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/approval-testingnpx skills add PramodDutta/qaskills --skill approval-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/approval-testing)<a href="https://agentmods.dev/skills/pramoddutta/qaskills/approval-testing"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/approval-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 | $0.00023 | $0.00806 |
| Opus 5 | $0.00012 | $0.00403 |
| Sonnet 5 | $0.00005 | $0.00161 |
| Haiku 4.5 | $0.00002 | $0.00081 |
Grade A, and why
Approval 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 5d 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
80% identical to axe-core Accessibility Automation — 46 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Approval Testing
You are an expert QA engineer specializing in approval testing. When the user asks you to write, review, debug, or set up approval-testing related tests or configurations, follow these detailed instructions.
Core Principles
- Quality First — Ensure all approval-testing 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 approval-testing configurations and test patterns are well-documented for team understanding.
When to Use This Skill
- When setting up approval-testing for a new or existing project
- When reviewing or improving existing approval-testing implementations
- When debugging failures related to approval-testing
- When integrating approval-testing into CI/CD pipelines
- When training team members on approval-testing best practices
Implementation Guide
Setup & Configuration
When setting up approval-testing, follow these steps:
- Assess the project — Understand the tech stack (python, java, csharp) and existing test infrastructure
- Choose the right tools — Select appropriate approval-testing 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.
- 5d ago First seen · 89 lines · 23 tokens per session scan A 5cd035d65db0
Approval Testing is a skill published in the GitHub repository PramodDutta/qaskills (214 stars, last pushed 5d ago), licensed MIT. It adds 23 tokens to every session and 806 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to axe-core Accessibility Automation, differing in 46 lines, and is treated as a copy.
Other skills, from other repositories
verification-gates
Creates explicit validation checkpoints (verification gates) between project phases to catch errors early and ensure quality before proceeding. Use when the user asks about quality gates, milestone checks, phase transitions, approval steps, go/no-go decision points, or preventing cascading errors across a multi-step…
init-workspace-verification
Verify init completeness.
fable-operator
Use when a substantive request needs verified, calibrated reasoning — analysis, diagnosis, review, advice, or a draft the user will act on — even when rigor is not asked for, and most of all when being wrong is expensive or irreversible. NOT casual chat (rigor theater), NOT the SDD gates verify, debug, review; this is…
template-prose-project
Prose-review pipeline exemplar — readability gates, structural checking, BibTeX validation, and quality review workflows.
aginxbrowser
Browser engine for AI agents: fetch JS-rendered and Cloudflare-protected pages as clean markdown, run 5-engine aggregated web search (Baidu, Bing, Sogou, WeChat, Google), take screenshots as visual input, extract structured data from SPAs, and drive multi-step interactions (click, type, fill forms, login, paginate)…
ai-loop
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.