Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add geledek/enterprise-ai-transformation-skills/plugin install enterprise-ai-transformation-skillsWrote 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.
[](https://agentmods.dev/skills/geledek/enterprise-ai-transformation-skills/people-readiness-conversation)<a href="https://agentmods.dev/skills/geledek/enterprise-ai-transformation-skills/people-readiness-conversation"><img src="https://agentmods.dev/badge/skills/geledek/enterprise-ai-transformation-skills/people-readiness-conversation/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.
<a href="https://agentmods.dev/skills/geledek/enterprise-ai-transformation-skills/people-readiness-conversation"><img src="https://agentmods.dev/badge/skills/geledek/enterprise-ai-transformation-skills/people-readiness-conversation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00154 | $0.01975 |
| Opus 5 | $0.00077 | $0.00988 |
| Sonnet 5 | $0.00031 | $0.00395 |
| Haiku 4.5 | $0.00015 | $0.00198 |
Grade A, and why
people-readiness-conversation 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 12d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
People — AI Leadership Readiness Conversation
Surface the people and leadership gaps that will block AI progress, regardless of how good the technology is. Four roles. Specific diagnostic questions. Actionable gap report.
BCG 2026: 70% of AI value comes from People. The 88/25 manager role-modeling gap is the most actionable single lever. Most organizations that under-perform on AI have a technology that works and people who don't.
Per-layer rating vocabulary (stable output contract): STRONG / DEVELOPING / CRITICAL-GAP.
Role 1: CEO Readiness — Champion vs. Cheerleader
The gap: a cheerleader endorses AI publicly; a champion personally owns AI outcomes.
McKinsey: firms where the CEO personally owns AI show a 3× performance differential. (Consult mckinsey-3x-senior-ownership.md)
Diagnostic questions (answer with evidence, not aspiration):
- Does the CEO personally own named AI initiatives? (Not "sponsor" them — own them. Is the CEO's name on the initiative, reviewing metrics, accountable for outcomes?)
- Does the CEO review AI initiative metrics at the same cadence as P&L?
- Has the CEO made a public commitment (internally) to a specific, measurable AI goal? (Not "we're all in on AI" — a number, a timeline, a business outcome)
- Has the CEO personally used AI tools in the past 30 days? (Not in a demo — in real work)
- Does the org have an AI strategy ratified by the C-suite? Or is it an IT/data team document?
GAP CLASSIFICATION:
- Cheerleader (endorses without ownership): PRIMARY GAP — nothing else will reach the 3× differential without this
- Aware but not active: SECONDARY GAP — developing
- Champion (personally owns, publicly accountable): PASS
Output: CEO STATUS | EVIDENCE | GAP CLASSIFICATION | SPECIFIC ACTION REQUIRED
Role 2: Manager Readiness — Role-Modeling Gap
The gap: 88% of managers believe AI role-modeling matters. Only 25% do it visibly. (BCG BFFxAI 2026 — consult bcg-manager-modeling.md)
Diagnostic questions:
- In the past month, how many managers have used AI outputs in a team meeting? (Not prepared privately — used publicly)
- In the past month, how many managers have run an AI prompt in front of their direct reports?
- Do managers assign AI-augmented tasks to their teams, and review the AI output together?
- Is AI use part of any manager's performance objective or review?
- What is the manager's stated belief about AI? ("AI will replace jobs" = adoption barrier; "AI is a tool I should model" = alignment)
What ships with it
1 file 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.
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.
- 12d ago First seen · 150 lines · 154 tokens per session scan A 653a0399db96
people-readiness-conversation is a skill published in the GitHub repository geledek/enterprise-ai-transformation-skills (9 stars, last pushed 2mo ago), licensed MIT. It adds 154 tokens to every session and 1,975 once invoked, about $0.0008 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 2026-08-31.
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