Fal Vision
nexu-io/open-design
Analyze images — segment objects, detect, run OCR, describe, and answer visual questions via fal.ai vision models.
Augmented vision tools for analyzing images beyond native visual capabilities.
MITAuto-check passed
Install Seeing Images
$ npx skills add oaustegard/claude-skills --skill seeing-images -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install oaustegard/claude-skills seeing-images --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/seeing-images .claude/skills/seeing-images && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "seeing-images" agent skill from https://github.com/oaustegard/claude-skills/tree/main/seeing-images into .claude/skills/seeing-images/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seeing-images", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/oaustegard/claude-skills/tree/main/seeing-imagesType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add oaustegard/claude-skills --skill seeing-images -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install oaustegard/claude-skills seeing-images --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/seeing-images .agents/skills/seeing-images && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "seeing-images" agent skill from https://github.com/oaustegard/claude-skills/tree/main/seeing-images into .agents/skills/seeing-images/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seeing-images", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add oaustegard/claude-skills --skill seeing-images -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install oaustegard/claude-skills seeing-images --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/seeing-images .cursor/skills/seeing-images && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "seeing-images" agent skill from https://github.com/oaustegard/claude-skills/tree/main/seeing-images into .cursor/skills/seeing-images/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seeing-images", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/oaustegard/claude-skills.git --path seeing-images--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add oaustegard/claude-skills --skill seeing-images -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install oaustegard/claude-skills seeing-images --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/seeing-images .gemini/skills/seeing-images && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "seeing-images" agent skill from https://github.com/oaustegard/claude-skills/tree/main/seeing-images into .gemini/skills/seeing-images/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seeing-images", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install oaustegard/claude-skills seeing-imagesInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add oaustegard/claude-skills --skill seeing-images -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/seeing-images .github/skills/seeing-images && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "seeing-images" agent skill from https://github.com/oaustegard/claude-skills/tree/main/seeing-images into .github/skills/seeing-images/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seeing-images", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add oaustegard/claude-skills --skill seeing-images -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install oaustegard/claude-skills seeing-images --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/seeing-images .opencode/skills/seeing-images && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "seeing-images" agent skill from https://github.com/oaustegard/claude-skills/tree/main/seeing-images into .opencode/skills/seeing-images/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seeing-images", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
seeing-images- GitHub stars
- 150
- Token cost
- ~1.4k tokens
- SKILL.md length
- 532 words
- Files
- 3 (incl. scripts)
- Skills in repo
- 67
- Repo updated
- First seen
- Licence
- MIT
At a glance
Augmented vision tools for analyzing images beyond native visual capabilities.
- Tasked with describing images in detail
- SKILL.md covers When to Use, Known Blindspots (from…, Workflow and Tool Reference, plus 1 more section
- Runs Python scripts from its folder
- Reproducing images as SVGs
What it does
Seeing Images is an agent skill from oaustegard/claude-skills. Augmented vision tools for analyzing images beyond native visual capabilities. Use when tasked with describing images in detail, reproducing images as SVGs, identifying subtle features, comparing image regions, reading degraded text, or any task requiring careful visual inspection. Also use when the image-to-svg skill needs ground truth about colors, shapes, or boundaries.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `CHANGELOG.md` and `scripts/see.py`).
The repository describes itself as: My collection of Claude skills. The licence is MIT.
When your agent uses it
- Tasked with describing images in detail
- Reproducing images as SVGs
- Identifying subtle features
- Comparing image regions
Example prompts
- “/seeing-images”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 90b0f1b. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Seeing Images loads about 1.4k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 532 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from oaustegard/claude-skills at commit 90b0f1b, republished under its MIT licence (© oaustegard). 532 words, ~1,372 tokens.
Download SKILL.mdSave it as
.claude/skills/seeing-images/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- seeing-images
- description
- Augmented vision tools for analyzing images beyond native visual capabilities. Use when tasked with describing images in detail, reproducing images as SVGs, identifying subtle features, comparing image regions, reading degraded text, or any task requiring careful visual inspection. Also use when the image-to-svg skill needs ground truth about colors, shapes, or boundaries.
- metadata.version
- 1.0.1
Seeing Images
Compensatory vision tools based on blindspots measured by vision diagnostic v1-v4 on 2026-03-25. Which model it ran on is not recorded here and it has not been re-run since, so read the thresholds as measured-then: they say a tool exists for each failure, not that the current model fails at exactly that number. Re-run the diagnostic before relying on a specific threshold.
When to Use
Activate this skill when:
- Describing an uploaded image in detail
- Reproducing an image as SVG (use BEFORE drawing to establish ground truth)
- Comparing two images or regions for differences
- Reading text in degraded/compressed/low-contrast images
- Identifying subtle features (gradients, faint overlays, reflections)
- Any image task where accuracy matters more than speed
Known Blindspots (from diagnostics)
Measured, not guessed:
| Blindspot | Threshold | Compensatory Tool |
|---|---|---|
| Luminance contrast | ~15-20 RGB steps invisible | enhance, histogram, sample |
| Gradients | <30-step range invisible | gradient_map, enhance |
| Context color bias | Dress effect, simultaneous contrast | isolate, sample |
| Small elements | <15px effectively invisible | crop, grid |
| Dense counting | Degrades >15 items, ~50% error at 30 | count_elements |
| Subtle atmospherics | Steam, faint reflections lost in noise | enhance, denoise |
Workflow
Setup (one line, every time)
import sys; sys.path.insert(0, '/mnt/skills/user/seeing-images/scripts')
from see import grid, sample, enhance, edges, histogram, isolate, palette, compare, count_elements, gradient_map, denoise, cropQuick Analysis (2-3 tool calls)
grid(path, rows=2, cols=2) # → view the output
sample(path, [(x1,y1), ...]) # → verify colors at points of interestDeep Analysis (for SVG reproduction, spot-the-difference, etc.)
grid(path, rows=3, cols=3) # 1. Overview
palette(path, n=10) # 2. Dominant colors
edges(path, threshold=30) # 3. Shape boundaries
sample(path, [(x1,y1), (x2,y2), ...]) # 4. Exact RGB at points
enhance(path, region=(x,y,w,h), mode='auto') # 5. Reveal low-contrast areas
isolate(path, region=(x,y,w,h)) # 6. Remove context biasTool Reference
All functions in scripts/see.py. Every function that produces an image saves to /home/claude/see_*.png and returns the path. Use view tool on the returned path.
grid(path, rows=3, cols=3, labels=True)
Splits image into labeled cells for systematic inspection. Call it first: it reduces attentional competition.
sample(path, points, radius=3)
Returns exact RGB values at specified pixel coordinates. Use to verify what you think you see. Averages over a small radius to handle noise.
histogram(path, region=None)
Color histogram showing value distribution. Reveals bimodal distributions (hidden gradients), dominant colors, and contrast range. With region=(x,y,w,h), analyzes only that area.
enhance(path, region=None, factor=2.0, mode='contrast')
Boosts contrast in the image or a region. Modes: 'contrast', 'brightness', 'color', 'sharpness'. Use factor=3-5 for near-threshold features.
Show full SKILL.md (218 more words)Show less
edges(path, threshold=50)
Sobel edge detection revealing shape boundaries invisible at low contrast. Lower threshold = more edges (noisier). Output is a white-on-black edge map.
gradient_map(path, region=None)
Computes local gradient magnitude across the image. Bright = high gradient, dark = flat. Reveals gradients below the 30-step detection threshold.
isolate(path, region, padding=20, bg=(128,128,128))
Extracts a region and places it on a neutral gray background. Removes surrounding context that causes simultaneous contrast and Dress-type illusions. The bg parameter defaults to mid-gray to minimize context bias.
compare(path, r1, r2)
Side-by-side comparison of two regions with diff overlay. Highlights pixel-level differences with amplification. Use for spot-the-difference tasks.
count_elements(path, region=None, color_range=None, min_size=3)
Programmatic element counting using connected component analysis. Specify approximate color_range as ((r_min,g_min,b_min), (r_max,g_max,b_max)) to count specific colored elements.
denoise(path, region=None, strength=3)
Median filter to reduce photographic noise, revealing subtle features hidden in the noise floor (like steam, faint reflections).
palette(path, n=8)
Extracts the n most dominant colors using k-means clustering. Returns RGB values and their proportions. Essential for SVG reproduction.
Accuracy Notes
Call grid() first on a complex image. Verify colors near context boundaries
with sample() or isolate(), counts above 15 with count_elements(),
gradients with gradient_map(), and faint features with enhance() before
describing them. Each of these is a row of the blindspot table, so the tool
call is the evidence — perception alone is not.
© oaustegard, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (scripts) in seeing-images of oaustegard/claude-skills.
- SKILL.md
- CHANGELOG.md
- scripts/see.py
Open the folder on GitHubat commit 90b0f1b
Compare with similar skills
Seeing Images next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Seeing Images this skilloaustegard/claude-skills | 150 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Fal Visionnexu-io/open-design | 100k | — | ~295 | Automated safety check: Pass | Apache-2.0 | |
| Vision Sftwshobson/agents | 40k | — | ~2k | Automated safety check: Pass | MIT | |
| Visiongridaco/grida | 2.7k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Senior Computer Visiondavila7/claude-code-templates | 33k | 2 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Agent Code Analyzerruvnet/ruflo | 74k | 2 repos | ~1.5k | Automated safety check: Pass | MIT |
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Vision Sft
wshobson/agents
Fine-tune vision-language models (VLMs) with supervised learning on image+text data.
Vision
gridaco/grida
Query images with a local Ollama vision model without loading the image into the main agent context.
Senior Computer Vision
davila7/claude-code-templates
World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems.
Agent Code Analyzer
ruvnet/ruflo
Agent skill for code-analyzer - invoke with $agent-code-analyzer
Agent Pagerank Analyzer
ruvnet/ruflo
Agent skill for pagerank-analyzer - invoke with $agent-pagerank-analyzer
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Questions about Seeing Images
What does Seeing Images do?
Augmented vision tools for analyzing images beyond native visual capabilities. Seeing Images is an agent skill from oaustegard/claude-skills. Augmented vision tools for analyzing images beyond native visual capabilities.
When should I use Seeing Images?
Seeing Images fits situations like: tasked with describing images in detail; reproducing images as SVGs; identifying subtle features; comparing image regions.
How do I install Seeing Images in Claude Code?
Run `npx skills add oaustegard/claude-skills --skill seeing-images -a claude-code`. Or copy the skill folder (seeing-images in oaustegard/claude-skills) into .claude/skills/seeing-images in your project. Claude Code loads it when a task matches its description.
How do I install Seeing Images in Codex?
Run `npx skills add oaustegard/claude-skills --skill seeing-images -a codex`. Or copy the skill folder (seeing-images in oaustegard/claude-skills) into .agents/skills/seeing-images in your project. Codex loads it when a task matches its description.
Can I use Seeing Images in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add oaustegard/claude-skills --skill seeing-images -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seeing-images, .gemini/skills/seeing-images, .github/skills/seeing-images and .opencode/skills/seeing-images in your project.
What does Seeing Images need to run?
Going by SKILL.md and its folder, Seeing Images needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Seeing Images access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Seeing Images safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Seeing Images use?
Seeing Images is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Seeing Images use?
About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Seeing Images?
Skills that share tags, products or a category with Seeing Images: Fal Vision (nexu-io/open-design, 100k stars), Vision Sft (wshobson/agents, 40k stars), Vision (gridaco/grida, 2.7k stars) and Senior Computer Vision (davila7/claude-code-templates, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Seeing Images?
oaustegard (a GitHub user) maintains it in oaustegard/claude-skills, which has 150 GitHub stars. The repository holds 67 skills in this directory. The repository was last updated on October 9, 2026.
Source: oaustegard/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.