table-schema

Table Schema (two layers: index vs Appendix)

Triggers & routing

• Trigger: table schema, schema-first tables, table design, 表格 schema, 先 schema 后填充.
• Use when: you want survey tables that are verifiable and fillable before LaTeX (typically Stage C4, after evidence packs exist).

Tables are not decorations; they are compression.

A common failure mode in this pipeline: the first table that gets generated looks like an internal index. So we separate tables into two layers:

1. outline/tables_index.md (internal)

• purpose: coverage/debugging + fast evidence scan
• allowed to be more exhaustive
• should NOT be inserted into the paper

2. outline/tables_appendix.md (reader-facing)

• purpose: publishable survey tables (clean layout + high information density)
• can be inserted into the final PDF as Appendix

This skill designs both layers before filling.

Default mode: semantic (LLM-first)

Treat this as a design task, not running a script.

If a column cannot be filled from existing evidence packs without guessing, the schema is wrong.

Roles (use explicitly)

Table Designer (reader lens)

Mission: choose tables that answer reader questions, not pipeline questions.

Do:

• make each table answer one question
• keep tables small enough to fill (two good tables beat one impossible mega-table)

Avoid:

• internal/log-style tables inside the paper
• column labels that only make sense inside this repo

Evidence Steward (fillability)

Mission: refuse schemas that require invented facts.

Do:

• map every column to concrete upstream fields
• reject columns that would force long paragraph cells

Avoid:

• TODO columns
• placeholders ("TBD", "...", "(placeholder)")

Workflow (explicit inputs)

• Use GOAL.md to keep the reader question and scope stable.
• Read queries.md:draft_profile when present; it controls the table budget, not the evidence standard.
• Use outline/outline.yml to align table row units with the paper structure.
• Use outline/subsection_briefs.jsonl to ground table dimensions/axes in the approved structure.
• Use outline/evidence_drafts.jsonl to ensure every planned column is fillable without guessing.

Inputs

• outline/outline.yml
• outline/subsection_briefs.jsonl
• outline/evidence_drafts.jsonl
• Optional: GOAL.md

Output

• outline/table_schema.md

Non-negotiables (schema contract)

• Minimum definitions by draft_profile:
  • course_paper: >=1 Index table and >=1 Appendix table
  • survey / deep: >=2 Index tables and >=2 Appendix tables
• Every table definition must include:
  • the question it answers
  • the row unit (H3 / benchmark / work / failure mode)
  • columns (with cell style constraints)
  • evidence mapping (which upstream fields fill which columns)
• Cell style: short phrases; avoid paragraph cells.
• Paper voice: Appendix table captions/columns must be publishable (no pipeline jargon).

Recommended defaults (arxiv-survey family)

For course_paper, use I1 and A1 as the compact default. Add I2 or A2 only when the evidence supports a distinct reader question. For survey and deep, use the full I1/I2/A1/A2 set below.

Index tables (for table-filler -> outline/tables_index.md)

I1) Subsection map (axes + representative works)

• Row unit: H3
• Columns: subsection; axes; representative works
• Evidence sources: subsection_briefs.axes + citations from evidence_drafts

I2) Concrete anchors (benchmarks / numbers / caveats)

• Row unit: H3
• Columns: subsection; anchor facts; representative works
• Evidence sources: anchor_sheet.anchors

Appendix tables (for appendix-table-writer -> outline/tables_appendix.md)

A1) Method/architecture map (representative works)

• Row unit: work/system line
• Columns: work; core idea; loop + interface assumptions; key refs
• Evidence sources: evidence_drafts (comparisons + definitions) + anchor_sheet

A2) Evaluation protocol / benchmark map

• Row unit: benchmark or evaluation setting (fallback: protocol dimension)
• Columns: benchmark/setting; task+metric; key protocol constraints; key refs
• Evidence sources: anchor_sheet + evidence_drafts.evaluation_protocol

Positive / negative examples

Good (publishable question + fillable columns):

• Question: "Which benchmarks anchor evaluation in this area, and what task/metric/constraints do they imply?"
• Columns: Benchmark; Task+metric; Protocol constraints; Key refs
• Evidence mapping: evidence_drafts.evaluation_protocol + anchor_sheet

Bad (internal/pipeline voice):

• Question: "What is evidence readiness + verification needs?"
• Columns: evidence levels, missing fields, TODO checklist

If you want internal diagnostics, put them in an audit report, not in reader-facing tables.

Script (optional bootstrap)

Quick Start

• uv run python .codex/skills/table-schema/scripts/run.py --help
• uv run python .codex/skills/table-schema/scripts/run.py --workspace <workspace>

All Options

• --workspace <workspace> (required)
• --unit-id <id> (optional; used only for runner bookkeeping)
• --inputs <outline;briefs;packs;goal> (optional; override inputs)
• --outputs <relpath> (optional; defaults to outline/table_schema.md)
• --checkpoint <C#> (optional; ignored by the bootstrapper)

Examples

• Bootstrap a two-layer schema (index + Appendix):

  uv run python .codex/skills/table-schema/scripts/run.py --workspace <workspace>

• Write to a custom schema path (rare):

  uv run python .codex/skills/table-schema/scripts/run.py --workspace <workspace> --outputs outline/table_schema.md

Notes:

• Use the script as a starting point, then refine the schema as a paper artifact.
• If a column cannot be filled from evidence packs without guessing, the schema is wrong.