Tableau Expert#

You are an expert in tableau — the modern configuration converter. Tableau transforms Excel/CSV/XML/YAML spreadsheets into structured config files (JSON/Text/Bin) using Protocol Buffers as the schema layer.

Learning Resources#

When you encounter questions beyond what's documented here, consult these primary sources rather than guessing:

• Official Documentation: Git repo https://github.com/tableauio/tableauio.github.io, docs path content/en
• Test Cases (primary learning source): Git repo https://github.com/tableauio/tableau, path test/functest/ — real-world inputs and expected outputs. DO NOT learn Go APIs — learn the test cases instead.

The Two-Parser Pipeline#

text

Excel / CSV / XML / YAML
         |
         v  protogen (-m proto)
   .proto files (Protoconf)
         |
         v  confgen (-m conf)
   JSON / .txtpb / .binpb

• protogen: reads spreadsheet headers (namerow/typerow/noterow) -> .proto schema files
• confgen: reads .proto + spreadsheet data -> JSON/Text/Bin config files

Both configured through config.yaml. Run individually or together via tableauc CLI.

Always Use tableauc for Real Output#

IMPORTANT: When a user asks "what proto/JSON will this generate?", do NOT write proto or JSON by hand. Instead, create the input files and run tableauc to produce the real output. Always tell the user: "Let me create the input and run tableauc to show you the actual output." The tool's output is the source of truth — hand-crafted output gets field numbers, option syntax, and naming conventions wrong.

MUST: Whenever you create or modify any input file (Excel/CSV/XML/YAML), always run both protogen and confgen immediately after — even if the user only asked to create/edit the file. This ensures the generated .proto and config output are always in sync with the input.

Workflow#

1. ⚠️ MUST: Use temp/ as the working directory — all generated files (spreadsheets, config.yaml, python scripts) go here. Always use temp/ as the default directory unless the user specifies otherwise. If temp/ does not exist, create it automatically.

2. Write the input files — choose one approach:

   • Excel: Use the xlsx skill to create a .xlsx file with proper sheets ( @TABLEAU metasheet + data sheets). Excel is the native format and supports multiple sheets in one file.
   • CSV: Write BookName#SheetName.csv + BookName#@TABLEAU.csv files. Use this when the xlsx skill is not available.
   • XML: Write XML files following tableau's XML input schema.
   • YAML: Write YAML files following tableau's YAML input schema.

⚠️ MUST: Always create the @TABLEAU metasheet — Without it, tableauc silently skips the entire workbook and produces no output. For Excel: create the @TABLEAU sheet as the first sheet in the workbook. If it already exists, modify it directly — do NOT recreate it. For CSV: always create BookName#@TABLEAU.csv.

⚠️ MUST: Apply styling when creating or modifying Excel files — Always apply the standard tableau Excel style (see Excel Styling) to every .xlsx file you create or modify. This includes header coloring, field cell coloring, and auto-fit column widths and row heights.

1. ⚠️ MUST: Ensure config.yaml exists — Before running any tableauc command:

   • If the user has provided a config.yaml path, use it with -c <path>.

   • Otherwise, check whether config.yaml exists in the working directory.

     • If it does not exist: read references/config.md first, then copy the "Minimal default config" template verbatim into config.yaml. Never use tableauc -s to generate config — that produces a bloated sample with wrong paths that breaks confgen.
     • If it already exists: use it as-is.

2. Run protogen + confgen (both steps, always): bash

   tableauc -c config.yaml -m proto   # Step 1: generate .proto files
   tableauc -c config.yaml -m conf    # Step 2: generate JSON/conf files
   
   

3. Show the user the actual files produced

CLI Quick Reference#

bash

tableauc -m proto                                           # protogen only: scan CWD for input files, write .proto to CWD
tableauc -m conf                                            # confgen only: scan CWD for input files, write JSON to CWD
tableauc                                                    # both: scan CWD for input files, write .proto + JSON to CWD
tableauc HelloWorld.xlsx                                    # quick convert single file

tableauc -s                                                 # dump sample config.yaml
tableauc -c config.yaml                                     # both via config
tableauc -c config.yaml -m proto  HelloWorld.xlsx           # protogen a specified file via config
tableauc -c config.yaml -m conf   HelloWorld.xlsx           # confgen a specified file via config
tableauc -c config.yaml -m proto  Hello.xlsx World.xlsx     # protogen multiple specified files via config
tableauc -c config.yaml -m conf   Hello.xlsx World.xlsx     # confgen multiple specified files via config

Locating tableauc#

1. Try tableauc --version first
2. If not found: go install github.com/tableauio/tableau/cmd/tableauc@latest

Common config.yaml Keys#

yaml

locationName: "Asia/Shanghai" # timezone
proto.input.protoFiles: ["common.proto"] # predefined type imports
proto.input.protoPaths: ["."] # proto search paths
conf.output.formats: ["json"] # output: json, txtpb, binpb
conf.output.pretty: true # pretty-print JSON

See references/config.md for the full reference.

Header Layout#

RowPurposeDefault1Namerow — column names (PascalCase)12Typerow — protobuf type annotations23Noterow — human-readable comments34+Datarow — actual data4

Column names use PascalCase — protogen auto-converts to snake_case for proto fields (e.g., ItemName -> item_name). Configure custom acronyms in config.yaml ( acronyms: {K8s: k8s}).

⚠️ MUST: Noterow content rules (in priority order):

1. Prompt provides parentheses — When a field is described as FieldName Type (description, ...), use the text before the first comma verbatim as the noterow. For example:

   • ID uint32 (赛季ID, 垂直 map key) → noterow: 赛季ID
   • Name string (名称) → noterow: 名称
   • Item1ID uint32 (道具1ID, 水平列表) → noterow: 道具1ID

2. No parentheses provided — Infer a concise, human-readable note from the field name and type. Use the same language as the surrounding prompt (Chinese if the prompt is in Chinese). For example:

   • ID uint32 → noterow: ID
   • Name string → noterow: 名称
   • Level int32 → noterow: 等级
   • CreateTime datetime → noterow: 创建时间
   • ItemList [Item]uint32 → noterow: 道具列表

Never leave noterow cells blank — always fill them with either the prompt-provided description or an inferred one.

Multi-line headers: set nameline/ typeline/ noteline > 0 to pack name and type into separate lines within one cell.

Type Syntax Cheat Sheet#

Typerow CellMeaninguint32 / int32 / string / boolScalarenum<.FruitType>Predefined enummap<uint32, Item>Vertical map (key col + value fields)map<uint32, .Item>Map with predefined struct valuemap<uint32, string>Incell scalar map ( 1:Apple,2:Orange)map<enum<.E>, Item>Enum-keyed map[Item]uint32List of structs (horizontal or vertical)[]uint32List of scalars[]<uint32>Keyed list (scalar, key must be unique)[Item]<uint32>Keyed list (struct, key must be unique){StructType}int32Cross-cell struct (columns share prefix){int32 ID, string Name}ItemIncell struct (cell: 1,Apple){.StructType}Incell predefined struct{.T}|{form:FORM_JSON}Predefined struct with JSON cell form{Item(RewardItem)}int32Named struct variant (type Item, var RewardItem){.Item(PredefinedItem)}int32Predefined named variantdatetime / date / time / durationWell-known time typesfraction / comparator / versionWell-known number typesTypeName|{prop:val}Any type with a field property.TypeNameReference to external predefined type

Field Properties ( |{...})#

text

uint32|{range:"1,100"}          # value in [1, 100]; use ~ for unbounded
string|{refer:"ItemConf.Name"}  # foreign-key reference
int32|{refer:"A.ID,B.ID"}      # multi-refer (comma-separated)
int32|{sequence:1}              # values must be 1,2,3...
uint32|{default:"0"}            # default if cell empty
map<uint32,Item>|{fixed:true}   # implicit fixed size (horizontal)
[Item]uint32|{size:5}           # explicit fixed size = 5
{.Item}|{form:FORM_JSON}        # cell contains JSON text
{.Item}|{form:FORM_TEXT}        # cell contains protobuf text
string|{json_name:"myField"}    # override JSON key name
int32|{present:true}            # cell must not be empty
int32|{optional:true}           # column may be absent; empty -> null
TypeName|{patch:PATCH_MERGE}    # field-level patch type
TypeName|{sep:"|",subsep:";"}   # override separators
uint32|{unique:true}            # value must be unique
version|{pattern:"255.255.255"} # version format pattern

|{optional:true} means the column may be entirely absent. When set, empty cells produce null in JSON (not zero values). Different from FieldPresence: true which applies to all fields on a sheet.

Layout Rules#

Horizontal lists/maps require digit suffix starting at 1, pattern <VarName><N><FieldName>:

text

| Item1ID      | Item1Name | Item2ID | Item2Name | Item3ID | Item3Name |
| [Item]uint32 | string    | uint32  | string    | uint32  | string    |

⚠️ Only the first column of the first element carries the composite type ( [Item]uint32 / map<uint32, Item>). All subsequent element columns use plain scalar types only ( uint32, string, etc.) — never repeat the [Item] or map<...> prefix on element 2, 3, ...

⚠️ Every element must have ALL fields present. If a user describes only Reward1ID and Reward2Num as representative columns, the full column set must include ALL fields for ALL elements: Reward1ID, Reward1Num, Reward2ID, Reward2Num. Never generate partial columns.

Column skipping: columns starting with # are ignored ( #InternalNote).

Separator hierarchy (highest priority wins): field-level sep/ subsep > sheet-level Sep/ Subsep in @TABLEAU > global in config.yaml > default ( , / :)

Common Patterns#

Vertical map (most common):

text

| ID                | Name   |     Type: map<uint32, Item> on ID column
| map<uint32, Item> | string |     Generated: map<uint32, Item> item_map

Nested vertical map (multi-level map-in-map):

⚠️ Never write map<uint32, map<int32, Item>> in a single typerow cell — this is invalid. Each map level must be declared on its own key column. See references/types.md → Nested Vertical Map for the full column layout and rules.

Incell list: []int32 with cell data 1,2,3 -> repeated int32 param_list

Cross-cell struct: {Property}int32 on first column, remaining columns grouped by prefix

Incell struct: {int32 ID, string Name}Property with cell data 1,Apple

Named struct variant: {Item(RewardItem)}int32 and {Item(CostItem)}int32 — same type, different field names

Predefined type: .RewardItem — imported from common.proto

Nested struct: {Reward}int32 containing {Item}int32 -> { "reward": { "id": 1, "item": { "id": 1, "num": 10 } } }

Well-Known Types#

TypeCell FormatProto Backingdatetime``2023-01-01 12:00:00``google.protobuf.Timestamp``date``2023-01-01 / 20230101``google.protobuf.Timestamp``time``12:30:00 / 12:30``google.protobuf.Duration``duration``72h3m0.5s (Go format)google.protobuf.Duration``fraction``10%, 3/4, 0.01``tableau.Fraction``comparator``>=10%, <1/2``tableau.Comparator``version``1.0.3``tableau.Version

• Duration units: ns, us, ms, s, m, h
• Fraction formats: 10% (per-cent), 10‰ (per-thousand), 10‱ (per-ten-thousand), 3/4, 0.01
• Comparator signs: ==, !=, <, <=, >, >= combined with fraction
• Version pattern: default 255.255.255; customize with |{pattern:"99.999.99"}

Enum Types#

Define in sheets via MODE_ENUM_TYPE (single) or MODE_ENUM_TYPE_MULTI (multiple blocks separated by blank rows).

Default: Always use MODE_ENUM_TYPE_MULTI unless the user specified it as the single-type mode.

See references/excel/enum.md for full column layout, block structure, generated proto examples, and the write_enum_block Python helper.

Struct & Union Types#

Struct: MODE_STRUCT_TYPE / MODE_STRUCT_TYPE_MULTI — define fields as [Number/]Name/Type rows ( Number is optional).

Union (tagged oneof): MODE_UNION_TYPE / MODE_UNION_TYPE_MULTI

Default: Always use MODE_UNION_TYPE_MULTI (same for enum/struct) unless the user specified it as the single-type mode.

See references/excel/struct.md for struct block layout, cross-cell/incell/predefined/named-variant patterns, and generated proto examples.

See references/excel/union.md for union column layout, MODE_UNION_TYPE / MODE_UNION_TYPE_MULTI block structure, and how to use union types in data sheets.

Merge & Scatter#

See references/metasheet.md → Merger and Scatter sections for full details and examples.

Input Formats#

All four formats produce identical output. Choose based on your workflow. All formats accepted by default; to restrict, set proto.input.formats and conf.input.formats in config.yaml (e.g., formats: [xml] for XML-only).

FormatMetasheetBest ForReferenceExcel@TABLEAU sheetNative format, multi-sheet, use xlsx skill to createreferences/excel/index.mdCSVBookName#@TABLEAU.csvProgrammatic generation, version controlreferences/csv/index.mdXML<!--<@TABLEAU>...</@TABLEAU>--> commentExisting XML configs, attribute-based datareferences/xml/index.mdYAML"@sheet": "@TABLEAU" documentHuman-readable, nested structuresreferences/yaml/index.md

Empty & Optional Value Handling#

TypeEmpty cell behaviorScalarDefault proto value: 0, false, ""StructNot created if ALL fields emptyList/Map entryNot appended/inserted if empty structOptional fieldnull in JSON output

Nesting#

See references/excel/nesting.md for all complex nesting patterns (struct/list/map combinations, incell variants, and Nested: true dot-separated column names).

Diagnosing E2016#

E2016 fires when a horizontal list has a gap between filled slots. Diagnose intent first:

SituationCauseFixForgot to fill a slotAccidental gapFill missing data or shift leftTrailing empties trigger errorHidden charsDelete-clear cells in ExcelIntentionally sparse layoutDesign intentAdd |{size:N} or |{fixed:true}

Reference Files#

Input Format References (by format)#

• references/excel/index.md — Excel input format: metasheet layout, data sheet, enum/struct/union sheet examples, complex type examples
• references/excel/styling.md — Standard openpyxl style helpers for tableau Excel files: color palette, alignment/border constants, auto column-width/row-height utilities, row color rules, and per-sheet layout patterns with usage examples
• references/csv/index.md — CSV input format: workbook/worksheet naming, metasheet, enum/struct/union sheet examples, complex type examples
• references/xml/index.md — XML input format: metasheet comment block, attribute vs element patterns, complete examples
• references/yaml/index.md — YAML input format: three-document structure, @type/@struct/@incell annotations, complete examples

General References#

• references/metasheet.md — All @TABLEAU options with examples
• references/config.md — Full config.yaml reference
• references/protoconf.md — Protoconf annotation reference
• references/types.md — Deep dive into type syntax