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 adimango/ai-adoption-playbook --skill fluency-assessmentgit clone --depth 1 https://github.com/adimango/ai-adoption-playbookWrote 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/adimango/ai-adoption-playbook/fluency-assessment)<a href="https://agentmods.dev/skills/adimango/ai-adoption-playbook/fluency-assessment"><img src="https://agentmods.dev/badge/skills/adimango/ai-adoption-playbook/fluency-assessment/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/adimango/ai-adoption-playbook/fluency-assessment"><img src="https://agentmods.dev/badge/skills/adimango/ai-adoption-playbook/fluency-assessment.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 | $0.00034 | $0.06715 |
| Opus 5 | $0.00017 | $0.03358 |
| Sonnet 5 | $0.00007 | $0.01343 |
| Haiku 4.5 | $0.00003 | $0.00671 |
Grade A, and why
fluency-assessment 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 4d 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 — 497 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Fluency Assessment
Purpose
Quick diagnostic that scores an organization's AI fluency across three pillars: psychological barriers, integration failures, and ownership gaps. Produces a one-page scorecard the leader can act on. This skill MUST run before any other interactive or workflow skill. It's the diagnostic before the prescription.
Core principle: Diagnose before you prescribe. This skill assesses — it does NOT build plans, pick tools, or write board narratives. Those are separate skills.
Time: Under 5 minutes for the quick quiz. Even faster if the leader has existing survey or assessment data. Optional deep-dive available if the leader wants more detail.
Flow
digraph fluency {
"Context (4 Qs)" [shape=box];
"Have existing data?" [shape=diamond];
"Import & map data" [shape=box];
"Gaps in data?" [shape=diamond];
"Fill gaps (targeted Qs)" [shape=box];
"Quick Quiz (11 Qs)" [shape=box];
"Score & produce scorecard" [shape=box];
"Offer team survey" [shape=box];
"Want deep-dive?" [shape=diamond];
"Deep-dive on weakest pillar" [shape=box];
"Route to next skill" [shape=doublecircle];
"Context (4 Qs)" -> "Have existing data?";
"Have existing data?" -> "Import & map data" [label="yes"];
"Have existing data?" -> "Quick Quiz (11 Qs)" [label="no"];
"Import & map data" -> "Gaps in data?";
"Gaps in data?" -> "Fill gaps (targeted Qs)" [label="yes"];
"Gaps in data?" -> "Score & produce scorecard" [label="no"];
"Fill gaps (targeted Qs)" -> "Score & produce scorecard";
"Quick Quiz (11 Qs)" -> "Score & produce scorecard";
"Score & produce scorecard" -> "Offer team survey";
"Offer team survey" -> "Want deep-dive?";
"Want deep-dive?" -> "Deep-dive on weakest pillar" [label="yes, have time"];
"Want deep-dive?" -> "Route to next skill" [label="no, move on"];
"Deep-dive on weakest pillar" -> "Route to next skill";
}
Process
Step 0: Load Configuration
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.
- 4d ago Changed 9d43e22305fc
- 12d ago First seen · 497 lines · 34 tokens per session scan A 9320400fe73a
fluency-assessment is a skill published in the GitHub repository adimango/ai-adoption-playbook (23 stars, last pushed 5d ago), licensed MIT. It adds 34 tokens to every session and 6,715 once invoked, about $0.0002 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 2026-08-30.
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