skills/table-results-review/SKILL.md
Review ML/AI result tables, LaTeX table files, captions, provenance, and paper table style. Use for benchmark, ablation, metric, model-spec, and compute tables.
npx skillsauth add a-green-hand-jack/ml-research-skills table-results-reviewInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Audit standalone paper tables before they become paper evidence, meeting material, or rebuttal material.
Use this skill when:
tables/results.tex and inserts them into sections with \input{tables/results}Do not use this skill for rendered figure assets or plot styling. Use figure-results-review for figures/*.pdf, figures/*.png, and figures/*.tex figure bundles. Use paper-evidence-board when the main task is linking many figures and tables to claims across the whole paper.
Pair this skill with:
paper-result-asset-builder when a paper-facing table needs to be generated or regenerated from CSV result files before table reviewpaper-evidence-gap-miner when the table review reveals a missing comparison, slice, variance, or baseline and existing CSVs may already contain itpaper-evidence-board when tables must be linked to paper claims, sections, reviewer risks, and actionsbaseline-selection-audit when a comparison table may miss important baselines or use unfair settingsresult-diagnosis when table numbers are surprising, unstable, negative, or contradictoryexperiment-design-planner when a table exposes missing controls, seeds, metrics, or ablationsexperiment-report-writer when raw logs need a structured report before table reviewconference-writing-adapter when final table narrative or compactness must match a target venueresearch-project-memory when claim/evidence/provenance/risk/action/handoff updates should persist across sessions.tex source, table description, caption, main-text callout, and provenance.submit-paper.table float inside wraptable; use an inline block with local caption/label handling, then tune wrap line count, width, font size, \tabcolsep, and small local \vspace by visual iteration.Collect:
tables/results.tex\input{tables/results} or equivalentCLM-###, EVD-###, TAB-###, RSK-###, or ACT-###Rewrite the intended evidence relation:
This table supports [claim] by showing [comparison/ranking/trend/tradeoff] under [setup].
If that sentence cannot be written, route to paper-evidence-board before polishing the table.
For paper tables, identify the standalone source:
tables/table_name.tex
Inspect:
table or table*tabular, tabularx, longtable, booktabs, resizebox, small, or custom macros\caption{}, \label{}, footnotes, arrows, bold/underline, row groups, column groups, and missing valuesFlag the bundle as incomplete if it lacks caption, label, callout, source provenance, or a clear bolding/rounding/missing-value rule.
Produce a table description before judging the caption.
The table description should state:
Do not put the full table description into the caption. Use it as the audit record that checks whether the caption and paper prose are faithful to the table.
For each table, answer:
Assign one status:
supports-claimsupports-narrower-claimambiguouscontradicts-claimdiagnostic-onlynot-readyCheck:
[H] still may leave vertical skips, so fix local whitespace in or around the table before changing global settingswraptable layouts, optional line count [N], width, caption height, font size, and \tabcolsep are documented as local layout choices rather than unexplained magic constantsFlag any issue that could cause a reviewer to misread the result.
Check:
If the table lacks necessary uncertainty or provenance, decide whether to rerun, add columns/footnotes, weaken the claim, or move the table to appendix/diagnostic status.
For each table, produce:
.tex, source data/log/config/report, table-generation parameters, experiment parameters, and source certaintyCaption pattern:
[What the table reports.] We compare [methods] on [task/dataset] using [metrics; direction] under [key experiment parameters].
[Grouping or fairness detail.] [Takeaway tied to the claim]. Bold marks [bolding rule].
For model-spec, metric-definition, or method-comparison tables:
[What the table defines or compares.] Columns summarize [fields] used in [paper section or experiment].
[Interpretive note.] [Takeaway tied to the claim or reader task].
Do not put every hyperparameter in the caption. Include the parameters needed to interpret the claim. Put full provenance in the review report, appendix, artifact, or paper/.agent/ record.
For every issue, route to one or more actions:
fix-table-wrapper: stale caption, label mismatch, unclear bolding rule, wrong resize, broken footnote, or row/column mismatch in tables/*.texedit-table: grouping, decimals, bolding, footnotes, missing values, row/column order, or metric arrowsrewrite-caption: setup, metric, takeaway, caveat, bolding rule, or claim alignmentwrite-description: missing table description or missing provenance recordrewrite-results-text: nearby paper prose overclaims or misses the takeawaybuild-result-asset: raw CSV evidence exists but the paper-facing table needs to be generated with documented aggregation, rounding, and provenancemine-existing-results: missing comparison, slice, variance, or baseline may already exist in CSVs or reportsrerun: missing seeds, variance, baseline, metric, or protocol after existing results are checkeddiagnose-result: suspicious, negative, unstable, or contradictory numbersbaseline-audit: missing or unfair baselinenarrow-claim: evidence only supports a smaller statementmove-to-appendix: useful but not central enough for main papercut: table does not support a paper needName the next skill when appropriate.
If saving to a project and no path is given, use:
docs/results/table_results_review_YYYY-MM-DD_<short-name>.md
The report must include:
.tex, input location, label, caption, paper callout locationWhen memory exists, update the smallest useful set of entries:
memory/evidence-board.md: table evidence status, source .tex, setup, table-generation parameters, experiment parameters, and linked claimsmemory/claim-board.md: claims supported, narrowed, contradicted, or not readymemory/risk-board.md: reviewer risks from table ambiguity, missing uncertainty, weak baselines, missing provenance, or overclaimingmemory/action-board.md: table edits, reruns, caption fixes, result diagnosis, baseline audit, or claim revisionspaper/.agent/: table map, source/input pairings, paper locations, table descriptions, caption state, provenance gaps, and stale table warnings.agent/worktree-status.md: result-generation or table-generation tasks and exit conditionsUse certainty labels:
verified for values checked against raw data, logs, generated table, or paper textuser-stated for user-supplied contextinferred for reviewer-risk and narrative judgmentsunverified for numeric or statistical claims that could not be inspectedBefore finalizing:
tables/*.textesting
Bootstrap project-local ml-research-skills. Use from global installs when creating a new ML research project, enabling this collection in an existing ML research repo, or deciding whether to install the full bundle locally. Route to project-init for new projects; do not handle paper or experiment work directly.
development
Route project operations tasks — git, memory, bootstrap, remote, workspace, code review, timeline, ops — to the correct skill. Use when the task involves commits, pushes, worktrees, project memory, enabling project-local skills, SSH/server coordination, sidecar runners, or audits. Do not solve the ops task directly.
testing
Route ML/AI paper writing tasks to the correct skill — contract planning, prose drafting, section writing, consistency editing, review simulation, rebuttal, submission, or citation work. Use when the task involves writing, revising, reviewing, or submitting a paper instead of guessing between paper-writing-assistant, paper-writing-contract-planner, paper-reviewer-simulator, auto-paper-improvement-loop, or citation skills. Do not draft prose directly.
data-ai
Project-local router for ML research skill selection. Use inside an initialized ML research project, or while maintaining this skill repo, when the user describes an ML research/paper/experiment/discovery/ops/release workflow and may not know the skill; route to a domain router or high-signal leaf. Do not use for generic non-ML projects.