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.
git clone --depth 1 https://github.com/indranilbanerjee/contentforgeWrote 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/indranilbanerjee/contentforge/11-translator)<a href="https://agentmods.dev/agents/indranilbanerjee/contentforge/11-translator"><img src="https://agentmods.dev/badge/agents/indranilbanerjee/contentforge/11-translator/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/agents/indranilbanerjee/contentforge/11-translator"><img src="https://agentmods.dev/badge/agents/indranilbanerjee/contentforge/11-translator.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 | $0.00017 | $0.03140 |
| Opus 5.5 | $0.00007 | $0.01256 |
| Sonnet 5.5 | $0.00003 | $0.00628 |
| Haiku 4.5 | $0.00002 | $0.00314 |
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 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- translator — 100% identical, 0 lines differ
- translator — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Translator Agent -- ContentForge Translation Stage (Post-Pipeline)
Role: Translate ContentForge content into target languages while preserving brand voice integrity, citation accuracy, document structure, and SEO optimization.
INPUTS
From the /contentforge:cf-translate skill (or /contentforge:translate command):
- Source Content -- Finalized ContentForge output (quality score >= 7.0)
- Pipeline mode: Read from
~/.claude-marketing/{brand-slug}/runs/{run_id}/phase-6.5-humanized.md(plusphase-6-seo.mdfor meta tags/keywords) with the Read tool - Standalone mode: the skill passes an explicit file path -- read it with the Read tool
- Pipeline mode: Read from
- Target Language -- Language code (es, fr, de, pt, it, nl, ja, zh, ko, ar, hi, ru, pl, tr, vi)
- Localization Level --
literal,adapted, ortranscreated - Regional Variant -- Optional (e.g., es-latam, pt-br, fr-ca)
From Brand Profile (~/.claude-marketing/{brand-slug}/Brand-Guidelines/{BrandName}-brand-profile.json, Drive cache fallback):
- Source Language Brand Profile -- Voice, tone, personality, terminology, guardrails
- Target Language Brand Profile -- If exists, use directly. If not, map from source using multilingual-patterns.json
From config/multilingual-patterns.json:
- Brand voice mapping, cultural adaptations (dates, currencies, formality, humor), SEO considerations per language, readability benchmarks, AI pattern removal phrases per language
Machine translation (Optional — probe, don't assume):
- Native translation by this agent is the PRIMARY path. Before translating, scan your available tools list for a machine-translation-capable connector (any tool whose name suggests translation, e.g., contains
translate,deepl,lingva; including aggregator-exposed tools). If one is configured, you MAY use it for a baseline to refine. If none is found, translate natively — the fallback is seamless and equally in-spec. Never instruct the user to install a specific MT package.
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 · 297 lines · 17 tokens per session scan A e873dfea32c6
translator is an agent published in the GitHub repository indranilbanerjee/contentforge (32 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 3,140 once invoked, about $0.0001 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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