AI Agent Skills

Use for building U-Boot artifacts for QEMU firmware boot testing, including defconfig selection, cross compile variables, SPL/TPL, U-Boot proper, FIT or ITB files, BL31…

Stress-tests an already-written game bug fix with adversarial cases selected from the state, timing, identity, lifecycle, persistence, and input surfaces the patch can a…

Turns an abstract game-design seed into a minimal discrete-state rule system by generating conflict-axis candidates, stress-testing with Rule Breaker and Strategy Breake…

Builds an answer-first plan by stating disprovable hypotheses and, for each, the "what would prove me wrong" test and the exact analysis that settles it, so the team tes…

Use when a task needs Playwright-backed browser automation from the shell: open or attach to browser sessions, inspect snapshots and element refs, click/type/fill forms,…

This skill handles all SAP ABAP development tasks: writing and debugging reports, function modules, classes, BAdIs, enhancement spots, user exits, ALV, SmartForms, Adobe…

Author a well-documented GitHub pull request — title and body — for the current branch. Reads the diff and commit trail, infers a Conventional Commits (or repo-native) t…

Challenge, push back, play devil's advocate on AI output or intentions. Use when: challenge this, are you sure, push back, prove it, what if you're wrong, devil's advoca…

Safe-to-fail experiment for Complex domain problems where cause-effect is only visible in retrospect. Two-phase: foreground qualify → background probe → sense result. Us…

Guidelines for writing robust, modern Java tests using JUnit 5, Mockito, and Testcontainers.

Detect and prevent overfitting to historical data via multiple testing corrections and pre-registration. Use when evaluating strategy variants to ensure performance is n…

Prevent train-test contamination, target leakage, and temporal leakage. Use when splitting data, fitting preprocessors, or engineering features for time-series ML.

Test strategy robustness to parameter variation and detect overfitting cliffs. Use when validating that performance is stable across parameter perturbations.

Bypass an LLM's safety/guardrails to make it produce restricted output or ignore its policy. Load when testing an AI product's content controls, "jailbreak", "guardrail…

Unbounded-consumption / denial-of-wallet attacks on LLM apps — force runaway tokens, cost, or latency. Load when testing an LLM product's limits/billing, on "LLM DoS", c…

Extract or steal an ML/LLM model's parameters, training data, or system prompt via query access — model stealing, membership inference, training-data extraction. Load wh…