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 fatihguner/foreman --skill ai-emotional-intelligencegit clone --depth 1 https://github.com/fatihguner/foremanWrote 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/fatihguner/foreman/ai-emotional-intelligence)<a href="https://agentmods.dev/skills/fatihguner/foreman/ai-emotional-intelligence"><img src="https://agentmods.dev/badge/skills/fatihguner/foreman/ai-emotional-intelligence/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/fatihguner/foreman/ai-emotional-intelligence"><img src="https://agentmods.dev/badge/skills/fatihguner/foreman/ai-emotional-intelligence.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 | $0.00127 | $0.04512 |
| Opus 5 | $0.00063 | $0.02256 |
| Sonnet 5 | $0.00025 | $0.00902 |
| Haiku 4.5 | $0.00013 | $0.00451 |
Grade A, and why
ai-emotional-intelligence 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 6d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Read runtime and advisory rules before applying this skill. Other Foreman layers and the catalog are in ../../content/, relative to this SKILL.md.
AI Emotional Intelligence
Here is an irony that will outlast every generation of large language model, every quantum computing breakthrough, and every breathless prediction about artificial general intelligence: the smarter machines become, the more valuable human intelligence grows. Not computational intelligence -- AI has won that contest definitively. Emotional intelligence: the capacity to perceive and manage one's own emotions, to read the emotional states of others, to build trust, to communicate with empathy, to motivate through meaning rather than metrics. According to Deloitte, soft-skill-intensive occupations will grow at 2.5 times the rate of other jobs and account for two-thirds of all positions by 2030. Google's Project Oxygen -- an internal study of what makes effective managers -- found that employees valued soft skills above STEM expertise. Seven out of ten employees, per recent research, believe soft skills are more necessary than hard skills for competing in the AI era. The paradox is not subtle: the age of artificial intelligence is, in fact, the age of emotional intelligence. Leaders who fail to grasp this will deploy brilliant technology to a workforce that does not trust, follow, or forgive them.
The Framework
Why Soft Skills Became Hard Requirements
The conventional hierarchy placed technical skills at the top and interpersonal skills somewhere below, in the category of "nice to have." AI has inverted this hierarchy with a logic that is both economically and philosophically sound.
Technical tasks -- data processing, pattern recognition, calculation, routine analysis -- are precisely what AI does well. As these tasks migrate to machines, the work that remains for humans is the work that machines cannot do: navigating ambiguity, exercising ethical judgment, building relationships, interpreting context, motivating teams through periods of uncertainty, and creating the cultural conditions under which innovation becomes possible. Hard skills become the domain of the machine. Soft skills become the domain of the human. And the soft skills, paradoxically, become the hard requirements for organisational survival.
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.
- 6d ago Changed · +199 lines · +127 tokens per session 202aca7e3049
- 12d ago First seen · 1 lines · 0 tokens per session scan A 0d7aa3ad210d
ai-emotional-intelligence is a skill published in the GitHub repository fatihguner/foreman (50 stars, last pushed 7d ago), licensed MIT. It adds 127 tokens to every session and 4,512 once invoked, about $0.0006 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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