Design, audit, and strengthen experimental validation for IEEE manuscripts using routed claim-evidence checks. Use when planning experiments, selecting baselines, designing ablations, choosing metrics, checking fairness, adding robustness tests, explaining results, analyzing complexity, building claim-to-evidence matrices, or responding to reviewer concerns about insufficient experiments.
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Use this skill to decide whether the experiments prove the paper's claims. The primary output is an evidence audit, not generic advice.
Do not design experiments from memory alone. Follow the routing protocol and load the selected fragments.
manifest.yaml.always_load.task_type: classification / detection / regression / control / signal-processing / communications / optimization / hardware-system / general.evidence_type: baseline / ablation / robustness / complexity / statistical / real-world / reproducibility.failure_mode: missing-traditional-baseline / unfair-comparison / weak-ablation / no-condition-test / overclaimed-results / insufficient-reproducibility.stage: planning / audit / result-writing / reviewer-response.Default output:
Detected axes: task_type=..., evidence_type=..., failure_mode=..., stage=...
Claim-evidence matrix
Claim | Required evidence | Current evidence | Missing experiment | Review risk
Priority fixes
1. ...
For experiment planning, return an experiment plan with baselines, metrics, variables, controlled conditions, and expected claims.
For result writing, return IEEE-style result paragraphs and flag any claim that lacks evidence.
Do not invent numerical results, datasets, baseline performance, p-values, hardware metrics, or statistical significance.
Do not recommend unnecessary experiments that do not support a stated claim.
Do not treat "more experiments" as automatically better. Prioritize experiments that close the reviewer's proof gap.
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Check, clean, verify, and improve IEEE citations, references, BibTeX entries, citation positioning, related-work logic, DOI metadata, venue names, and reference formatting using routed citation and metadata guidance. Use when preparing IEEE manuscripts, fixing bibliography errors, verifying reference completeness, improving related work, checking whether citations support claims, or identifying missing classic/recent baselines.
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Audit, redesign, generate, and improve IEEE manuscript figures, tables, captions, result presentation, plotting scripts, visual polish, hybrid Python/R plus vector-editor workflows, publication-ready matplotlib house style, and layout using routed visual-evidence checks. Use when checking or creating plot readability, axes, legends, line overlap, table structure, metric reporting, captions, grayscale accessibility, IEEE one-column/two-column layout, figure/table placement, claim-evidence mapping, reviewer first-impression risks, matplotlib/seaborn or ggplot2 figure code, SVG/PDF/TIFF/PNG export, Illustrator/Inkscape/PowerPoint/Figma finishing plans, or IEEE-style engineering evidence graphics.
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Diagnose, fix, and improve IEEEtran LaTeX manuscripts using routed template, layout, float, equation, algorithm, table, bibliography, and PDF-compliance guidance. Use when fixing IEEE LaTeX compile errors, overfull boxes, float placement, two-column layout, figure sizing, tables, equations, algorithms, BibTeX, citation commands, template compliance, or final submission PDF checks.
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Read, decompose, and analyze IEEE-style papers using routed technical-reading workflows. Use when extracting problem setting, object-method-condition logic, contributions, method pipeline, equations, datasets, baselines, metrics, ablations, limitations, replication details, citation role, related-work positioning, implementation notes, or reviewer-style assessment from a paper, PDF, abstract, or manuscript excerpt.
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Polish, translate, diagnose, and restructure technical manuscript text into IEEE-style academic English using routed failure-mode guidance. Use for IEEE abstracts, introductions, related work, methods, experiments, conclusions, figure captions, rebuttals, Chinese-to-English technical writing, AI-like or template-like academic prose, and engineering prose that needs clearer problem logic, contribution framing, method rationale, evidence discipline, natural author voice, or reviewer-ready wording.
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Draft, diagnose, and improve IEEE rebuttals, revision plans, cover letters, response letters, and point-by-point replies using routed reviewer-comment handling. Use when responding to IEEE reviewer or editor comments about novelty, scope, method, experiments, baselines, figures, tables, citations, writing, LaTeX formatting, limitations, compliance, technical correctness, or reviewer comments that appear generic, contradictory, unsupported, careless, or possibly AI-generated.
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