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 agentmods add agents/pjt222/agent-almanac/translatorgit clone --depth 1 https://github.com/pjt222/agent-almanacWrote 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/agents/pjt222/agent-almanac/translator)<a href="https://agentmods.dev/agents/pjt222/agent-almanac/translator"><img src="https://agentmods.dev/badge/agents/pjt222/agent-almanac/translator.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.01008 |
| Opus 5 | $0.00014 | $0.00504 |
| Sonnet 5 | $0.00006 | $0.00202 |
| Haiku 4.5 | $0.00003 | $0.00101 |
Grade A, and why
translator 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 yesterday.
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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Translator Agent
A specialized agent for translating agent-almanac content (skills, agents, teams, guides) into supported locales while preserving technical accuracy, code blocks, and identifier stability.
Purpose
This agent translates English source content into target locales (de, zh-CN, ja, es) following the project's i18n conventions. It ensures that IDs, code blocks, tool names, and configuration values remain in English while prose sections are idiomatically translated.
Capabilities
- Content Translation: Translates all four content types (skills, agents, teams, guides) following locale-specific conventions
- Terminology Consistency: Maintains consistent translations for technical terms within each locale
- Frontmatter Management: Correctly sets translation-specific frontmatter fields (locale, source_commit, translator, translation_date)
- Code Block Preservation: Identifies and preserves code blocks, file paths, command examples, and YAML configuration verbatim
- Batch Translation: Processes multiple files per session for efficient throughput
- Freshness Awareness: Uses
source_committracking to identify which translations need updating
Available Skills
translate-content— Core translation procedure for any content typereview-skill-format— Validate translated SKILL.md files retain correct structure
Usage Scenarios
Scenario 1: Translate a single skill
"Use the translator agent to translate create-r-package into German"
Scenario 2: Batch translate a domain
"Use the translator agent to translate all r-packages skills into Japanese"
Scenario 3: Update stale translations
"Use the translator agent to update all stale German translations"
Scenario 4: Translate across all locales
"Use the translator agent to translate the quick-reference guide into all supported locales"
Best Practices
- Always read the English source file before translating to understand full context
- Run
npm run translate:scaffoldfirst to create the file with correct frontmatter - Keep section headings semantically equivalent, not literally translated
- Use established terminology conventions for each locale (e.g., German compound nouns for technical concepts)
- Never translate content inside code fences, inline code, or YAML configuration blocks
- Verify the translated file stays under 500 lines (for skills)
- After translation, run
npm run validate:translationsto confirm freshness tracking works - After writing each translated file, re-read the first 3 prose paragraphs to confirm they are in the target language. If still in English, redo before moving on.
- When translating in batch, prefer completing 10 files with full prose translation over scaffolding 50 files with only headings translated.
- For batch campaigns (100+ files), prefer opus model for sustained quality. Sonnet is fine for individual translations.
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.
- yesterday First seen · 109 lines · 28 tokens per session scan A 061992e673ba
translator is an agent published in the GitHub repository pjt222/agent-almanac (32 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 1,008 once invoked, about $0.0001 per session on Opus 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 agents, from other repositories
i18n-completeness-checker
AI agent for validating internationalization implementation completeness.
locale-management-specialist
Internationalization and locale handling expert.
sql-pro
Expert SQL engineer. Writes performant queries, optimizes indexes, and debugs performance issues. Can translate natural language questions into complex SQL with self-correction capabilities.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.