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 katalon-labs/true-skills --skill test-reportinggit clone --depth 1 https://github.com/katalon-labs/true-skillsWrote 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/katalon-labs/true-skills/test-reporting)<a href="https://agentmods.dev/skills/katalon-labs/true-skills/test-reporting"><img src="https://agentmods.dev/badge/skills/katalon-labs/true-skills/test-reporting/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/katalon-labs/true-skills/test-reporting"><img src="https://agentmods.dev/badge/skills/katalon-labs/true-skills/test-reporting.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 | $0.00181 | $0.03755 |
| Opus 5 | $0.00090 | $0.01878 |
| Sonnet 5 | $0.00036 | $0.00751 |
| Haiku 4.5 | $0.00018 | $0.00376 |
Grade A, and why
test-reporting 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 10d 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Katalon Test Reporting
Use this skill when someone outside QA asks a question about quality and the answer has to survive being asked where it came from. It reads the analyze stage and feeds the plan stage. The output is an answer with the named specifics behind it, never a metric dump. release-analyze judges one release; this skill reports the direction across several and writes what a manager says out loud.
Availability Boundary
State the boundary before promising a report, because most of what "reporting" normally means is not an MCP call.
- Available via MCP. The metric surface:
fetch_requirement_data(coverage status),fetch_test_case_data(case quality signals),fetch_test_stability_data(flakiness),fetch_test_configuration_data(configuration coverage),fetch_defect_data(defect status and context),find_test_results/read_execution/read_execution_test_results(execution history, and the only data that carries its own dates),find_iterations(the period spine), andlist_projects/list_repositories/find_test_suites/read_test_suite/find_test_casesto establish what each number is counted over. - Not directly available, and no tool exists to add.
- No trend or aggregation tool. Nothing in the MCP returns a series, an average, or a delta. Every trend here is assembled by looping periods yourself.
- No point-in-time read. Every
fetch_*_datatool returns current state. You cannot ask what requirement coverage was at release 3.0. Only execution records carry dates. - No dashboard, chart, or report entity. Dashboards are a TestOps UI surface. This skill writes text and a snapshot file, nothing else.
- No publishing surface. The MCP cannot post to Slack, Confluence, email, or a deck. Hand the written brief back to the user and let them place it.
- No Release or Build entity. Bind periods to iterations via
find_iterations, or to explicit date ranges. Never to a release object. - No escaped-defect flag.
fetch_defect_datareturns status and context, not whether a defect reached production. Ask the user which ALM field classifies it. If there is none, report "defects opened after the release run" and label it as a proxy. - No effort, cost, headcount, or cycle-time data. That is the
test-estimationgap. Say so and stop. Never estimate effort from test counts. - No custom fields or tags. Any team dimension (component, squad, product line) has to come from folder or suite structure, or from the user.
- The workaround that makes trending real. A snapshot file written on every run, plus the execution-dated series that needs no snapshot. See
references/snapshot-and-trend.md. The first run establishes a baseline and says so instead of inferring a direction.
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.
- 10d ago First seen · 203 lines · 181 tokens per session scan A 894a27836cb4
test-reporting is a skill published in the GitHub repository katalon-labs/true-skills (8 stars, last pushed yesterday), licensed MIT. It adds 181 tokens to every session and 3,755 once invoked, about $0.0009 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 2026-08-31.
Other skills, from other repositories
screen-reader-testing
Test web applications with screen readers including VoiceOver, NVDA, and JAWS. Use when validating screen reader compatibility, debugging accessibility issues, or ensuring assistive technology support.
web3-testing
Test smart contracts comprehensively using Hardhat and Foundry with unit tests, integration tests, and mainnet forking. Use when testing Solidity contracts, setting up blockchain test suites, or validating DeFi protocols.
temporal-python-testing
Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.
data-quality-frameworks
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
e2e-testing-patterns
Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.
workflow-patterns
Use this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.