ai-adoption-change-management

ai-adoption-change-management is a skill for Claude Code from PranavNagrecha/AwesomeSalesforceSkills. It costs 88 tokens per session (3,629 once invoked), scanned A, original, no licence file.

A guide to the people and process side of rolling out Agentforce or Einstein AI features. It covers building trust, training users, collecting feedback, and measuring adoption.

In plain words
What is it for?
Use it to plan AI training, gather structured user feedback, build trust, and measure adoption after launch.
Why use it?
It helps organizations address user concerns and learn whether an AI rollout is being accepted and used.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the sfskills plugin — 74 skills, 69 commands, 50 agents shipped together

Good fit Use it to plan AI training, gather structured user feedback, build trust, and measure adoption after launch.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pranavnagrecha/awesomesalesforceskills/ai-adoption-change-management
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add PranavNagrecha/AwesomeSalesforceSkills --skill ai-adoption-change-management
Clone the repo
git clone --depth 1 https://github.com/PranavNagrecha/AwesomeSalesforceSkills

Made for: Claude Code.

Or install sfskills, the plugin that ships this one along with the rest of its 74 skills, 69 commands, 50 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ai-adoption-change-management

README.md
[![agentmods](https://agentmods.dev/badge/skills/pranavnagrecha/awesomesalesforceskills/ai-adoption-change-management/github.svg)](https://agentmods.dev/skills/pranavnagrecha/awesomesalesforceskills/ai-adoption-change-management)
Your own site
<a href="https://agentmods.dev/skills/pranavnagrecha/awesomesalesforceskills/ai-adoption-change-management"><img src="https://agentmods.dev/badge/skills/pranavnagrecha/awesomesalesforceskills/ai-adoption-change-management/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ai-adoption-change-management

Your own site · 80×15
<a href="https://agentmods.dev/skills/pranavnagrecha/awesomesalesforceskills/ai-adoption-change-management"><img src="https://agentmods.dev/badge/skills/pranavnagrecha/awesomesalesforceskills/ai-adoption-change-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,629 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00088 $0.03629
Opus 5 $0.00044 $0.01814
Sonnet 5 $0.00018 $0.00726
Haiku 4.5 $0.00009 $0.00363

Measured 9d ago against content hash e6168913907a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ai-adoption-change-management scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/check_ai_adoption_change_management.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/admin/ai-adoption-change-management/SKILL.md · 238 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 238 lines · 88 tokens per session scan A e6168913907a

Subscribe to this mod's changes

ai-adoption-change-management is a skill published in the GitHub repository PranavNagrecha/AwesomeSalesforceSkills (17 stars, last pushed 8d ago), with no licence file. It adds 88 tokens to every session and 3,629 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

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