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.
npx skills add jeremylongworth-source/AgentSkills --skill ai-adoption-plangit clone --depth 1 https://github.com/jeremylongworth-source/AgentSkillsWrote 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/jeremylongworth-source/agentskills/ai-adoption-plan)<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/ai-adoption-plan"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/ai-adoption-plan/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/jeremylongworth-source/agentskills/ai-adoption-plan"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/ai-adoption-plan.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 | $0.00046 | $0.00330 |
| Opus 5.5 | $0.00018 | $0.00132 |
| Sonnet 5.5 | $0.00009 | $0.00066 |
| Haiku 4.5 | $0.00005 | $0.00033 |
Grade A, and why
ai-adoption-plan 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 1mo 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.
What it actually says
AI Adoption Plan
Core Workflow
- Identify target users, workflows, current pain, adoption barriers, incentives, training needs, and change risks.
- Define the adoption path: pilot users, champions, training, support, communication, measurement, and feedback loops.
- Separate productivity goals from role, policy, or workflow redesign.
- Plan enablement artifacts, office hours, support channels, and usage guardrails.
- Define adoption metrics, quality metrics, and review cadence.
- Flag employee-impacting, policy, privacy, security, legal, or people-review needs.
Safety Rules
- Do not recommend employee-impacting changes without people/legal review.
- Do not assume adoption equals value; require metrics and feedback.
- Do not encourage sensitive data use or uncontrolled AI tool adoption.
- Escalate policy, workforce, privacy, security, customer, or regulated-use concerns.
Deliverable Shape
For AI adoption plans, provide:
- Target users and workflows
- Adoption barriers
- Rollout plan
- Training and support plan
- Communication plan
- Metrics and feedback loop
- Governance and review needs
References
- Read
references/ai-adoption-plan-checklist.mdwhen preparing AI rollout, enablement, training, adoption, or change-management plans.
What ships with it
2 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.
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.
- 1mo ago First seen · 46 lines · 46 tokens per session scan A 323165a89ea4
ai-adoption-plan is a skill published in the GitHub repository jeremylongworth-source/AgentSkills (1 stars, last pushed 17d ago), licensed MIT. It adds 46 tokens to every session and 330 once invoked, about $0.0002 per session on Opus 5.5. 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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