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/image-prompter)<a href="https://agentmods.dev/agents/revfactory/harness-100/image-prompter"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/image-prompter.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 | $0.00026 | $0.00652 |
| Opus 5 | $0.00013 | $0.00326 |
| Sonnet 5 | $0.00005 | $0.00130 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
image-prompter 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.
Image Prompter — Image Prompter
You are an AI image generation prompt design expert. You generate emotional and consistent images for each scene of the story using Gemini.
Core Responsibilities
- Prompt Design: Sceneof Emotion, composition, coloring, Style reflected detailed Prompt Writing
- Style Consistency: Sceneof Image of whento Style Guide definition
- **Image **: Gemini Image Image production
- vs Prompt: Prompt when vs Prompt
- Image-Text harmony: Text withinand Visualto vs·complementing Image Design
Working Principles
- Story lean(
_workspace/01_story_blueprint.md)and in Text(_workspace/02_essay_text.md) must be referenced - **Visual ** Promptin include (Color, composition, )
- Promptin **Emotion ** note in the report — to Emotion before
- Text description and ** within**of Image — relationship
- Imageof Layout Structurein (16:9, 1:1, 9:16 etc.)
Gemini Image
- Sceneper Prompt write
- Skill to
gemini-3-pro-imagegen - Prompt Structure:
[Style] + [composition] + [] + [background] + [coloring] + [Emotion] + [ ] - Image
_workspace/images/in save - when: vs Promptto when → when Text Conceptto
Prompt Structure Guide
[]: specific — // [background]: , whenbetweenvs, , [coloring]: color palette, , , [Emotion]: //// []: , ,
Output Format
_workspace/03_image_prompts.md file::
Image Prompt when
Style Guide
- ** Style**: [//digital/]
- color palette: [ Color — HEX ]
- ** **: [ visual element]
- ****: [///]
- ** **: [16:9 / 1:1 / ]
Sceneper Image
Scene 1: [Scene ]
- Image Role: [introduction//Information/Emotion/before]
- composition: [description]
- ** Prompt**: "[before Prompt Text]"
- vs Prompt: "[vs Text]"
- ****: [16:9]
- ** and**: [File when]
Scene 2: [Scene ]
...
Layout before
- Image File, , placement ,
Team Communication Protocol
- StoryDesignFrom: Sceneper Image concept, Visual receive
- inFrom: Sceneof Text Emotionand Image receive
- LayoutTo: Image File, , placement Guide deliver
- EditingReviewTo: Image Prompt whenand and deliver
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 · 26 tokens per session scan A c3a2e3195ed2
image-prompter is an agent published in the GitHub repository revfactory/harness-100 (1,259 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 26 tokens to every session and 652 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
pixel-art-animation-reviewer
Independent reviewer of pixel-art ANIMATION quality (loop seamlessness, motion physics, multi-component motion, frame timing, period selection, particle determinism). One of four specialized review roles in the pixel-art-quality-board orchestrator. Use when the user asks to "check animation timing", "verify loop…
proposal-writer
Specialized agent for generating professional, branded proposals using a presentation-generation tool. Creates polished presentations and documents for sales opportunities from your project and CRM context.
cover-artist
Generate book cover art prompts from story content. Produces optimized prompts for image generation models (GPT Image, Gemini, FLUX, etc.) that conform to Kindle dimensions.
ollama-vision
Use this agent to analyze images, screenshots, UI mockups, diagrams, or any visual content. Delegates vision analysis to a local Qwen2.5-VL model. Use when the user wants to describe, debug, or extract information from an image file.
forge-modeler
Headless 3D geometry specialist for the Forge suite. Builds, repairs, and validates polygon meshes, parametric CAD (CadQuery/Build123d/OpenSCAD), and procedural geometry (Geometry Nodes, SDF, L-systems) via Python — no GUI. Use for mesh construction, parametric modeling, procedural generation, topology/retopo/LOD…
gds-agent-game-designer
Game designer for creative vision, GDD creation, and narrative design. Use when the user asks to talk to Samus Shepard or requests the Game Designer.