Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/dsm5e/aso-trackernpx agentmods add skills/dsm5e/aso-tracker/higgsfield-image-shotsWrote 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/dsm5e/aso-tracker/higgsfield-image-shots)<a href="https://agentmods.dev/skills/dsm5e/aso-tracker/higgsfield-image-shots"><img src="https://agentmods.dev/badge/skills/dsm5e/aso-tracker/higgsfield-image-shots/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/dsm5e/aso-tracker/higgsfield-image-shots"><img src="https://agentmods.dev/badge/skills/dsm5e/aso-tracker/higgsfield-image-shots.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 | $0.00104 | $0.04202 |
| Opus 5 | $0.00052 | $0.02101 |
| Sonnet 5 | $0.00021 | $0.00840 |
| Haiku 4.5 | $0.00010 | $0.00420 |
Grade A, and why
higgsfield-image-shots 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 12d 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.
This is a copy
94% identical to higgsfield-image-shots — 18 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 445 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Cinematic Image Prompting
This skill covers still image shot composition — framing, angles, and implied camera movement for AI image generation. Use these keywords and patterns when building prompts for any Higgsfield image model.
Key difference from video camera controls: These are composition directives
for a single frame. The [img 1] token references a Soul ID character or
uploaded reference image. Replace it with your character description or @ Element
when no reference image is used.
How to Use This Reference
Every entry has:
- Shot/Movement — the cinematography term
- AI Prompt Keyword — the exact words to put in your image prompt
- Purpose — what emotional/compositional effect it creates
- Prompt Example — a ready-to-adapt prompt phrase
Prompt pattern for image generation:
[Shot keyword] of [img 1 or character description] + [pose/action] + [environment detail] + [lighting/atmosphere]
Distance & Size — Shot Framing
These control how much of the subject fills the frame and how much environment is visible. Choose based on whether the image is about the world, the character, or a detail.
Extreme Wide Shot (EWS)
AI Prompt Keyword: EWS, Vast, Landscape Definition: The subject is barely visible; emphasizes the vast landscape or location. Purpose: Establish vastness, show isolation, or emphasize scale. Prompt Example:
Extreme wide shot of [img 1] standing alone in a vast, empty frozen tundra.
The subject is small in the distance, surrounded by massive snowy mountains.
Cinematic lighting
Wide Shot (WS) / Long Shot
AI Prompt Keyword: Wide Shot, Full Body Definition: Shows the full subject within their environment. Purpose: Provide context and spatial awareness. Prompt Example:
Wide shot of [img 1] standing full body in a snowstorm. She is wearing fur armor,
boots visible, centered in a snowy forest clearing. Environmental context.
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.
- 12d ago First seen · 445 lines · 104 tokens per session scan A 20da6605c995
higgsfield-image-shots is a skill published in the GitHub repository dsm5e/aso-tracker (139 stars, last pushed 26d ago), licensed MIT. It adds 104 tokens to every session and 4,202 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to higgsfield-image-shots, differing in 18 lines, and is treated as a copy.
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