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 rsturla/eternal-images --skill asd-ste100git clone --depth 1 https://github.com/rsturla/eternal-imagesWrote 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/rsturla/eternal-images/asd-ste100)<a href="https://agentmods.dev/skills/rsturla/eternal-images/asd-ste100"><img src="https://agentmods.dev/badge/skills/rsturla/eternal-images/asd-ste100/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/rsturla/eternal-images/asd-ste100"><img src="https://agentmods.dev/badge/skills/rsturla/eternal-images/asd-ste100.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 | $0.00077 | $0.00640 |
| Opus 5.5 | $0.00031 | $0.00256 |
| Sonnet 5.5 | $0.00015 | $0.00128 |
| Haiku 4.5 | $0.00008 | $0.00064 |
Grade A, and why
asd-ste100 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ASD-STE100 Simplified Technical English
Simplified Technical English (STE) is a controlled language from the aerospace industry. It uses a set of writing rules and a dictionary of approved words. The goal is text that a reader cannot misread, including a non-native reader.
This skill is an unofficial aid. It does not guarantee full compliance. For disputed words or rules, see the official source at https://asd-ste100.org. A human writer makes the final decision.
When to apply it
Apply STE to technical and procedural text: documentation, code comments, commit messages, tool descriptions, error messages, and agent-to-agent instructions. Do not apply STE to creative writing or marketing copy, where voice and nuance are the point.
Workflow
Do these three steps. Fix the form, but do not change the meaning.
Step 1 — Classify the text
Decide the type of each passage, because the rules differ:
- Procedure — an instruction to do something. Sentence limit: 20 words.
- Description — an explanation of a thing or an idea. Sentence limit: 25 words.
Step 2 — Apply the core rules
- Write short sentences. Keep to the word limit for the text type.
- Write one instruction per sentence.
- Use the active voice.
- Use simple verb tenses: imperative, simple present, simple past, simple
future. Do not use
-ingverb forms as verbs. Do not use the passive voice in procedures. - Use one word for one meaning. Use approved words. See references/word-choice.md.
- Do not omit articles (
a,the) or other words that make the text clear. - Put the condition before the instruction. Example: "If the test fails, stop the build."
- Use the same term for the same thing each time. Do not use synonyms.
- Use a vertical list for complex or sequential information.
For the full rule set, see references/writing-rules.md.
Step 3 — Verify
Check the result against references/checklist.md. Fix each problem, then check again. Stop when the text meets all rules or when a rule would change the meaning.
What ships with it
3 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.
- 2mo ago First seen · 67 lines · 77 tokens per session scan A dcc90dbb6325
asd-ste100 is a skill published in the GitHub repository rsturla/eternal-images (11 stars, last pushed yesterday), licensed MIT. It adds 77 tokens to every session and 640 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 2026-08-30.
asd-ste100 compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| asd-ste100rsturla/eternal-images | Skill | 11 | yesterday | MIT | A | 77 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |