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 sruthir28/enterprise-ai-skills --skill ai-use-case-scorergit clone --depth 1 https://github.com/sruthir28/enterprise-ai-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/sruthir28/enterprise-ai-skills/ai-use-case-scorer)<a href="https://agentmods.dev/skills/sruthir28/enterprise-ai-skills/ai-use-case-scorer"><img src="https://agentmods.dev/badge/skills/sruthir28/enterprise-ai-skills/ai-use-case-scorer/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/sruthir28/enterprise-ai-skills/ai-use-case-scorer"><img src="https://agentmods.dev/badge/skills/sruthir28/enterprise-ai-skills/ai-use-case-scorer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00091 | $0.01624 |
| Opus 5 | $0.00046 | $0.00812 |
| Sonnet 5 | $0.00018 | $0.00325 |
| Haiku 4.5 | $0.00009 | $0.00162 |
Grade A, and why
ai-use-case-scorer 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Use-Case Scorer
Turns "I should be using AI more" into "here are the 3 things I'm building this week, here's why, and here's what I'm explicitly NOT doing." Built for the individual IC trying to figure out where to deploy AI in their own work.
Why this exists
Most AI-use-case lists are theater — pages of "potential" use cases that never get built. This skill compresses the call: of the use cases on your list, which 2–3 actually pay off this month, and which to ignore.
Built for the IC. If you're rolling AI out to a 50-person team, this is the wrong framework — that's change management, not personal scoring.
Scoring framework: V × F × S
Each use case scored on three axes (1–5 scale).
Value — what's the upside?
| Score | Time saved | Quality lift | Strategic fit |
|---|---|---|---|
| 5 | >5 hrs/wk | Visibly better output | Hits a top-3 personal goal |
| 3 | 1–5 hrs/wk | Modest improvement | Adjacent to a goal |
| 1 | <1 hr/wk | Marginal | Not connected to goals |
Value score = round(avg of three sub-scores)
Feasibility — can you actually do it?
| Score | Tool maturity | Your skill / time |
|---|---|---|
| 5 | Mature off-the-shelf skill or tool exists | Ship in one sitting |
| 3 | Tools exist but need glue | A weekend project |
| 1 | Requires custom dev / new infra | Multi-week build |
Feasibility score = round(avg of two sub-scores)
Safety — what could go wrong? (Inverted: higher = safer)
| Score | Quality risk | Data risk | Trust risk |
|---|---|---|---|
| 5 | Errors easy to catch | No sensitive data | Team comfortable with AI |
| 3 | Errors land in internal docs | Some PII / internal data | Mixed signals from team |
| 1 | Errors land in customer / exec face | Confidential / regulated | Active resistance |
Safety score = round(avg of three sub-scores)
Final score = V × F × S
Range: 1 (don't bother) to 125 (perfect).
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 · 140 lines · 91 tokens per session scan A 2d1b322b2077
ai-use-case-scorer is a skill published in the GitHub repository sruthir28/enterprise-ai-skills (139 stars, last pushed 11d ago), licensed MIT. It adds 91 tokens to every session and 1,624 once invoked, about $0.0005 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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