ai-for-change-management
Reusable Windsurf rules and Cursor agent skill files for cross-project AI-assisted development
Install / Use
npx skills add Ryukijano/agent-skills --skill ai-for-change-managementInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Tags
Our assessment of ai-for-change-management
ai-for-change-management scores 53/100 on our quality scale, 4224th of 4,595 Development & Engineering skills we index.
Its SKILL.md is 1.9 KB long, well organised into 10 sections with 1 code example: moderately detailed.
It has no GitHub stars yet, so there is no community track record; judge it on its content.
Maintenance, license and trust
- We could not determine when the repository was last updated.
- Our last check on 2026-10-20 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 68/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
ai-for-change-management compared with similar skills
All 4 of these similar skills score higher than ai-for-change-management; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| ai-for-change-management (this skill)by Ryukijano | 53 | 0 | — | SKILL.md |
| taste-skillby Leonxlnx | 100 | 101.6k | 3d ago | CLAUDE.md |
| ai-job-searchby ai-job-search-dev | 100 | 64.0k | 2d ago | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 44.0k | 3d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 31d ago | SKILL.md |
Frequently asked questions
- How do I install ai-for-change-management?
- Run
npx skills add Ryukijano/agent-skills --skill ai-for-change-management. The install tabs above show the steps for each supported agent. - Which AI agents does ai-for-change-management work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is ai-for-change-management safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 68/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is ai-for-change-management still maintained?
- We could not determine when the repository was last updated.
Skill content
View source on GitHubAI for Change Management
Description
Use AI to leading organizational change, tracking adoption, personalize enablement, or tailoring communications to stakeholder segments.
When to use
You are leading organizational change, tracking adoption, personalizing enablement, or tailoring communications to stakeholder segments.
Usage
- Sense stakeholder sentiment and readiness.
- Map interventions to ADKAR or Kotter stages.
- Personalize training and nudges by role.
- Generate targeted communications and FAQs.
Steps
- Sense stakeholder sentiment and readiness.
- Map interventions to ADKAR or Kotter stages.
- Personalize training and nudges by role.
- Generate targeted communications and FAQs.
- Measure adoption and engagement lift.
- Deploy in client engagements, capture requirements from discovery calls, and measure time-to-insight and decision quality (Task-GenAI Fit-style).
Code pattern
from sklearn.ensemble import RandomForestClassifier
# Predict employee readiness for a change initiative
X = df[["tenure", "prior_change_exposure", "sentiment_score", "manager_support"]]
y = df["ready"]
clf = RandomForestClassifier(class_weight="balanced", random_state=42).fit(X, y)
Tuning notes
- Anchor AI output in change-management frameworks like ADKAR or Kotter.
- Protect employee privacy and avoid surveillance perceptions.
- Validate sentiment models with qualitative feedback and focus groups.
- Pair AI-generated content with human oversight for tone and trust.
Verification
- Classify stakeholder sentiment and compare to survey results.
- Build a readiness model and validate against actual adoption outcomes.
- Test personalized communication and measure engagement lift.
References
- https://arxiv.org/abs/2510.19997
- https://arxiv.org/abs/2411.08693
- https://doi.org/10.1177/00218863231168974
- https://www.inderscience.com/info/inarticle.php?artid=132074
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.