# Reflection and Self-Checking — AI Agents and Tool Use

Source: https://www.geekswithgeeks.com/en/ai-agents-mcp/found-reflection

> Have the agent check its work against criteria, preferring checks that code can run.

## Check before you answer

**Reflection** adds a step where the agent reviews its draft or result before finishing: does the answer address the question, do the numbers add up, did the tool really succeed? The strongest checks are executable (run the tests, validate the JSON, re-query the record). A model critiquing itself helps for style and completeness but can repeat its own mistakes.

## Give the critic different information

A reviewer that sees the same context as the writer shares its blind spots. Give the check something new: the original requirements, a checklist, or the real tool output.

**Quiz:** Which self-check is most reliable?

- [ ] Asking "are you sure?"
- [x] Running the tests and reading the result
- [ ] Re-reading the same answer
- [ ] Making the answer longer

*Answer:* Running the tests and reading the result. Executable checks give objective evidence instead of another opinion.