Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add oaustegard/claude-skills/plugin install media-processingWrote 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/oaustegard/claude-skills/seeing-images)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/seeing-images"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/seeing-images/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/oaustegard/claude-skills/seeing-images"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/seeing-images.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 | $0.00070 | $0.01277 |
| Opus 5.5 | $0.00028 | $0.00511 |
| Sonnet 5.5 | $0.00014 | $0.00255 |
| Haiku 4.5 | $0.00007 | $0.00128 |
Grade A, and why
seeing-images 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 1mo 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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, crop
Quick Analysis (2-3 tool calls)
grid(path, rows=2, cols=2) # → view the output
sample(path, [(x1,y1), ...]) # → verify colors at points of interest
Deep 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 bias
What ships with it
2 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.
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.
- 1mo ago Changed · +4 lines 1388304951ed
- 1mo ago First seen · 103 lines · 70 tokens per session scan A a3a4e15b53e0
seeing-images is a skill published in the GitHub repository oaustegard/claude-skills (157 stars, last pushed yesterday), licensed MIT. It adds 70 tokens to every session and 1,277 once invoked, about $0.0003 per session on Opus 5.5. 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 skills, from other repositories
superdesign
Design or redesign frontend UI, presentations, and graphics on the Superdesign canvas with a choice of leading AI models. Use whenever the user wants to design a page, feature, flow, slide deck, or brand-new product; improve or reproduce existing UI; compare design results across top models; explore visual variants…
figma-to-code
Generate production-ready React/Next.js code from Figma designs. Instructs proper Figma MCP tool usage, component reuse strategies, and variant mapping. CRITICAL: ALWAYS use this skill when user provides a Figma link or mentions implementing/redesigning from Figma design. Never attempt manual implementation without…
Linear
Managing Linear issues, projects, and teams. Use when working with Linear tasks, creating issues, updating status, querying projects, or managing team workflows.
smb-sales-boost
Find, preview and export growing local businesses (SMB leads) from the SMB Sales Boost database through its REST API - search by keyword, location and buying signals, preview for free, export CSV/JSON/XLSX, re-download past exports, enrich lists of website URLs, manage saved searches, keyword lists, email schedules…
bpmn-xml-generator
Generate well-formed, schema-valid BPMN 2.0 XML for a target process engine (Stateway, Camunda 8 / Zeebe, or Flowable). Use this skill whenever the user asks to create, write, design, model, or define a business process, workflow, or BPMN diagram — even if they just describe a flow in plain language ("I need a process…
balzac
Balzac is an AI content platform CLI. Create workspaces, manage SEO keywords, generate article suggestions, write articles, publish content across integrations, and monitor Google Search Console performance. Supports workspaces, keywords, suggestions, briefings, articles, competitors, links, integrations, search…