the contracted output
SQL Analyst follows its markdown output contract and covers answer, assumptions, risks, next evidence.
Verify before use
Run the profile's quality checks, expose evidence gaps, and route high-impact low-risk conclusions to human review.
Capabilities
What the profile can use
- Knowledge grounding
- Structured deliverables
- Verification pass
- Analysis and code
Enabled tool families: code. Runtime availability still depends on account configuration, permissions, and the task.
Output contract
What a complete response must contain
The contract improves consistency; it does not make an answer automatically correct. Kona still marks assumptions, evidence gaps, and review requirements.
Prompt examples
Start with context and a decision
Prompt example
Act as my SQL Analyst. Write dialect-aware, readable SQL with explicit assumptions, joins, time zones, null handling, deduplication, and performance considerations. Explain how to validate the result. Start by listing the missing inputs that would materially change the result.
Prompt example
Use the SQL Analyst workflow for this sql task: [describe the situation]. Audience: [who will use it]. Constraints: [time, budget, policy, or data]. Return answer, assumptions, risks, next evidence.
Prompt example
Review this draft as the SQL Analyst: [paste draft]. Check it against the stated evidence, identify unsupported claims or missing assumptions, and return a prioritized correction list.
Put SQL Analyst to work.
Use the default profile or fork it into a version your team controls.