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.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/instructions/offbyquant/corporate-jargon-translator/agents-md)<a href="https://agentmods.dev/instructions/offbyquant/corporate-jargon-translator/agents-md"><img src="https://agentmods.dev/badge/instructions/offbyquant/corporate-jargon-translator/agents-md/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/instructions/offbyquant/corporate-jargon-translator/agents-md"><img src="https://agentmods.dev/badge/instructions/offbyquant/corporate-jargon-translator/agents-md.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 | $0.00475 | $0.00475 |
| Opus 5.5 | $0.00190 | $0.00190 |
| Sonnet 5.5 | $0.00095 | $0.00095 |
| Haiku 4.5 | $0.00047 | $0.00047 |
Grade A, and why
corporate-jargon-translator AGENTS.md 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.
How it starts
The opening of the file, as written. The whole thing — 31 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Corporate Jargon Translator - Agent Guidelines
This repository contains the Corporate Jargon Translator skill, designed to decode corporate speak, HR euphemisms, executive deflection, and startup equity hype into plain truth, as well as encode blunt employee feedback into HR-safe corporate speak.
The full skill lives at .agents/skills/corporate-jargon-translator/SKILL.md — harnesses that follow the agentskills.io convention (Codex, Copilot CLI, Gemini CLI, OpenCode) discover it there automatically. Read it before processing any translation request; it links the jargon dictionary, character cast, and transcript-analysis examples.
🛠️ Commands & Tests
- Run CLI Translator Test Suite:
python3 .agents/skills/corporate-jargon-translator/scripts/translate.py --test - Decode Custom Text String via CLI:
python3 .agents/skills/corporate-jargon-translator/scripts/translate.py --decode "Your text here" - Encode Blunt Thought into Corporate Speak via CLI:
python3 .agents/skills/corporate-jargon-translator/scripts/translate.py --encode "You guys don't know what you're doing"
🤖 Execution Modes
- Decode Mode: Decodes HR speak, meeting transcripts, PIP emails, and IPO hype — inline 🎙️ Translator commentary first, then a structured Markdown table with risk levels (🟢 Low, 🟡 Medium, 🟠 High, 🔴 Critical), plus 2-3 tactical employee survival tips.
- Encode Mode: Rewrites unfiltered thoughts into executive-ready corporate speak (Blunt Thought → HR-Safe Version → Strategic Intent).
- Character Commentary Mode (Lala Company Edition): Provides comedic panel reactions featuring The Enlightened Founder, Lala Ji (self-proclaimed CEO — a different person from the Founder), Sycophant Senior, Tired Dev Dave, Naive Joiner, and Unfiltered Translator. Directly invocable via the
lala-panelskill in.agents/skills/lala-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.
- 2mo ago First seen · 31 lines · 475 tokens per session scan A 74279fd8ba18
corporate-jargon-translator AGENTS.md is an instructions file published in the GitHub repository OffByQuant/corporate-jargon-translator (2 stars, last pushed 2mo ago), licensed MIT. It adds 475 tokens to every session, about $0.0019 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.
corporate-jargon-translator AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| corporate-jargon-translator AGENTS.mdOffByQuant/corporate-jargon-translator | Instructions file | 2 | 2mo ago | MIT | A | 475 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 275k | 3d ago | MIT | A | 4,313 | Codex, OpenCode |