Data Quality Agent · First external AI review

Review the LLM agent design in 8-15 minutes

Give the first AI/ML systems reviewer one focused public page for inspecting the agent design and submitting countable review evidence without exposing private data.

Submit AI review Open tracking issue

Copy-ready ask

Could you review my Data Quality Agent as an AI Engineer project? The short path now includes the LLM value comparison that shows adaptive strategy selection beating a fixed checklist across 14 scenarios. Public review form: https://sunnnn2005.github.io/data-quality-agent/first-ai-reviewer-ask.html

Slot: review_slot_07 · Status: not_sent

app/agent.py

Agent loop and tool routing

Does the LLM choose tools based on evidence instead of following a fixed script?

docs/agent-safety-boundaries.md

Safety boundaries

Are read-only data access, query limits, and redaction rules clear enough?

docs/llm-agent-checklist-verdict.md

Evidence-backed reporting

Are facts, inferences, limitations, and resume-safe claims separated?

docs/llm-value-comparison.md

Adaptive strategy value

Does the 14-scenario comparison make the agentic strategy selection more credible than a fixed workflow?

docs/real-model-evidence-capture.md

Real model evidence gate

Would the telemetry be enough to verify a real OpenAI-compatible run later?

Review questions

  • What is the strongest AI Engineer signal in this project?
  • What is the least credible or most missing part of the agent design?
  • Which file or behavior should be improved before this is resume-strong?
  • Would you count this as an LLM agent project, and why?

Required public evidence

  • reviewer is not the repository owner
  • at least one inspected file, page, command, or behavior is named
  • one concrete AI-agent strength or gap is described
  • I give permission for this public issue to be counted as project review evidence.
  • no private data, secrets, customer records, private emails, addresses, API keys, or production rows

Counting boundary

This page can support the first AI Engineer review only after a real non-owner reviewer submits a public, redacted GitHub issue with permission to count. A sent message or page view does not count.

I give permission for this public issue to be counted as project review evidence.