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 skills add nicolocurioni96/withnico-skills --skill app-screenshot-studiogit clone --depth 1 https://github.com/nicolocurioni96/withnico-skillsWrote 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/nicolocurioni96/withnico-skills/app-screenshot-studio)<a href="https://agentmods.dev/skills/nicolocurioni96/withnico-skills/app-screenshot-studio"><img src="https://agentmods.dev/badge/skills/nicolocurioni96/withnico-skills/app-screenshot-studio/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/nicolocurioni96/withnico-skills/app-screenshot-studio"><img src="https://agentmods.dev/badge/skills/nicolocurioni96/withnico-skills/app-screenshot-studio.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 | $0.00000 | $0.03010 |
| Opus 5.5 | $0.00000 | $0.01204 |
| Sonnet 5.5 | $0.00000 | $0.00602 |
| Haiku 4.5 | $0.00000 | $0.00301 |
Grade A, and why
shotkit 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 2mo 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
1 near-identical copy found in the catalogue:
- shotkit — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shotkit
End-to-end App Store screenshot pipeline for indie iOS developers. From raw Simulator capture to upload-ready assets, with native App Store Connect integration.
This skill is fully automated. When triggered, the agent handles the entire pipeline — booting simulators, capturing screenshots, compositing with trending styles, and uploading to App Store Connect — without requiring manual interaction.
What This Skill Does
Stage 1 — Auto-Capture (optional): Boots Xcode Simulator devices, launches the app via bundle ID, navigates screens via deep links, sets a clean status bar (9:41, full battery), and captures raw UI screenshots — all without user interaction.
Stage 2 — Generate Copy: Produces locale-aware headlines (max 30 chars) + sublines (max 60 chars) for each screenshot frame. If no copy.json is provided, the agent generates one based on the app's features and target audience.
Stage 3 — Composite: Renders styled screenshot images using Pillow — background, device UI area, app screenshot, and text overlay — with 5 template styles.
Stage 4 — Organize & Validate: Outputs an ASC-ready folder structure ({locale}/{device}/), validates dimensions against App Store requirements, and generates an upload checklist.
Stage 5 — Upload (optional): Uploads screenshots directly to App Store Connect via native API integration. Supports uploading new screenshots and replacing existing ones.
Workflow
Step 1 — Collect Inputs
Ask the developer for the following (or infer from context if already provided):
Required:
- App name
- Core features to highlight (3–8 bullet points)
- Target audience (one sentence)
- Primary language (default: English)
- Additional locales (optional, e.g. Italian, German, Japanese)
Screenshot source (choose one):
- A) Automated capture from Simulator → ask for app Bundle ID and deep link URLs per screen
- B) Existing screenshots folder → ask for path to folder of PNG/JPG files
- C) No UI screenshots yet → generate placeholder-based composites with colored UI mockups
What ships with it
21 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .skill-meta.json 184 B
- references/app_store_connect.md 1.6 KB
- references/capture_guide.md 848 B
- references/copy_example.json 1.5 KB
- references/device_specs.md 980 B
- references/template_guide.md 2.7 KB
- scripts/asc_api.py 11 KB runs code
- scripts/asc_download.py 4.3 KB runs code
- scripts/asc_init.py 4.5 KB runs code
- scripts/asc_upload.py 7.1 KB runs code
- scripts/auto_capture.sh 11 KB runs code
- scripts/capture_simulator.sh 1.5 KB runs code
- scripts/color_utils.py 4.5 KB runs code
- scripts/device_frames.py 11 KB runs code
- scripts/doctor.py 5.1 KB runs code
- scripts/generate_screenshots.py 27 KB runs code
- scripts/install_deps.sh 1.9 KB runs code
- scripts/shotkit 8.7 KB
- scripts/trending_palettes.json 3.6 KB
- scripts/trending.py 8.4 KB runs code
- scripts/validate_output.py 9.2 KB runs code
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.
- 2mo ago First seen · 302 lines · 0 tokens per session scan A 570a9d1a9679
shotkit is a skill published in the GitHub repository nicolocurioni96/withnico-skills (5 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,010 tokens. 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 2026-08-31.
shotkit compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| shotkitnicolocurioni96/withnico-skills | Skill | 5 | 3mo ago | MIT | A | 0 | Cursor |
| ui-enhancer-radarTerryc21/radar-suite | Skill | 20 | 17d ago | Apache-2.0 | A | 148 | Claude Code |
| ui-path-radarTerryc21/radar-suite | Skill | 20 | 17d ago | Apache-2.0 | A | 86 | Claude Code |
| m3-expressiveahmed3elshaer/everything-claude-code-mobile | Skill | 66 | 4mo ago | MIT | A | 41 | Claude Code |
| liquid-glassahmed3elshaer/everything-claude-code-mobile | Skill | 66 | 4mo ago | MIT | A | 40 | Claude Code |
| accessibility-patternsahmed3elshaer/everything-claude-code-mobile | Skill | 66 | 4mo ago | MIT | A | 35 | Claude Code |
| ttb-skill-native-swiftui-componentstqtuan1201/TTBaseUIKit | Skill | 23 | 3mo ago | MIT | A | 55 | Claude Code, Codex |