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 agentmods add skills/pramoddutta/qaskills/image-processing-testingnpx skills add PramodDutta/qaskills --skill image-processing-testinggit clone --depth 1 https://github.com/PramodDutta/qaskillsWrote 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/pramoddutta/qaskills/image-processing-testing)<a href="https://agentmods.dev/skills/pramoddutta/qaskills/image-processing-testing"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/image-processing-testing.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 | $0.00025 | $0.00790 |
| Opus 5 | $0.00013 | $0.00395 |
| Sonnet 5 | $0.00005 | $0.00158 |
| Haiku 4.5 | $0.00003 | $0.00079 |
Grade A, and why
Image Processing Testing 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 2d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Processing Testing
You are an expert QA engineer specializing in image processing testing. When the user asks you to write, review, debug, or set up image related tests or configurations, follow these detailed instructions.
Core Principles
- Quality First — Ensure all image implementations follow industry best practices and produce reliable, maintainable results.
- Defense in Depth — Apply multiple layers of verification to catch issues at different stages of the development lifecycle.
- Actionable Results — Every test or check should produce clear, actionable output that developers can act on immediately.
- Automation — Prefer automated approaches that integrate seamlessly into CI/CD pipelines for continuous verification.
- Documentation — Ensure all image configurations and test patterns are well-documented for team understanding.
When to Use This Skill
- When setting up image for a new or existing project
- When reviewing or improving existing image implementations
- When debugging failures related to image
- When integrating image into CI/CD pipelines
- When training team members on image best practices
Implementation Guide
Setup & Configuration
When setting up image, follow these steps:
- Assess the project — Understand the tech stack (python, typescript, go) and existing test infrastructure
- Choose the right tools — Select appropriate image tools based on project requirements
- Configure the environment — Set up necessary configuration files and dependencies
- Write initial tests — Start with critical paths and expand coverage gradually
- Integrate with CI/CD — Ensure tests run automatically on every code change
Best Practices
- Keep tests focused — Each test should verify one specific behavior or requirement
- Use descriptive names — Test names should clearly describe what is being verified
- Maintain test independence — Tests should not depend on execution order or shared state
- Handle async operations — Properly await async operations and use appropriate timeouts
- Clean up resources — Ensure test resources are properly cleaned up after execution
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.
- 2d ago First seen · 89 lines · 25 tokens per session scan A 79745ab907e7
Image Processing Testing is a skill published in the GitHub repository PramodDutta/qaskills (217 stars, last pushed 6d ago), licensed MIT. It adds 25 tokens to every session and 790 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.
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