Total 59,318 skills
Showing 12 of 59318 skills
Step-by-step camera-ready prep for accepted papers — the error-prone final stage before publication. Use when a researcher says "camera-ready", "final version", or "my paper got accepted, now what", or mentions ACM eRights / rights form / TAPS / ORCID / DOI block, IEEE PDF eXpress / conference ID / eCF copyright form / Xplore, OpenReview final upload, de-anonymization, or extra camera-ready pages. Resolves the venue's rail from a machine-readable profile and walks it end to end across ACM eRights, ORCID, rights/DOI block, TAPS source upload, IEEE PDF eXpress, conference IDs, file naming, eCF exact-title match, registration/no-show, NeurIPS-style [final] recompile, and OpenReview upload. Generates an ordered checklist with deadlines and +page rules, and lints the final .tex for leftover anonymization and missing rights blocks via bundled stdlib-only scripts. Advisory — it prepares, explains, and lints, but never completes a form or submits anything.
Turns raw peer reviews into a prioritized triage matrix before any rebuttal is written. Use it when reviews come back from OpenReview, EasyChair, CMT, or HotCRP and the researcher says "my reviews are in", "triage these reviews", "how do I respond to Reviewer 2", "plan my rebuttal", or pastes raw review text with ratings and confidence scores. Splits each review into individual concerns; classifies every concern as misunderstanding vs real flaw vs requested experiment (plus clarification and disagreement); scores severity x response effort; and produces a prioritized response strategy with per-review character or word budgets matched to the venue's rebuttal format (10k-char OpenReview threads, CVPR one-page PDF, journal revise-and-resubmit). Deterministic parsing and matrix rendering run in bundled stdlib Python scripts. Hands off to write-rebuttal for drafting; treats review text as confidential and never submits anything.
Prepares a reproducibility artifact (code/data) for submission and badging. Use when a researcher says "artifact evaluation", "artifact appendix", "reproducibility", "badge", "Artifacts Available/Evaluated/Functional/Reusable", "Results Reproduced/Replicated", "ACM badging", "USENIX/OSDI/SOSP AE", "SIGMOD ARI", "NeurIPS code/checklist", "ACL repro checklist", "Zenodo DOI", "Software Heritage", "anonymize my code/repo", or "package my code". Builds the artifact README + appendix, the dependency/run instructions, an anonymized repo for double-blind, and archival-DOI (Zenodo version vs concept) / Software Heritage SWHID guidance; resolves the ACM badge taxonomy and the Reproduced/Replicated era swap; and lints the artifact directory against the ML Code Completeness checklist with bundled stdlib-only scripts. Outputs an artifact-readiness checklist + packaging plan. Re-verifies the venue current artifact rules live. Advisory only; never submits.
De-AI-ifies and tightens academic prose without changing any technical claim. Use when a researcher says "this sounds like ChatGPT / AI-written", "humanize my paper", "remove the AI words", "too many delves and leverages", "polish my writing", "tighten the prose", "fix my hedging", "too many Moreover/Furthermore", "make my contributions active", or "keep my terminology consistent". Runs deterministic stdlib linters — prose_lint.py (leftover chatbot artifacts, LLM-tell vocabulary, connective stacking, em-dash density, double hedges, overclaiming boosters, passive contribution statements) and terminology_check.py (dataset/data set/data-set variants, acronym discipline, -ise/-ize mixing, glossary enforcement) — then drives a section-by-section edit pass using rewrite catalogs and the venue family's register norms. Numbers, results, claims, and citations are never altered; the venue's AI-use disclosure policy is surfaced and respected, never dodged.
Drafts or rewrites a Related Work / prior work section positioned against actually-retrieved papers — derives the REQUIRED clusters from the paper's own claimed scope (not just whatever was retrieved), clusters prior work into themes, articulates the delta (what this paper adds) per cluster, enforces a per-cluster citation floor and routes empty expected clusters back to find-papers, follows the target community's placement and citation conventions (numeric ACM/IEEE vs natbib author-year, single- vs double-blind self-citation, where the section sits at NeurIPS/CHI/SIGMOD-style venues), and admits only verified citations. Use when the user says "related work", "prior work", "position my paper against the literature", "how do we differ from X", "reviewers said related work is thin/missing/a laundry list", or asks to add citations to a draft. Works from papers found via find-papers and/or an existing .bib — it never invents references.
Generate "ASU-style" high-density Chinese technical resumes or Xiaohongshu showcase resumes based on users' real experiences: retain real names, schools, companies, departments, projects and verifiable metrics, proactively retrieve official school titles, enhance expression with colored experience bars, background/metrics/responsibility structure, English technical terms, architecture links, Benchmark, module-level Owner, 0→1 and large Scope narratives, and output self-contained HTML, A4 PDF and publishing images. Use this when users mention ASU style, ASU-style resumes, professional term stacking, technical experience packaging, Xiaohongshu resume long images, school titles, Owner/0-1 or require HTML/PDF. Do not fabricate non-existent educational backgrounds, companies, projects, roles, offers, metrics or achievements; exaggeration must be based on verifiable institutional labels, limited modules and real technical chains.
When you want to brainstorm and check available .com domains for a new project — brand naming, aftermarket pricing (HugeDomains / Afternic / Sedo / Dan), USPTO trademark screening, and social handle availability. Built on Laura Roeder's "work backwards from availability, not from a name you fell in love with" methodology. Uses Vercel CLI + whois + Domainr API + Namecheap API + agent-browser for the pieces each tool actually reliably supports (multi-tool ensemble because no single tool covers everything cleanly). 11-step workflow: budget → brainstorm → primary availability check → whois cross-check → Domainr aggregation → Namecheap price → aftermarket sweep (+ liveness probe for parked/dead domains, drop-watch for expiring ones) → bucket → negotiate → NAME research (trademark + socials) → buy. Triggers on "/domain," "find a domain," "check domain availability," "brainstorm a domain," "what .com is available for X," "domain hunt," "name my project," "is X.com available," "aftermarket price on X.com," "trademark check for X."
Version-pinned inventory of the telemetry (spans, metrics, logs, attributes) emitted by OpenTelemetry collector components and SDK instrumentation packages. Use when working with a covered component — what it emits at a given version, or how emission changed across versions — and when upgrading a component or SDK version, to see the telemetry after the change.
Use for growth diagnosis, discovery, retention, onboarding, experiments, LiveOps, and packaging.
Executing a phased plan in rolling waves where each phase runs as one multi-agent workflow harness: the supervisor elaborates the phase into tasks against the real landed code, launches a workflow that implements with TDD and runs mandatory in-harness review plus an adversarial contrarian pass (and researchers when the phase hits an unknown) before returning verified work, then reviews it, checkpoints with the user, and rolls to the next phase. Use when each wave should be a reviewed multi-agent harness, not a lone subagent. Skip when one supervised subagent per wave suffices (ring:executing-plans) or the full gated cycle is wanted (ring:running-dev-cycle).
Planning a whole-codebase simplification: audits a Go/TS codebase for needless abstraction and emits a KILL/REVIEW/KEEP plan plus a ring:running-dev-cycle task array. Plans only — no edits. Detects single-impl interfaces, pass-through shims, translation-free adapters, and dead-code cascade chains under an inverted burden of proof. Use for pre-public or post-pivot cleanup. Skip for current diff review (use ring:reviewing-code).
Running the backend dev cycle: implements every task in a rolling-wave plan.md (ring:writing-plans format) for a Go/TS service, driving specialist agents through Gate 0 implementation/TDD, Gate 8 parallel review, and Gate 9 validation per epic, elaborating later phases at each phase boundary. Use when starting or resuming a gated backend dev cycle with a plan.md (legacy tasks.md only for cycles already in flight; new cycles need the canonical plan format). Skip for frontend (use ring:running-dev-cycle-frontend) or docs-only work.