adopt-ai-habit-review

Prepares a quarterly AI habit review with the original need, current evidence against the same definitions, what changed in the tool and the work, and what to keep, simplify, refresh or retire. Use for "run adopt-ai-habit-review", "AI habit review", "quarterly AI adoption review", "people went back to the old way", "is our AI rollout still working", "what should we retire from the AI programme", "refresh our AI training materials", "AI adoption six months later", part of the Claude Guide for AI Adoption Pack by 90n.

What does this entry provide?

adopt-ai-habit-review is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # AI Habit Review ## When To Use The launch was six months ago, the tool has changed three times, and half the team is back to the old way. Nobody has looked si. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding adopt-ai-habit-review to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: GitHub Skill Search
Quality: 58/100
Install method: codex
Repo: polar-bear-org/claude-skills
Repo updated: Oct 30, 2026

Install command

codex skill install polar-bear-org/claude-skills

Install method: codex

Review the upstream source before running this command.

GitHub project

Quality

Repo stars

Repo updated

Unknown

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.

Security signals

Scan coverage: Install metadata and the indexed document body.

Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.

Discovery note

# AI Habit Review ## When To Use The launch was six months ago, the tool has changed three times, and half the team is back to the old way. Nobody has looked since at whether the p

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