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 first-use-case-pickergit 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/first-use-case-picker)<a href="https://agentmods.dev/skills/adimango/ai-adoption-playbook/first-use-case-picker"><img src="https://agentmods.dev/badge/skills/adimango/ai-adoption-playbook/first-use-case-picker/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/first-use-case-picker"><img src="https://agentmods.dev/badge/skills/adimango/ai-adoption-playbook/first-use-case-picker.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 | $0.00038 | $0.03382 |
| Opus 5 | $0.00019 | $0.01691 |
| Sonnet 5 | $0.00008 | $0.00676 |
| Haiku 4.5 | $0.00004 | $0.00338 |
Grade A, and why
first-use-case-picker 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 — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.
First Use Case Picker
Purpose
Helps a founder choose the right first AI use case for their team. The goal is maximum visible wins with minimum friction — not the theoretically best use case, but the one most likely to actually succeed and shift attitudes. Produces a scored comparison of 2-3 use cases with a clear recommendation.
Core principle: The first use case isn't about productivity. It's about proof. Pick the one that creates believers.
Context Intake
For Department: and Currency:, use the first available source: the current fluency scorecard → adoption.local.md (the department this run covers; by default the one marked (primary) — see CLAUDE.md Local Configuration) → ask the leader (currency defaults to USD).
Flow
digraph usecase {
"Review scorecard + blockers" [shape=box];
"Understand workflow (3-4 Qs)" [shape=box];
"Identify pain points (2-3 Qs)" [shape=box];
"Assess team dynamics (2-3 Qs)" [shape=box];
"Score candidate use cases" [shape=box];
"Present 2-3 options with recommendation" [shape=box];
"Founder picks" [shape=diamond];
"Produce use case brief" [shape=box];
"Route to next skill" [shape=doublecircle];
"Review scorecard + blockers" -> "Understand workflow (3-4 Qs)";
"Understand workflow (3-4 Qs)" -> "Identify pain points (2-3 Qs)";
"Identify pain points (2-3 Qs)" -> "Assess team dynamics (2-3 Qs)";
"Assess team dynamics (2-3 Qs)" -> "Score candidate use cases";
"Score candidate use cases" -> "Present 2-3 options with recommendation";
"Present 2-3 options with recommendation" -> "Founder picks";
"Founder picks" -> "Produce use case brief" [label="chosen"];
"Founder picks" -> "Present 2-3 options with recommendation" [label="none fit, adjust"];
"Produce use case brief" -> "Route to next skill";
}
Process
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 7c6b30405aae
- 12d ago First seen · 262 lines · 38 tokens per session scan A 8d23c11eba98
first-use-case-picker is a skill published in the GitHub repository adimango/ai-adoption-playbook (23 stars, last pushed 5d ago), licensed MIT. It adds 38 tokens to every session and 3,382 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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