Paper Result Asset Builder

Turn CSV experiment outputs into paper-facing evidence assets: tables, figures, captions/callouts, and provenance records. This skill is the bridge from raw result files to paper artifacts.

Use this skill for:

• inventorying CSV result files and their columns, metrics, methods, datasets, seeds, and run identifiers
• deciding which CSV slices can support a paper claim
• generating or updating tables/*.tex, figures/*.pdf, figures/*.png, and figures/*.tex
• recording filtering, aggregation, rounding, bolding, plotting, and provenance rules
• separating paper-facing visualization from experiment-time debugging plots
• preparing assets for table-results-review, figure-results-review, and experiment-story-writer

Do not use this skill to decide whether a paper claim is worth making. Use paper-evidence-board or paper-evidence-gap-miner for claim/evidence triage. Do not use it to write the results narrative; use experiment-story-writer after assets exist. Do not use it for experiment-time debugging dashboards.

Skill Directory Layout

<installed-skill-dir>/
├── SKILL.md
├── scripts/
│   └── inventory_csv_results.py
├── references/
│   ├── csv-result-contract.md
│   └── paper-asset-rules.md
└── templates/
    ├── result-inventory.md
    └── result-asset-provenance.md

Progressive Loading

• Always read references/csv-result-contract.md and references/paper-asset-rules.md.
• Use scripts/inventory_csv_results.py to inspect CSV files before reading large result files into context.
• Use templates/result-inventory.md when creating paper/.agent/result-inventory.md.
• Use templates/result-asset-provenance.md when creating paper/.agent/result-asset-provenance.md.
• Read local paper/.agent/writing-contract.md, paper/.agent/paper-evidence-board.md, paper/.agent/writing-memory/, paper/.agent/evidence-completion-plan.md, paper/.agent/visual-style.md, figures/*.tex, tables/*.tex, and current result sections when present.

Core Principles

• Paper assets exist to support claims, not to dump all available results.
• CSV files are source evidence; paper tables and figures are curated views over those sources.
• Experiment-time visualizations and paper-facing visualizations are different artifacts.
• Paper-facing assets may be visible to coauthors, reviewers, arXiv, or publishers; CSVs, plotting scripts, notebooks, provenance ledgers, and internal diagnostic plots are private unless explicitly cleaned for that audience.
• Every table or figure needs source CSV paths, filtering rules, aggregation rules, metric direction, rounding, styling, and claim mapping.
• Prefer reusing existing CSV results before asking for new compute.
• Never silently hand-enter numbers without provenance.
• If the asset requires a missing result, route to paper-evidence-gap-miner before inventing placeholders.
• After building assets, route to table-results-review or figure-results-review.

Step 1 - Locate CSV Result Sources

Search likely locations:

code/docs/results/**/*.csv
code/docs/runs/**/*.csv
code/docs/reports/**/*.csv
code/outputs/**/*.csv
code/results/**/*.csv
outputs/**/*.csv
results/**/*.csv

If the project uses different result paths, follow the user's paths.

Run the inventory script when useful:

python3 <installed-skill-dir>/scripts/inventory_csv_results.py <project-dir>

Save the curated inventory to:

paper/.agent/result-inventory.md

If there is no paper/ directory and the current directory is the paper repo, save to:

.agent/result-inventory.md

Step 2 - Define the Paper Asset Job

For each requested table or figure, write:

- Asset ID:
- Asset type: table / figure
- Paper location:
- Claim supported:
- Reviewer question answered:
- Source CSV files:
- Required rows/slices:
- Metrics:
- Aggregation:
- Uncertainty:
- Styling:
- Output paths:

If this cannot be written, route to paper-evidence-board or paper-evidence-gap-miner.

Step 3 - Build the Table or Figure View

Use structured CSV parsing, not ad hoc copy/paste.

For tables:

• choose row and column groups around the reader's comparison path
• aggregate seeds/repeats before rounding
• define bolding/underlining and missing-value rules
• include metric direction arrows when appropriate
• output standalone tables/<name>.tex
• keep the source CSVs and generation scripts outside author-visible/public paper source unless the project explicitly chooses to release them

For figures:

• choose plot type based on the claim: bar, line, scatter, heatmap, Pareto frontier, calibration curve, slice plot, qualitative grid, or appendix diagnostic
• apply paper/.agent/visual-style.md when present
• export stable paper assets such as figures/<name>.pdf and optionally figures/<name>.png
• output a LaTeX wrapper figures/<name>.tex with caption and label scaffolding
• keep private plotting code, notebooks, and debug plots out of author-visible/public source by default

Step 4 - Record Provenance

Update:

paper/.agent/result-asset-provenance.md

For every asset, record:

• source CSV path and file hash when practical
• run IDs, configs, seeds, datasets, splits, methods, and metrics
• filtering and aggregation code or exact rules
• rounding and bolding rules
• plotting parameters and visual style decisions
• manual edits, if any
• claim IDs and paper locations
• uncertainty or missing provenance

Step 5 - Handoff to Review and Writing

After creating assets:

• use table-results-review for tables/*.tex
• use figure-results-review for figures/*.pdf, figures/*.png, and figures/*.tex
• use experiment-story-writer for result prose
• update paper-evidence-board with asset-to-claim mappings
• update paper-writing-memory-manager when new or changed assets affect captions, result prose, abstract, introduction, limitations, or conclusion
• update memory/provenance-board.md with CSV/report-to-asset traceability, aggregation rules, scripts, and paper locations when project memory exists
• update memory/source-visibility-board.md or route to submit-paper when generated assets are intended for an author-visible, anonymous, arXiv, camera-ready, or publisher-visible source surface
• update memory/handoff-board.md with ready handoffs to figure-results-review, table-results-review, experiment-story-writer, or paper-evidence-board
• update memory/phase-dashboard.md when the project moves from evidence production to paper asset building or drafting

Final Sanity Check

Before finalizing:

• every number or plotted point traces back to a CSV source
• filtering and aggregation rules are explicit
• paper-facing visual style is separate from experiment-time visualization
• output files are paper-ready assets, not raw debug plots
• table/figure job maps to a claim or reviewer question
• missing results are routed to paper-evidence-gap-miner
• provenance is saved or returned
• private source files such as CSVs, notebooks, plotting scripts, and provenance ledgers are not placed in visible paper source unless intentionally cleaned