Learning & Documentation Agent Skills

Use when a user wants an AI, LLM, machine-learning, agent, optimizer, protocol, or infrastructure topic turned into a sourced visual…

Require the learner to explain a concept in their own words before the AI evaluates or extends it.

Generates polished 1080p technical explainer and demo videos with Chinese voiceover, automated subtitles, and structured visual cards…

Explain any topic at five escalating levels — High School, College, PhD, Philosopher, Gigabrain — where each level responds directly to…

Use when drafting ACM FAccT author responses — the short factual-correction rebuttal after preliminary reviews, and, distinctively for the…

Use when preparing an accepted ACM FAccT paper for camera-ready — de-anonymizing and adding the withheld Positionality/Acknowledgements…

Use when positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML, HCI, law and policy, STS and…

Use when revising an ACM FAccT paper so that a fairness/accountability/transparency contribution is legible on the first page to a mixed…

Swap faces in a video using AI via the HeyGen API.

Verifies the factual claims in a technical document against sources, and reports which hold, which do not, and which could not be checked.

Track performance across sessions and reduce scaffolding as competence grows.

Use when packaging a USENIX FAST artifact for the USENIX Artifact Evaluation scheme (Artifacts Available, Artifacts Functional, Results…

Use when drafting USENIX FAST author responses, covering the short pre-notification rebuttal during the author-response period and…

Use when positioning a USENIX FAST submission against the storage-systems literature across FAST, OSDI, ATC, SOSP, EuroSys, HotStorage…

Use when reasoning about how a USENIX FAST submission is evaluated, covering double-blind program-committee review with outside referees…

Use when deciding what belongs in a USENIX FAST paper body versus its artifact and appendices, covering the USENIX two-column page budget…

Use when deciding whether a storage project belongs at USENIX FAST or should be routed to OSDI, ATC, NSDI, EuroSys, HotStorage, MSST…

Use when revising a USENIX FAST paper for a storage contribution on the first page, a design/mechanism narrative a storage reviewer can…

Enumerate every observable entry point of the application from P1+P2 evidence, group them into feature candidates, and scaffold a…

Create or normalize a feature folder under `doc/project/features/<feature>/`.

Give effective feedback that promotes learning and growth.