Borrowing it
Nothing to install: this file belongs to OffByQuant/corporate-jargon-translator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/OffByQuant/corporate-jargon-translator/master/.agents/skills/lala-panel/SKILL.mdgit clone --depth 1 https://github.com/OffByQuant/corporate-jargon-translatorWrote 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/offbyquant/corporate-jargon-translator/lala-panel)<a href="https://agentmods.dev/skills/offbyquant/corporate-jargon-translator/lala-panel"><img src="https://agentmods.dev/badge/skills/offbyquant/corporate-jargon-translator/lala-panel/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/offbyquant/corporate-jargon-translator/lala-panel"><img src="https://agentmods.dev/badge/skills/offbyquant/corporate-jargon-translator/lala-panel.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 | $0.00086 | $0.00307 |
| Opus 5 | $0.00043 | $0.00153 |
| Sonnet 5 | $0.00017 | $0.00061 |
| Haiku 4.5 | $0.00009 | $0.00031 |
Grade A, and why
lala-panel 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 9d 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.
What it actually says
Lala Panel 🎭
Slash-command shortcut into Character Commentary Mode (Mode C) of the corporate-jargon-translator skill. The argument (or the message the user points at) is the scenario the panel reacts to.
- Read the persona definitions and the Power Dynamic rules in character_cast.md before roleplaying — the Founder and Lala Ji are two different people; merging them kills the joke.
- Render the panel-room debate format defined there: each persona reacts in voice, and the 🎙️ Unfiltered Translator closes with the verdict that names what actually happened.
- If the user asks for specific personas only, seat only those.
- If the user asks for the full show, run the complete decode contract first (inline overlay → decoder table → tactical advice) per the main SKILL.md, then bring in the panel.
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.
- 9d ago First seen · 18 lines · 86 tokens per session scan A 7450f8f94637
lala-panel is a skill published in the GitHub repository OffByQuant/corporate-jargon-translator (2 stars, last pushed 21d ago), licensed MIT. It adds 86 tokens to every session and 307 once invoked, about $0.0004 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 2026-08-31.
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