wissingcc
Community@WissingChen
A skill suite managing the full CS/AI research lifecycle: literature retrieval, idea validation, experiment execution, result analysis, academic writing, and HTML slide decks.
Agent Skills by wissingcc
Showing 11 vetted skills indexed across 1 GitHub repositories.
plain_talk
Rewrites AI output to remove jargon, filler, and enforce conclusion-first phrasing.
slide_deck
Generates self-contained horizontal-paging HTML slide decks from existing research artifacts.
knowledge_keeper
Retrieves, evaluates, and archives academic papers into a local citation-tracked knowledge base.
academic-paper-writing
Drafts and revises CS/AI/Robotics academic manuscripts with evidence-traceable claims and reviewer-oriented structure.
write_md
Improves Markdown readability, plans report figures, and renders self-contained HTML reports.
research_progress
Evaluates research ideas through value, related-work, and feasibility checks before experiment design.
result_analysis
Interprets experiment results against pre-registered expectations and diagnoses which causal link failed.
result_visualization
Generate charts, evidence tables, and argument diagrams for research reports with figure validation.
research_manager
Organizes research project directories, status transitions, and archival rules for a .kilo workspace.
experiment_manager
Manages experiment branches, run reports, artifacts, and promotion workflows for research directions.
skill_rsi
Records skill improvement proposals in an inbox and applies them only after user review.
Frequently Asked Questions About wissingcc
FAQPage SchemaWhat tasks can I accomplish with wissingcc's research skills?▼
You can search and capture literature with citation-graph expansion, validate whether a research idea is worth pursuing, run and checkpoint experiments with convergence accounting, interpret results with statistical verdicts, write CS/AI/robotics manuscripts, and produce HTML slide decks and reports.
Who are these skills designed for?▼
They target academic researchers, PhD students, and ML/robotics engineers who manage multi-stage research projects — from literature review and idea convergence through experiment execution, evidence interpretation, and final paper or presentation delivery.
How do the skills work together in practice?▼
research_manager anchors the .kilo/ project skeleton and file lifecycle; all other skills declare it as a dependency. knowledge_keeper, research_progress, experiment_manager, result_analysis, and result_visualization each own one research phase and explicitly delegate to one another.
What are the prerequisites and dependencies?▼
Every skill except research_manager and plain_talk declares 'requires: research_manager', so the project skeleton skill must be present first. plain_talk must load at the start of every session to enforce jargon-free, conclusion-first output.
How are improvements to the skill family handled?▼
The skill_rsi skill acts as a self-improvement inbox: it records friction points, user corrections, and missing scenarios as proposals, applying changes only after explicit user review — it never silently edits other skills.