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 PramodDutta/qaskills --skill allure-report-generatorgit 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/allure-report-generator)<a href="https://agentmods.dev/skills/pramoddutta/qaskills/allure-report-generator"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/allure-report-generator/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/pramoddutta/qaskills/allure-report-generator"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/allure-report-generator.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 | $0.00032 | $0.08635 |
| Opus 5.5 | $0.00013 | $0.03454 |
| Sonnet 5.5 | $0.00006 | $0.01727 |
| Haiku 4.5 | $0.00003 | $0.00864 |
Grade D, and why
Allure Report Generator scanned grade D with 4 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
const response = await fetch('http://localhost:3000/api/orders', { method: 'POST', Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
"allure:clean": "rm -rf allure-results allure-report", Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.post( Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
import { execSync } from 'child_process'; How it starts
The opening of the file, as written. The whole thing — 1,124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Allure Report Generator
Allure is an open-source test reporting framework that produces rich, interactive HTML reports from test execution results. Unlike basic test reporters that show pass/fail summaries, Allure provides detailed test categorization, step-by-step execution breakdowns, attachment support for screenshots, logs, and videos, historical trend tracking across builds, and environment metadata. This skill guides AI coding agents through configuring Allure reporters for popular testing frameworks, annotating tests with meaningful metadata, integrating with CI/CD pipelines, and establishing report hosting strategies that give teams comprehensive test visibility.
Core Principles
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Reports Serve Multiple Audiences: A good test report provides quick pass/fail summaries for managers, detailed failure analysis for developers, trend data for QA leads, and categorized views for test strategists. Allure's multi-view design supports all these personas from a single report.
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Annotations Are Documentation: Test step annotations, severity labels, and feature/story categorization serve as living documentation of test intent. Well-annotated tests in Allure reports communicate what is being tested and why without requiring code access.
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Attachments Accelerate Debugging: Screenshots, DOM snapshots, network logs, and video recordings attached to test steps eliminate the need to reproduce failures locally. Every failure should carry sufficient attachments for diagnosis from the report alone.
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History Reveals Patterns: A single test run is a snapshot. Historical trend data across builds reveals flaky tests that oscillate between pass and fail, degrading tests with gradually increasing failures, and regression patterns that correlate with specific changes.
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Categories Group Failures by Root Cause: Allure categories classify failures by type (product defect, test defect, infrastructure issue) rather than by test name. This grouping accelerates triage by surfacing the most common failure modes across the entire suite.
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 First seen · 1,124 lines · 32 tokens per session scan D 002db37f299a
Allure Report Generator is a skill published in the GitHub repository PramodDutta/qaskills (237 stars, last pushed 5d ago), licensed MIT. It adds 32 tokens to every session and 8,635 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it D with 4 findings (sends data to an external url, recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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