v1.0.0
First downloadable release of ai-model-regression-behavioral-drift-prevention-rules-f18c40e4.
Developer ToolsQ/88 · Quality reviewed
AI Model Regression & Behavioral Drift Prevention Rules
$29.99One-time purchase
A production-grade Cursor rules package and evaluation harness configuration designed to prevent code generation regressions, benchmark LLM outputs, and enforce deterministic guardrails across model updates.
- Current version
- 1.0.0
- Files included
- 11
- Digital delivery
- Instant download
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Built to save a real afternoon
/01
Pin the model, the prompt and the decoding parameters
/02
Output contracts that refuse an unknown enum instead of defaulting
/03
Golden sets that survive a legitimate prompt improvement
/04
Nightly drift detection, so you do not learn it from a customer
/05
An evaluation harness in about 150 lines, not a platform
What is included
AI Model Regression & Behavioral Drift Prevention Rules
ANTI-PATTERNS.mdFILE/01
CHANGELOG.mdFILE/02
EVAL-HARNESS.mdFILE/03
LICENSE.mdFILE/04
README.mdFILE/05
fr/README.mdFILE/06
metadata/product.jsonFILE/07
rules/00-model-pinning.mdcFILE/08
rules/10-output-contracts.mdcFILE/09
rules/20-golden-tests.mdcFILE/10
rules/30-drift-detection.mdcFILE/11
Requirements
- An application that calls a hosted or self-hosted LLM at runtime
- The ability to record inputs and outputs for a sample of those calls
- CI that can run a job on a schedule, not only on push
Digital delivery
Secure download available after payment confirmation.
Practical license
Use and adapt the files in your own projects.
Versioned files
A clear changelog is included in every package.
Version history
Good questions, straight answers.
Does this name specific model versions?+
No, deliberately. A document listing current model identifiers is wrong within a quarter, and a rule citing a deprecated snapshot teaches the reader to discount the rest. The rules are provider-neutral.
Is it tied to a language or framework?+
No. The harness examples are Python and the design translates directly. The Cursor rules are plain .mdc files; the same content works in CLAUDE.md, AGENTS.md or Copilot instructions.
We already have tests. Why would this catch anything?+
Because drift does not change your code. Your suite stays green while the model underneath returns different output. Six of the seven failures documented in the pack were invisible to a green test suite.
How large does the golden set need to be?+
Thirty to a hundred hand-written cases built from real production inputs. Detection power flattens quickly past that; the nightly schedule matters far more than the case count.
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