Borrowing it
Nothing to install: this file belongs to GabrielOnDelphi/Claude-Tools-for-Delphi. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/GabrielOnDelphi/Claude-Tools-for-Delphi/main/.claude/skills/light-review-FakeTest/SKILL.mdgit clone --depth 1 https://github.com/GabrielOnDelphi/Claude-Tools-for-DelphiWrote 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/gabrielondelphi/claude-tools-for-delphi/light-review-faketest)<a href="https://agentmods.dev/skills/gabrielondelphi/claude-tools-for-delphi/light-review-faketest"><img src="https://agentmods.dev/badge/skills/gabrielondelphi/claude-tools-for-delphi/light-review-faketest/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/gabrielondelphi/claude-tools-for-delphi/light-review-faketest"><img src="https://agentmods.dev/badge/skills/gabrielondelphi/claude-tools-for-delphi/light-review-faketest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 3 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Prompt Injection · line 97 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00090 | $0.02676 |
| Opus 5 | $0.00045 | $0.01338 |
| Sonnet 5 | $0.00018 | $0.00535 |
| Haiku 4.5 | $0.00009 | $0.00268 |
Grade A, and why
light-review-FakeTest 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 8d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/light-review-FakeTest — Test-Integrity Auditor
This skill answers one question: is the suite's green real, or do some tests pass without testing anything? A "fake" test is one that stays green even when the product code it names is broken — zero assertions, Assert.Pass-only, a tautology, a setup-only check, a tautological helper, a vague "something errored" check, or a negative test with no probe.
Scope: this audits EXISTING tests for honesty — whether each one can fail. It does NOT measure code coverage or find missing tests; a suite of 100%-honest tests can still under-test the product. Coverage gaps are a different job — say so if the user conflates the two.
You (the main thread) orchestrate. You do NOT audit the tests yourself — the light-review-FakeTest agent does the per-test analysis. Your job: resolve the scope, establish the green baseline, launch the auditor (sharded if large), optionally run a mutation proof, then summarize.
Parse $args
$args may contain a path (file / folder / several files) and/or a mode keyword:
- default — baseline run + static audit.
staticor--no-run— skip the build+run baseline; static audit only (use when the build infra isn't here or the user just wants the read).deepormutation— after the static audit, PROVE the findings with a git-safe mutation pass (Step 4). Opt-in because it edits product code (and reverts it) and rebuilds repeatedly.
Step 1 — Resolve the test scope
Build the test set — the list of test .pas units to audit:
- Explicit file(s) → use as-is.
- A folder → Glob
<folder>/**/*.pas, then keep only units that are actually tests: Grep them forDUnitX.TestFrameworkorTestFramework(the frameworkuses), plus[Test]or aTTestCasedescendant. Drop helpers/fixtures that contain no tests (still note them — the auditor may need them to resolve helpers). - No argument → discover. Look for a
Tests\orUnitTesting\folder under the project; if none, Grep the repo forDUnitX.TestFramework|TestFrameworkto find test units. Present the discovered set and proceed. If you find more than ~25 test units, print the count and ask whether to audit all or narrow. - No test units found at all → say so and stop. There is nothing to audit; do not invent a scope.
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.
- 8d ago Changed · +2 lines 0a3c301b58b4
- 12d ago First seen · 106 lines · 90 tokens per session scan A 2c4047e82ba1
light-review-FakeTest is a skill published in the GitHub repository GabrielOnDelphi/Claude-Tools-for-Delphi (18 stars, last pushed 5d ago), licensed MPL-2.0. It adds 90 tokens to every session and 2,676 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
migrate-xunit-to-xunit-v3
Migrate .NET test projects from xUnit.net v2 to xunit.v3 and fix v3 breaks. Use for package/CPM conversion, OutputType=Exe, preserving the VSTest or MTP runner (including projects currently using YTest.MTP.XUnit2), incompatible TFMs, async void tests, string-to-Type attributes, custom Fact/Theory/BeforeAfterTest…
go-testing
Trigger: Go tests, go test coverage, Bubbletea teatest, golden files. Apply focused Go testing patterns.
nw-fp-clojure
Clojure language-specific patterns, data-first modeling, REPL-driven development, and spec.
mobiai-ios-testing
Use when writing or running tests in an iOS project — unit tests, UI tests, snapshot tests, choosing the right framework.
junit-5-skill
Generates production-grade JUnit 5 unit and integration tests in Java. Covers assertions, parameterized tests, lifecycle hooks, mocking with Mockito, and nested tests. Use when user mentions "JUnit", "JUnit 5", "@Test", "assertEquals", "Assertions", "Java unit test". Triggers on: "JUnit", "@Test", "assertEquals"…
restore-internals-seams-in-finally-blocks-after-each-test
When delegating a task affected by this skill, include.