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Found 16 Skills
Guides pre-writing planning for academic papers with 4 structured steps: story design (task-challenge-insight-contribution-advantage), experiment planning (comparisons + ablations), figure design (pipeline + teaser), and 4-week timeline management. Includes counterintuitive planning tactics (write a mock rejection letter to identify weaknesses before writing, narrow before broad claims, design ablations first). Use when: user wants to plan a paper before writing, design story/contributions, plan experiments, create figure sketches, set a writing timeline, or write a pre-emptive rejection letter for planning purposes. Do NOT use for actual writing (use paper-writing), running experiments (use experiment-pipeline), self-reviewing a finished draft (use paper-review), or finding research problems (use research-ideation).
Guides writing effective rebuttals after receiving peer review feedback. Covers review diagnosis (score-driven color-coding), response strategy (champion identification, common-theme consolidation), tactical writing (18 rules), and counterintuitive rebuttal principles. Use when: user received reviewer scores/comments, needs to write a rebuttal or author response, wants to respond to specific criticism (e.g. 'limited novelty', 'missing baselines'), mentions 'rebuttal', 'reviewer comments', 'author response', or 'respond to reviewers'. Do NOT use for pre-submission self-review (use paper-review instead).
Guides research ideation through a 5-step goal-driven workflow: define long-term goal, build literature tree (novelty + challenge-insight), select a problem (well-established solution check), design a solution (cross-domain transfer + decomposition), validate and iterate. Also covers structured paper reading (3 depth levels). Use when: user wants to find a research direction, brainstorm ideas, build field vision, do a literature review, evaluate idea novelty, or read papers systematically. Do NOT use for comparing/ranking existing ideas (use idea-tournament) or planning a paper (use paper-planning).
Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.