---

name: analyze-codebase-workflow locale: wenyan-ultra source_locale: en source_commit: 82c77053 fence_basis_commit: 82c77053 translator: "Julius Brussee homage — caveman" translation_date: "2026-04-19" description: > Analyze an arbitrary codebase to auto-detect workflows, data pipelines, and file dependencies using putior's put_auto() engine. Produces an annotation plan that maps detected I/O patterns to source files across 30+ supported languages with 902 auto-detection patterns. Use when onboarding onto an unfamiliar codebase to understand data flow, starting putior integration in a project without existing annotations, auditing a project's data pipeline before documentation, or preparing an annotation plan before running annotate-source-files. license: MIT allowed-tools: Read Write Edit Bash Grep Glob metadata: author: Philipp Thoss version: "1.0" domain: workflow-visualization complexity: intermediate language: multi tags: putior, workflow, analysis, auto-detect, polyglot, data-pipeline

析庫流

掃庫自察數流、檔 I/O、依，出註計可手精。

用

• 入新庫須知數流→用
• 項無 PUT 註而起 putior→用
• 文前審項數流→用
• annotate-source-files 前備註計→用

入

• 必：庫或源處之路
• 可：注定子處（默全庫）
• 可：含/排之言（默諸察）
• 可：察範：唯入、唯出、或兩（默兩+依）

行

一：掃庫構

識源檔與其言以知 putior 可析者。

library(putior)

# List all supported languages and their extensions
list_supported_languages()
list_supported_languages(detection_only = TRUE)  # Only languages with auto-detection

# Get supported extensions
exts <- get_supported_extensions()

以列檔知庫成：

# Count files by extension in the target directory
find /path/to/repo -type f | sed 's/.*\.//' | sort | uniq -c | sort -rn | head -20

得：庫中諸延附數。映於 get_supported_extensions() 知覆。

敗：庫無檔合支延→putior 不能自察。或言支但檔用非標延。

二：察言覆

各察言驗自察紋有否。

# Check which languages have auto-detection patterns (18 languages, 902 patterns)
detection_langs <- list_supported_languages(detection_only = TRUE)
cat("Languages with auto-detection:\n")
print(detection_langs)

# Get pattern counts for specific languages found in the repo
for (lang in c("r", "python", "javascript", "sql", "dockerfile", "makefile")) {
  patterns <- get_detection_patterns(lang)
  cat(sprintf("%s: %d input, %d output, %d dependency patterns\n",
    lang,
    length(patterns$input),
    length(patterns$output),
    length(patterns$dependency)
  ))
}

得：各言紋數印。R 124、Python 159、JavaScript 71 等。

敗：言返無紋→支手註而非自察。計手註此檔。

三：行自察

於標處行 put_auto() 以發流元。

# Full auto-detection
workflow <- put_auto("./src/",
  detect_inputs = TRUE,
  detect_outputs = TRUE,
  detect_dependencies = TRUE
)

# Exclude build scripts and test helpers from scanning
workflow <- put_auto("./src/",
  detect_inputs = TRUE,
  detect_outputs = TRUE,
  detect_dependencies = TRUE,
  exclude = c("build-", "test_helper")
)

# View detected workflow nodes
print(workflow)

# Check node count
cat(sprintf("Detected %d workflow nodes\n", nrow(workflow)))

大庫漸析子處：

# Analyze specific subdirectories
etl_workflow <- put_auto("./src/etl/")
api_workflow <- put_auto("./src/api/")

得：數框含 id、label、input、output、source_file 等欄。各行為一察流步。

敗：果空→源或無可識 I/O 紋。試開除錯：workflow <- put_auto("./src/", log_level = "DEBUG") 察掃檔與配紋。

四：生初圖

繪自察流以評覆與識缺。

# Generate diagram from auto-detected workflow
cat(put_diagram(workflow, theme = "github"))

# With source file info for traceability
cat(put_diagram(workflow, show_source_info = TRUE))

# Save to file for review
writeLines(put_diagram(workflow, theme = "github"), "workflow-auto.md")

得：Mermaid 流圖示察點以數流邊接。點標當有意函/檔名。

敗：圖示斷點→自察找 I/O 紋而不能推接。常事——接由出檔名配入檔名而生。註計（次步）解缺。

五：出註計

生構文示所發及待手註者。

# Generate annotation suggestions
put_generate("./src/", style = "single")

# For multiline style (more readable for complex workflows)
put_generate("./src/", style = "multiline")

# Copy suggestions to clipboard for easy pasting
put_generate("./src/", output = "clipboard")

文以覆評：

## Annotation Plan

### Auto-Detected (no manual work needed)
- `src/etl/extract.R` — 3 inputs, 2 outputs detected
- `src/etl/transform.py` — 1 input, 1 output detected

### Needs Manual Annotation
- `src/api/handler.js` — Language supported but no I/O patterns matched
- `src/config/setup.sh` — Only 12 shell patterns; complex logic missed

### Not Supported
- `src/legacy/process.f90` — Fortran not in detection languages

### Recommended Connections
- extract.R output `data.csv` → transform.py input `data.csv` (auto-linked)
- transform.py output `clean.parquet` → load.R input (needs annotation)

得：清計分自察檔與待手註者，附各檔具體薦。

敗：put_generate() 無出→確路正且含支言之源檔。

驗

• put_auto() 於標處行而無誤
• 察流至少一點（除非庫無可識 I/O）
• put_diagram() 自察流出有效 Mermaid
• put_generate() 為察紋之檔出註薦
• 註計文已建附覆評

忌

• 掃過廣：庫根行 put_auto(".") 或含 node_modules/、.git/、venv/ 等。標定源處
• 盼全覆：自察找檔 I/O 與庫呼非商邏。常 40-60% 覆；餘待手註
• 忽依：detect_dependencies = TRUE 旗捕 source()、import、require() 連腳。停則失跨檔接
• 言不配：非標延（如 .R 對 .r、.jsx 對 .js）或不察。用 get_comment_prefix() 察延識否。Dockerfile、Makefile 等無延檔以全名配支
• 大庫：百源檔以上→按模/處析以保圖可讀

參

• install-putior — 前置：先裝 putior
• annotate-source-files — 次步：按計加手註
• generate-workflow-diagram — 註畢生末圖
• configure-putior-mcp — 用 MCP 工為互析