LLM Campaign Drift Gate

by kennethkhoocy

LLM Campaign Drift Gate is a Quality skill for Claude Code, published by kennethkhoocy in applied-micro-skills.

48 stars0 forkson kennethkhoocy/applied-micro-skillsAdded 2026/08/11Repository updated 2026/07/22

View source on GitHub Download repo ZIP

applied-microeconomicsclaude-codeclaude-skillscodexcodex-skillsempirical-research

Install in seconds

Install LLM Campaign Drift Gate

Copy LLM Campaign Drift Gate into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/kennethkhoocy/applied-micro-skills/tree/main/plugins/applied-micro/skills/llm-campaign-drift-gate ~/.claude/skills/llm-campaign-drift-gate

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/kennethkhoocy/applied-micro-skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: plugins/applied-micro/skills/llm-campaign-drift-gate/SKILL.md in kennethkhoocy/applied-micro-skills
Installs to: ~/.claude/skills/llm-campaign-drift-gate
Collection: One of 25 skills cataloged from this repository
Category: Quality — 1354 skills

What LLM Campaign Drift Gate does

Verifies LLM model consistency before resuming a paused batch-scoring campaign by comparing fresh responses to cached outputs. Detects silent model drift from alias repoints or serving revisions to prevent splicing different model versions into one measure.

LLM Campaign Drift Gate is cataloged under Quality on DirSkills. LLM Campaign Drift Gate comes from a repository tagged applied-microeconomics, claude-code, claude-skills, codex and codex-skills.

Documentation

README

Excerpt

LLM Campaign Drift Gate

Problem

Batch-scoring campaigns (exposure measures, classifiers, extraction runs) call provider aliases that can be silently repointed to a new model at any time. Resuming a half-finished campaign after the alias moves splices two different scorers into one variable, with the version boundary correlated with whatever orders the chunks (time, firm id) — a silent confound. Providers can also RETIRE the old model entirely, making the original campaign uncompletable.

Context / Trigger Conditions

Resuming a scoring run more than ~a day after its last paid chunk
"Top up credits and finish the run" requests
Any incremental scoring against an existing response cache
Symptom of a missed gate: a step-change in scores at a resume boundary

Solution

This is the opening of the README. Read the full README on GitHub.

Commands LLM Campaign Drift Gate provides

Slash commands named in this skill’s SKILL.md, listed in the order they first appear.

/models

Frequently asked about LLM Campaign Drift Gate

What else does kennethkhoocy publish alongside LLM Campaign Drift Gate?
LLM Campaign Drift Gate is one of 25 skills that DirSkills catalogs from kennethkhoocy/applied-micro-skills, the repository it ships in. Its siblings there include Adversarial Empirical Review, Annotator Input Parity Check and AsyncOpenAI Concurrency Fix. Each one is a separate skill with its own page in this directory, installs the same way LLM Campaign Drift Gate does, and is maintained by kennethkhoocy in that same repository. The rest of the collection is listed on the kennethkhoocy/applied-micro-skills page.
How does LLM Campaign Drift Gate compare to other Quality skills?
LLM Campaign Drift Gate ranks #1298 by stars among the 1354 Quality skills in this catalog. The most-starred ones next to it are Benchmark, Benchmark Optimization Loop and API Design Patterns. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of LLM Campaign Drift Gate against them. Open each page to compare what they document and how they install.