feat: rename execute_record_counts_smoke_test to run_connector_readiness_test_report

[aaronsteers]

feat: rename execute_record_counts_smoke_test to run_connector_readiness_test_report

Summary

This PR renames the execute_record_counts_smoke_test function to run_connector_readiness_test_report and significantly enhances its behavior to generate a comprehensive markdown-formatted readiness report instead of returning a structured object. The changes address feedback that LLMs were using this function incorrectly due to its confusing name and improve its utility as a final readiness assessment tool.

Key Changes:

• Function renamed from execute_record_counts_smoke_test to run_connector_readiness_test_report
• Return type changed from MultiStreamSmokeTest object to markdown-formatted string
• Added validation warnings for suspicious record counts (multiples of 10, 1 record, 0 records)
• Added field count validation to ensure records have at least 2 fields
• Enhanced reporting with stream subset information ("X out of Y streams") and detailed per-stream statistics
• Preserved error handling behavior for failed streams

Review & Testing Checklist for Human

• Test with real connector manifests - Verify the markdown output is readable and accurate with actual connectors (not just test data)
• Validate field count warnings - Test with connectors that have records with 1 field vs 2+ fields to ensure the validation logic works correctly
• Check record count warnings - Test edge cases like exactly 10 records, 1 record, 0 records to verify warnings trigger appropriately
• Verify MCP integration - Restart the MCP server and confirm the renamed function is properly registered and callable
• Performance testing - Test with larger datasets to ensure the new include_records_data=True calls don't cause significant slowdowns

Recommended Test Plan:

1. Test the function directly with various connector manifests (Rick and Morty, real connectors)
2. Verify the MCP server recognizes the new function name after restart
3. Check that the chatmode configuration correctly references the new function
4. Test edge cases: empty streams, single-field records, pagination scenarios

---

Diagram

%%{ init : { "theme" : "default" }}%%
graph TD
    ValidationTesting["connector_builder_mcp/<br/>_validation_testing.py"]:::major-edit
    ConnectorBuilder["connector_builder_mcp/<br/>_connector_builder.py"]:::minor-edit
    ChatmodeConfig[".github/chatmodes/<br/>connector-builder-mcp-test-mode<br/>.chatmode.md"]:::minor-edit
    MCPServer["MCP Server<br/>Registration"]:::context
    
    
    ValidationTesting -->|"imports function"| ConnectorBuilder
    ConnectorBuilder -->|"registers as tool"| MCPServer
    ChatmodeConfig -->|"references tool name"| MCPServer
    
    ValidationTesting -->|"calls with include_records_data=True"| StreamTestRead["execute_stream_test_read<br/>(existing function)"]:::context
    ValidationTesting -->|"generates markdown report"| MarkdownOutput["Markdown Report<br/>with warnings"]:::context
    
    subgraph Legend
        L1[Major Edit]:::major-edit
        L2[Minor Edit]:::minor-edit  
        L3[Context/No Edit]:::context
    end
    
    classDef major-edit fill:#90EE90
    classDef minor-edit fill:#87CEEB
    classDef context fill:#FFFFFF

Loading

Notes

• Breaking Change: This is a breaking API change as the return type completely changed from structured object to string
• Performance Impact: The function now calls execute_stream_test_read with include_records_data=True to enable field count validation, which may be slower for large datasets
• TODO Added: Included commented placeholder for future page size validation as requested
• All Tests Pass: Code quality checks and existing unit tests (76 tests) all pass successfully

Session Info: Requested by AJ Steers (@aaronsteers) - Devin Session

Important

Auto-merge enabled.

This PR is set to merge automatically when all requirements are met.

[devin-ai-integration]

Original prompt from AJ Steers

@Devin - Rename this function in the connector builder mcp: 'execute_record_counts_smoke_test'.

The LLM is using it instead of the test read function, and is not using it at the end when it should be. Let's rename it and update it's behavior. Let's call it 'run_connector_readiness_test_report' - and let's update its results to look more like a final readiness report:
1. If failure occurs, we can behave basically the same as now. Simply return the error in a helpful way to help the caller resolve it.
2. Set the max records default to 10000 per stream. (More likely to give helpful data if we actually reach the end of the streams.)
3. If a subset of streams are selected, report back we ran the report "for X out of total Y streams".
4. If things run successfully without error, we should return a markdown-formatted results report.
5. For each stream tested:
    a. Records Extracted. How many records were retrieved for the stream.
    b. Records Count Warnings. Warn if records extracted are a multiple of 10, a multiple of page size, 1, or 0. This warning does not necessarily mean the stream is broken, but it does mean the counts are suspect and should be raised as a warning.
    c. Page Size Correct. TODO (don't implement but add a commented-out code snippet with this instruction): If a page_size arg is specified, but the pages aren't coming back in increments of that size. If page_size is not specified, we can ignore/skip this check.
    d. Does each stream have records with at least 2 fields. 
    e. Probably more tests we can add later...

[devin-ai-integration]

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[github-actions]

PyTest Results (Full)

0 tests  ±0   0 ✅ ±0   0s ⏱️ ±0s
0 suites ±0   0 💤 ±0 
0 files   ±0   0 ❌ ±0 

Results for commit f87cc68. ± Comparison against base commit 1db9be4.

♻️ This comment has been updated with latest results.

[github-actions]

PyTest Results (Fast)

0 tests  ±0   0 ✅ ±0   0s ⏱️ ±0s
0 suites ±0   0 💤 ±0 
0 files   ±0   0 ❌ ±0 

Results for commit f87cc68. ± Comparison against base commit 1db9be4.

♻️ This comment has been updated with latest results.

[devin-ai-integration]

Thanks for the feedback @aaronsteers! You're absolutely right about the performance concern with include_records_data=True.

I've reverted back to include_records_data=False and temporarily disabled the field count validation until we implement the include_record_stats functionality you described.

The include_record_stats approach with basic property statistics (num_properties, types, null counts) is much more efficient than loading full record data. Should I implement this new include_record_stats parameter as part of this PR, or would you prefer to handle that in a separate PR?

For now, the function provides:

• ✅ Record count warnings (multiples of 10, 1 record, 0 records)
• ✅ Stream subset reporting
• ✅ Markdown formatted output
• ⏸️ Field count validation (disabled until include_record_stats is available)

All other functionality remains as requested.