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 talkstream/ru-text --skill ru-scoregit clone --depth 1 https://github.com/talkstream/ru-textWrote 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/talkstream/ru-text/ru-score)<a href="https://agentmods.dev/skills/talkstream/ru-text/ru-score"><img src="https://agentmods.dev/badge/skills/talkstream/ru-text/ru-score/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/talkstream/ru-text/ru-score"><img src="https://agentmods.dev/badge/skills/talkstream/ru-text/ru-score.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 | $0.00075 | $0.01452 |
| Opus 5.5 | $0.00030 | $0.00581 |
| Sonnet 5.5 | $0.00015 | $0.00290 |
| Haiku 4.5 | $0.00007 | $0.00145 |
Grade A, and why
ru-score 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 18d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- ru-score — 94% identical, 11 lines differ
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Russian Text Quality Score
Score the text provided in $ARGUMENTS (or the most recent Russian text output if no arguments) using the ru-text scoring rubric.
Procedure
Where the reference files live
This skill reads the corpus that ships with the ru-text skill, which is installed alongside it. Locate that folder once, then read the named files from it:
- Look for a directory named
referenceswhose parent directory is namedru-text, and which containsinfo-style.md. Every file named below sits in that folder. - Search with file tools, never with a shell.
Globon a pattern like**/ru-text/references/info-style.md, or whatever file search the host offers, thenRead. This command has no use for a command line:Bashis on itsdisallowed-toolslist, and hosts that do not implement that field still refuse it — measured in Claude Cowork on 12.08.2026, where an openinglsreturned «Permission to use Bash has been denied» in red before the search found the corpus anyway. The call bought nothing and cost the reader a scare. - In Claude Code the folder is
${CLAUDE_SKILL_DIR}/../ru-text/references/—Readinfo-style.mdthere first and skip the search. If that path arrives unexpanded or the read fails, fall back to the search above. - Do not guess a path. If the folder cannot be found, say so and stop — a check run against remembered rules instead of the corpus is not this command, and reporting one as the other is the failure this whole product exists to prevent.
-
Load rubric — read
scoring.mdfor the full rubric with anchors. -
Determine domain — identify whether the text is UI/interface, business email, article, or general:
- UI text → also load
ux-writing.mdfor the Reader Precision dimension - Business email → also load
business-writing.mdfor the Reader Precision dimension - General → use
info-style.mdonly
- UI text → also load
-
Evaluate each dimension separately — score in this order:
- T — Типографика (weight 0.15): quotes, dashes, spaces, special characters per
typography.md - Ч — Чистота языка (weight 0.25): stop-words, bureaucratic language, clichés, passive voice per
info-style.md+anti-patterns.md - Г — Грамотность (weight 0.20): punctuation, agreement, tautology per
editorial-grammar.md+editorial-punctuation.md - С — Структура (weight 0.20): logical flow, paragraphs, transitions, heading use per
info-style.mdstructure section +addenda.md - Ц — Точность для читателя (weight 0.20): facts, evidence, reader benefit, actionability per domain rules
- T — Типографика (weight 0.15): quotes, dashes, spaces, special characters per
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.
- 18d ago Changed · +2 lines 063c423d5923
- 1mo ago First seen · 97 lines · 75 tokens per session scan A 1057f053b01a
ru-score is a skill published in the GitHub repository talkstream/ru-text (281 stars, last pushed 2d ago), licensed MIT. It adds 75 tokens to every session and 1,452 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.
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