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 johari-windowgit 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/johari-window)<a href="https://agentmods.dev/skills/fatihguner/foreman/johari-window"><img src="https://agentmods.dev/badge/skills/fatihguner/foreman/johari-window/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/johari-window"><img src="https://agentmods.dev/badge/skills/fatihguner/foreman/johari-window.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 | $0.00105 | $0.03610 |
| Opus 5 | $0.00053 | $0.01805 |
| Sonnet 5 | $0.00021 | $0.00722 |
| Haiku 4.5 | $0.00011 | $0.00361 |
Grade A, and why
johari-window 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 2d 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 — 194 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.
Johari Window
What do the people you work with most closely know about you that you do not know about yourself? The question is uncomfortable precisely because the answer, by definition, is invisible to the person it most concerns. Joseph Luft and Harrington Ingham -- whose first names combine to form "Johari" -- devised their four-pane window model in 1955 at the University of California, Los Angeles, as a tool for understanding self-awareness in group settings. Six decades later, it remains one of the most intuitively powerful frameworks for diagnosing trust, communication, and relational effectiveness in teams. Its enduring utility lies in a simple geometric truth: the less a team knows about each other's thinking, motivations, and concerns, the more organisational energy is wasted on misinterpretation, defensive posturing, and avoidable conflict.
The Framework
The Johari Window divides information about a person into four quadrants based on two axes: what is known to the self and what is known to others.
The Four Quadrants
Known to Self Unknown to Self
┌─────────────────────┬─────────────────────┐
│ │ │
Known to │ OPEN │ BLIND SPOT │
Others │ (Arena) │ │
│ │ │
├─────────────────────┼─────────────────────┤
│ │ │
Unknown to │ HIDDEN │ UNKNOWN │
Others │ (Facade) │ │
│ │ │
└─────────────────────┴─────────────────────┘
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.
- 2d ago First seen · 194 lines · 105 tokens per session scan A b008bcafa64f
johari-window is a skill published in the GitHub repository fatihguner/foreman (48 stars, last pushed 3d ago), licensed MIT. It adds 105 tokens to every session and 3,610 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 2026-09-06.
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