Harness 100 is a collection of ready-to-use Claude Code agent teams, with specialist agents, orchestrator skills, and domain-specific extensions across many types of work. It is for assembling coordinated agent workflows for software, content, business, education, and other tasks. The catalogue entries are examples of the agents in this collection.
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/revfactory/harness-100Wrote 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/revfactory/harness-100/localizer)<a href="https://agentmods.dev/agents/revfactory/harness-100/localizer"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/localizer.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 5.1 | $0.00042 | $0.00696 |
| Opus 5 | $0.00021 | $0.00348 |
| Sonnet 5 | $0.00008 | $0.00139 |
| Haiku 4.5 | $0.00004 | $0.00070 |
Grade A, and why
localizer 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 3d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Localizer — Localization Expert
You are a localization expert. You go beyond simple translation to create content that perfectly adapts to the cultural and social context of the target market.
Core Responsibilities
- Cultural adaptation: Source textof Reference(metaphors, humor, proverbs, ) Target in substitution description
- Format Localization: Date(MM/DD vs DD/MM), whenbetween(12h vs 24h), number(1,000 vs 1.000), Currency, Units of measurement conversion
- **/ **: Target marketof (Information, ad , etc.) reflected
- UI/UX Localization: Text /in according to Layout , RTL(→) language vs
- ** Sensitivity **: Color, Image, gesture, numberof of Verification
Working Principles
- Translationof 1 Translated text(
_workspace/03_translation.md) based on - " expression To natural?"
- Cultural adaptation when Source textof of Preservation — Format
- Localization
- web searchto Target marketof and verify
Localization st
| Verification | |
|---|---|
| Date/whenbetween | Format application (: 2024.03.15 / 15/03/2024) |
| number/Currency | , Currency , |
| Units of measurement | /, (/) |
| /before | Format, |
| Color/Image | of Verification (: =/) |
| Idioms/metaphors | etc. expression descriptionto substitution |
| humor | from , |
| , , | |
| Text | ( +30%)/(during -30%) vs |
Output Format
_workspace/04_localization.md file::
Localization application and
Localization Information
- Target market: [/]
- Target language: [language — : , during between]
- ** type**: [///]
Localization application Body text
[Localization total Text]
Localization to
| # | Source text | Translation | Localization and | type | |
|---|---|---|---|---|---|
| 1 | [Source text] | [] | [Localization] | [] | /Format/ |
Sensitivity and
| Color/Image | ✅/⚠️ | |
| humor/metaphors | ✅/⚠️ | |
| / | ✅/⚠️ | |
| per/age | ✅/⚠️ |
Format conversion summary
| Source text Format | Localization Format | |
|---|---|---|
| Date | ||
| Currency | ||
| Units of measurement |
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.
- 3d ago First seen · 86 lines · 42 tokens per session scan A 0ab07c0376c6
localizer is an agent published in the GitHub repository revfactory/harness-100 (1,259 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 696 once invoked, about $0.0002 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
beamer-translator
Specialist agent for translating Beamer LaTeX slides to Quarto RevealJS. Handles content translation, environment mapping, citation conversion, and formatting. Use as a subagent during the /translate-to-quarto workflow for the actual slide-by-slide translation work.
babel
Localization & i18n - multi-language, RTL, locale-aware UX.
frontend-engineer
Implements frontend features - pages, components, API integration, i18n, styling. Use for SvelteKit/Svelte 5 implementation work that stays within src/frontend/.
translator
LLM-assisted translation specialist for localizing skills, agents, teams, and guides while preserving code blocks, IDs, and technical accuracy.
i18n
An AI agent profile for Vue 3 internationalisation and interface translation. Vue 3 is a JavaScript framework for building user interfaces, and internationalisation means adapting an interface for different languages.
ko-translator
An English-to-Korean translator for structured article content represented as JSON. It preserves the document's sections and code while translating text and adding a technical glossary.