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 OpenHands/extensions --skill plain-english-contentgit clone --depth 1 https://github.com/OpenHands/extensionsWrote 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/openhands/extensions/plain-english-content)<a href="https://agentmods.dev/skills/openhands/extensions/plain-english-content"><img src="https://agentmods.dev/badge/skills/openhands/extensions/plain-english-content/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/openhands/extensions/plain-english-content"><img src="https://agentmods.dev/badge/skills/openhands/extensions/plain-english-content.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 | $0.00072 | $0.01395 |
| Opus 5.5 | $0.00029 | $0.00558 |
| Sonnet 5.5 | $0.00014 | $0.00279 |
| Haiku 4.5 | $0.00007 | $0.00139 |
Grade A, and why
plain-english-content 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 1mo 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Open content up so anyone can understand it the first time they read it, without losing substance, nuance or precision. Aim to open up, not dumb down. Apply the GOV.UK style guide approach: plain English, user needs first, active voice, front-loaded structure and accessible formatting.
Use this skill for reports, research write-ups, guidance, documentation, summaries, and public-facing prose where clarity and accessibility matter. When writing a report, default to this style. When briefing a research agent, pass this skill so the report follows the same style.
Content design principles
- Start from the user need. Write what the reader needs to know to do or decide something, not what the writer wants to say.
- Front-load everything. Put the most important point first in the document, each section, each paragraph and each sentence. Use the inverted pyramid: conclusion first, then detail, then background.
- Keep one idea per sentence and one topic per paragraph. Split sentences that contain more than one idea.
- Be specific and concrete. Give the number, name and date. Cut vague abstractions like "a range of", "going forward" and "in terms of".
- Cut everything that does not add meaning. Shorter is clearer. Remove duplication.
Plain English
- Open content up, do not dumb it down. Keep the substance, nuance and precision. Strip out only what makes it hard to read: jargon, long sentences, abstract nouns and tangled structure. Make the content clear enough for a non-specialist and precise enough for an expert.
- Use the active voice. Say who does what. Write "We reviewed the data", not "The data was reviewed".
- Keep sentences short: about 15 to 20 words, and rarely more than 25. Keep paragraphs short.
- Use everyday words. Replace jargon and formal wording with plain alternatives:
- use, not utilise or leverage
- help, not facilitate or empower
- work with, not collaborate, liaise or engage with
- make or provide, not deliver
- about, not in relation to or with regard to
- so, not in order to
- start, not commence
- end, not terminate
- buy, not purchase
- enough, not sufficient
- solve, fix or deal with, not tackle or combat
- effect on, not impact on
- Do not use impact as a verb.
- Avoid metaphors and cliches: drive, unlock, deep dive, robust, key, ring-fence, hub, portal, landscape, ecosystem and going forward.
- Address the reader as "you". Write about the organisation as "we". Use "they", "them" and "their" rather than gendered pronouns. Write "disabled people", not "the disabled".
- Use contractions for a warmer tone when appropriate, such as "we'll" and "you'll". Avoid negative contractions: write "cannot", not "can't". Avoid "should've", "could've" and "would've".
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 79 lines · 72 tokens per session scan A 2ef939ec154a
plain-english-content is a skill published in the GitHub repository OpenHands/extensions (167 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 1,395 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 2026-09-03.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…