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EvoScientist
GitHub 제작자 프로필

EvoScientist

2개 GitHub 저장소에서 수집된 18개 skills를 저장소 단위로 보여줍니다.

수집된 skills
18
저장소
2
업데이트
2026-06-19
저장소 탐색

저장소와 대표 skills

paper-graph
기타 중등 후 교사

Use this skill to map the **genealogical lineage and historical progression** of a research field. It is designed to visualize the **evolutionary path of ideas**, showing how technical challenges in earlier works were addressed by subsequent research improvements. The final deliverable is a Markdown file with embedded Mermaid diagrams the user can paste into a viewer or commit to their repo. Trigger this when the user needs to understand the **developmental trajectory of a topic**, the 'family tree' of a model, or how a research line matured over multiple years. Do NOT trigger for queries seeking **inventories of specific artifacts**, such as lists of common datasets, benchmarks, or libraries. Avoid this for finding a single 'latest' paper, performing simple keyword search, or conducting head-to-head technical comparisons between specific models. This skill is meant for synthesizing a **chronological narrative of improvement** across multiple works, not for cataloging currently available resources or one-off

2026-06-19
paper-navigator
기타 중등 후 교사

Find and read academic papers (S2 + arXiv). Disambiguate ambiguous queries, search by keyword + citation graph + recommendations + snippets, judge by author-graded rubric, and read with L1/L2/L3 strategy. Trigger phrases: find papers, search papers, related work, citation analysis, recent advances, read this paper, baseline with code. Do NOT use for: survey reports (research-survey), idea generation (research-ideation), Related Work sections (paper-writing).

2026-06-09
paper-figures
기타 생물 과학자

Use this skill to produce standalone, publication-ready PNG graphics and reproducible matplotlib scripts from tabular data (CSVs or DataFrames). This tool is built specifically for rendering numerical data into formal scientific visualizations—including scatter, line, bar, pie, ring, bubble, tornado, KDE, violin, box, heatmap, histogram, and area charts, plus composite multi-panel figures that combine these types in a single image—for scholarly manuscripts. Only trigger this skill when the final deliverable is an individual image file. Do not use this skill for interactive dashboards or HTML-rendered outputs (Plotly, Streamlit, Quarto, Jupyter notebooks), nor when the request involves building a container document or presentation that includes charts (slide deck, conference poster). Finally, it is not for non-data conceptual illustrations like flowcharts, algorithm schematics, or process diagrams. This skill focuses on high-fidelity data rendering into final image files, not presentation design, document layo

2026-06-08
evomath-tao
기타 중등 후 교사

Use this skill whenever the user submits a non-trivial mathematical claim that needs a rigorous proof or audit. Trigger on IMO/Putnam/USAMO/Olympiad-style problems, ML/AI theoretical statements, research conjectures, suspected-false claims, multi-step proofs the user already failed on, proof drafts with possible hidden assumptions, or any request containing 'prove rigorously', 'verify this', 'is this true', 'find the gap', 'audit my proof', 'find a counterexample', or 'use EvoMath' that targets a mathematical claim. Activate also when the problem requires more than three reasoning steps. Do NOT use for single-step calculations, definition lookups, textbook exercises with a known recipe, code analysis tasks, literature survey questions, pure symbolic manipulation, or non-mathematical applications of those trigger phrases (e.g., 'is it true that GPT-4 can solve math?', 'verify this LaTeX syntax'); hand those back instead.

2026-05-12
evo-memory
데이터 과학자

Manages persistent research memory across ideation and experimentation cycles. Maintains two stores: Ideation Memory M_I (feasible/unsuccessful directions) and Experimentation Memory M_E (reusable strategies for data processing, model training, architecture, debugging). Three evolution mechanisms: IDE (after research-ideation), IVE (after experiment failure — classifies failures as implementation vs fundamental), ESE (after experiment success — extracts reusable strategies). Use when: updating memory after completing research-ideation cycles or experiment pipelines, classifying why a method failed (implementation vs fundamental failure), starting a new research cycle needing prior knowledge, user mentions 'update memory', 'classify failure', 'what worked before', 'research history', 'evolution'. Do NOT use for running experiments (use experiment-pipeline), debugging experiment code (use experiment-craft), or generating ideas (use research-ideation).

2026-04-14
experiment-pipeline
데이터 과학자

Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and experiment-craft (5-step diagnostic on failure). Use when: user has a planned experiment, needs to reproduce baselines, organize experiment workflow, or systematically validate a method. Do NOT use for debugging a specific experiment failure (use experiment-craft) or designing which experiments to run (use paper-planning).

2026-04-14
research-ideation
데이터 과학자

End-to-end research ideation pipeline: literature grounding → multi-track idea generation (3 personas: innovator/pragmatist/critic) → iterative refinement → ELO tournament ranking → update evo-memory (IDE) → user selects direction → expand into manuscript-quality proposal. Use when: user wants to find a research direction, brainstorm ideas, evaluate idea novelty, design a novel solution, rank/compare research ideas, or generate a research proposal. Do NOT use for finding/searching/reading papers (use paper-navigator), literature survey reports (use research-survey), or planning a paper (use paper-planning).

2026-04-14
research-survey
기타 중등 후 교사

Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary section refinement → final assembly. Produces survey-grade output with taxonomy-based method analysis, LaTeX formalizations, comparative tables, and dense citations. Use when: user wants a literature review, research survey, field overview, or systematic synthesis of multiple papers. Do NOT use for finding/searching papers (use paper-navigator), generating research ideas (use research-ideation), or writing a paper's Related Work section (use paper-writing).

2026-04-14
이 저장소에서 수집된 skills 16개 중 상위 8개를 표시합니다.
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