[BUG] Data Integrity Failure in Literal Value Processing

Environment

• Platform (select one):
• Other: Claude Code (Anthropic CLI)
• Claude CLI version: 1.0.70 (Claude Code)
• Operating System: Ubuntu
• Terminal: SSH via MobaXTerm (Windows 11)

Bug Description

Language model fails to preserve user-specified literal values during command generation, leading to data corruption in database operations. The model treats user-provided
literals as content to be probabilistically generated rather than as immutable constants to be preserved exactly.

Steps to Reproduce

1. Provide instruction containing a specific literal identifier (e.g., "Remove callsign W4NHL from the vol table")
2. Request database operation using that identifier
3. Observe model generates syntactically valid but incorrect identifier based on training data patterns (e.g., changes "W4NHL" to "WH4NHL")
4. Model proceeds with operation on wrong data despite verification queries showing no matching records
5. Model reports "success" for operations that accomplished nothing

Expected Behavior

• User-specified literals should be extracted and preserved exactly as provided
• Only command syntax should be subject to probabilistic generation
• Verification queries returning zero results should halt subsequent operations and prompt for clarification
• Model should distinguish between literal data requiring exact preservation and syntax requiring generation

Actual Behavior

• Model regenerates user-provided literals during command construction
• Substitutes statistically probable alternatives from training data patterns
• Ignores verification query results showing no matching records
• Proceeds with DELETE operations guaranteed to be no-ops
• Reports "success" based on zero-count verification that matches pre-operation state
• Exhibits confident behavior throughout error sequence, making detection difficult

Additional Context

Technical Analysis: The issue suggests fundamental failure to distinguish between literal data (user-specified values) and generated syntax (command structure). This indicates
the model may be treating user data as prompts for further generation rather than constants to be preserved.

Impact Severity: Critical for data integrity - silent corruption of user-specified identifiers in database operations undermines reliability for any data manipulation tasks.

Pattern Recognition: Generated incorrect values follow valid patterns for the data type (both "W4NHL" and "WH4NHL" are legitimate amateur radio callsign formats), making
errors appear plausible and harder to detect.

Logic Chain Failure: Model executes: Query → No results found → Proceed with DELETE anyway → Confirm zero count → Declare success, showing failure in conditional logic
processing.