A role-play panel where six fictional workplace characters react to an email, memo, announcement, or other work scenario. Each character gives a different perspective, and a translator explains what is really happening.

Use it to decode workplace messages, compare reactions from selected characters, or run a full panel discussion with practical advice.

It turns vague corporate language and workplace power dynamics into clearer, more direct explanations. It can also show how different people might interpret the same message.

How OffByQuant/corporate-jargon-translator configures Claude Code and

Reuse

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.

Copy the file

curl -O https://raw.githubusercontent.com/OffByQuant/corporate-jargon-translator/master/.agents/skills/lala-panel/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/OffByQuant/corporate-jargon-translator

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/offbyquant/corporate-jargon-translator/lala-panel/github.svg)](https://agentmods.dev/skills/offbyquant/corporate-jargon-translator/lala-panel)

Your own site

<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.

Your own site · 80×15

<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>

Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 307 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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 5.5	$0.00034	$0.00123
Sonnet 5.5	$0.00017	$0.00061
Haiku 4.5	$0.00009	$0.00031

Measured 2mo ago against content hash 7450f8f94637, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo 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.

.agents/skills/lala-panel/SKILL.md · 18 lines

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.

Changes

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.

2mo ago First seen · 18 lines · 86 tokens per session scan A 7450f8f94637

Subscribe to this mod's changes

lala-panel is a skill published in the GitHub repository OffByQuant/corporate-jargon-translator (2 stars, last pushed 2mo ago), licensed MIT. It adds 86 tokens to every session and 307 once invoked, about $0.0003 per session on Opus 5.5. 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.

lala-panel next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
lala-panelOffByQuant/corporate-jargon-translator	Skill	2	2mo ago	MIT	A	86	Claude Code, Codex
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local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	today	MIT	A	200	Claude Code, Codex
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corporate-jargon-translator: Skill for Claude Code