Prompt Reasoning

[galshubeli]

Summary by CodeRabbit

• Improvements
  • Enhanced SQL query generation with more explicit guidance for the analysis process.
  • Improved handling of follow-up questions to ensure SQL queries are generated only when appropriate.

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📝 Walkthrough

Walkthrough

The analysis agent's embedded prompt was restructured to replace the "instructions_comments" field with a new "query_analysis" field and refine the "sql_query" field description with more explicit SQL generation constraints and continuation logic guidance.

Changes

Cohort / File(s)	Summary
Agent Prompt Restructuring api/agents/analysis_agent.py	Replaced "instructions_comments" JSON field with "query_analysis" containing detailed SQL translation guidance. Updated "sql_query" field description to be more explicit about single query generation and continuation handling.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

Poem

🐰 A prompt refined, instructions clearer,
"query_analysis" brings the SQL nearer,
No more ambiguous, no more to parse,
One valid query—the agent's new task!
Hopping forward with structured grace,
Better guidance finds its place. 🎯

🚥 Pre-merge checks | ✅ 2 | ❌ 1

❌ Failed checks (1 inconclusive)

Check name	Status	Explanation	Resolution
Title check	❓ Inconclusive	The title 'Prompt Reasoning' is vague and non-descriptive. While it may relate to changes in prompt structure within the analysis agent, it doesn't clearly convey what was changed or why.	Consider a more specific title such as 'Replace instructions_comments with query_analysis in analysis agent' or 'Refactor prompt structure for SQL query analysis' to better communicate the main change.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

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[railway-app]

🚅 Deployed to the QueryWeaver-pr-367 environment in queryweaver

Service	Status	Web	Updated (UTC)
QueryWeaver	✅ Success (View Logs)	Web	Jan 7, 2026 at 2:47 pm

[github-actions]

Dependency Review

✅ No vulnerabilities or license issues or OpenSSF Scorecard issues found.

Scanned Files

None

[galshubeli]

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[Copilot]

Pull request overview

This PR refines the analysis agent's prompt instructions to improve SQL query generation accuracy. The changes focus on replacing a vague "instructions_comments" field with a structured "query_analysis" field that enforces explicit reasoning about query construction decisions.

Key Changes:

• Replaced the open-ended "instructions_comments" field with a detailed "query_analysis" field that requires structured reasoning about columns, grain, metrics, aggregation, ranking, and filters
• Updated the "sql_query" field description to emphasize generating a single valid SQL query and clarified the rules for using previous answers

[coderabbitai]

Actionable comments posted: 1

Caution

Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (1)

api/agents/analysis_agent.py (1)

258-258: Update reference to removed field.

This line references "instructions_comments" which was removed from the JSON schema (replaced by "query_analysis" at line 285). The model should be instructed to use the "explanation" field for commenting on instruction application issues.

📝 Proposed fix

-            - If you CANNOT apply instructions in the SQL, explain why under
-              "instructions_comments", "explanation" and reduce your confidence.
+            - If you CANNOT apply instructions in the SQL, explain why under
+              "explanation" and reduce your confidence.

🤖 Fix all issues with AI agents

In @api/agents/analysis_agent.py:
- Line 285: The long dictionary string value for the "query_analysis" key in
api/agents/analysis_agent.py exceeds pylint's 100-character line limit; split
the string into multiple shorter pieces (using implicit concatenation inside
parentheses or separate quoted strings joined with +) so the text content
remains identical but no single source line exceeds 100 characters, and update
the "query_analysis" entry accordingly (locate the "query_analysis" key in the
dict/structure in analysis_agent.py and break its value into multiple lines).

📜 Review details

Configuration used: defaults

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 578a6ab and c8f5a0a.

📒 Files selected for processing (1)

• api/agents/analysis_agent.py

🧰 Additional context used

📓 Path-based instructions (1)

**/*.py

📄 CodeRabbit inference engine (.github/copilot-instructions.md)

All Python code should pass pylint (use make lint)

Files:

• api/agents/analysis_agent.py

🪛 GitHub Actions: Pylint

api/agents/analysis_agent.py

[error] 285-285: pylint: C0301 Line too long (781/100) detected at line 285. Exit code 16 from the pylint run: 'pipenv run pylint $(git ls-files '*.py')'.

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)

• GitHub Check: test

🔇 Additional comments (1)

api/agents/analysis_agent.py (1)

289-291: LGTM! Clearer SQL query instruction.

The updated description provides more explicit guidance on SQL generation, clarifying that exactly one valid SQL query should be generated and that previous answers should only be used for continuation questions. This improves the prompt's clarity.

[overcut-ai]

Summary:

• Major: 1

Key themes:

• Prompt prose still references the removed instructions_comments field, so the agent will emit an output schema the downstream parser no longer accepts.

Next steps:

• Reconcile the narrative instructions with the new query_analysis / sql_query schema (or restore instructions_comments) so the agent output contract remains self-consistent.