L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Documents · SKILL.md

annotate-source-files

annotate-source-files

Add PUT workflow annotations to source files using the correct language-specific comment prefix. Covers annotation syntax, skeleton generation via put_generate(), multiline annotations, .internal variables, and validation. Supports 30+ languages with automatic comment prefix detection. Use after analyzing a codebase and having an annotation plan, when addin…

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: annotate-source-files locale: caveman-ultra source_locale: en source_commit: 82c77053 fence_basis_commit: 82c77053 translator: "Julius Brussee homage — caveman" translation_date: "2026-04-19" description: > Add PUT workflow annotations to source files using the correct language-specific comment prefix. Covers annotation syntax, skeleton generation via put_generate(), multiline annotations, .internal variables, and validation. Supports 30+ languages with automatic comment prefix detection. Use after analyzing a codebase and having an annotation plan, when adding workflow documentation to new or existing source files, or when documenting data pipelines, ETL processes, or multi-step computations. 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, annotation, workflow, comment-syntax, polyglot, documentation

Annotate Source Files

Add PUT workflow annotations → putior extracts structured workflow data + generates Mermaid diagrams.

Use When

  • After analyze-codebase-workflow + annotation plan
  • Add workflow docs new/existing src
  • Enrich auto-detected w/ manual labels + connections
  • Doc data pipelines, ETL, multi-step computations

In

  • Required: Src files to annotate
  • Required: Annotation plan or workflow steps knowledge
  • Optional: Style — single-line or multiline (default: single-line)
  • Optional: Use put_generate() skeletons? (default: yes)

Do

Step 1: Determine Comment Prefix

Each lang has specific prefix. get_comment_prefix() → correct one.

library(putior)

# Common prefixes
get_comment_prefix("R")    # "#"
get_comment_prefix("py")   # "#"
get_comment_prefix("sql")  # "--"
get_comment_prefix("js")   # "//"
get_comment_prefix("ts")   # "//"
get_comment_prefix("go")   # "//"
get_comment_prefix("rs")   # "//"
get_comment_prefix("m")    # "%"
get_comment_prefix("lua")  # "--"

→ String like "#", "--", "//", or "%".

Line + block comments: putior detects annotations in both line comments (//, #, --) + C-style block comments (/* */, /** */). JS/TS both // + /* */ scanned. Python triple-quote strings (''' ''') not detected — use # for Python.

If err: Ext not recognized → lang may not be supported. Check get_supported_extensions(). Unsupported langs → use # conventional default.

Step 2: Generate Skeletons

put_generate() → annotation templates based on auto-detected I/O.

# Print suggestions to console
put_generate("./src/etl/")

# Single-line style (default)
put_generate("./src/etl/", style = "single")

# Multiline style for complex annotations
put_generate("./src/etl/", style = "multiline")

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

Example out for R file:

# put id:'extract_data', label:'Extract Customer Data', input:'customers.csv', output:'raw_data.internal'

Example out for SQL:

-- put id:'load_data', label:'Load Customer Table', output:'customers'

→ 1+ annotation comment lines per file, pre-filled w/ detected fn names + I/O.

If err: No suggestions → file may not have recognizable I/O patterns. Write annotations manually.

Step 3: Refine Annotations

Edit generated skeletons → accurate labels, connections, metadata.

Annotation syntax:

<prefix> put id:'unique_id', label:'Human Readable Label', input:'file1.csv, file2.rds', output:'result.parquet, summary.internal'

Fields:

  • id (required): Unique ID, for node connections
  • label (required): Human-readable desc shown diagram
  • input: Comma-separated ins
  • output: Comma-separated outs
  • .internal ext: Marks in-memory vars (not persisted between scripts)
  • node_type: Mermaid shape + class styling. Values:
    • "input" — stadium shape ([...]) data srcs + config
    • "output" — subroutine shape [[...]] generated artifacts
    • "process" — rectangle [...] processing steps (default)
    • "decision" — diamond {...} conditional logic
    • "start" / "end" — stadium shape ([...]) entry/terminal

Example w/ node_type:

# put id:'config', label:'Load Config', node_type:'input', output:'config.internal'
# put id:'transform', label:'Apply Rules', node_type:'process', input:'config.internal', output:'result.rds'
# put id:'report', label:'Generate Report', node_type:'output', input:'result.rds'

Multiline syntax (complex):

# put id:'complex_step', \
#   label:'Multi-line Label', \
#   input:'data.csv, config.yaml', \
#   output:'result.parquet'

Block comment syntax (//-prefix langs only: JS, TS, Go, Rust, C, C++, Java, etc.):

Langs w/ // line comments also support PUT in /* */ + /** */ blocks. Use * put as line prefix inside block body:

/* put id:'init', label:'Initialize Config', output:'config.internal' */

/**
 * put id:'process', \
 *   label:'Process Records', \
 *   input:'config.internal, records.json', \
 *   output:'results.json'
 */
function processRecords(config, records) {
  // ...
}

JSDoc annotations useful documenting workflow + API docs:

/**
 * Transform raw sensor data into normalized readings.
 * put id:'normalize', label:'Normalize Sensor Data', input:'raw_readings.json', output:'normalized.parquet'
 */
export function normalizeSensorData(readings: SensorReading[]): NormalizedData {
  // ...
}

Note: Block comment annotations not supported for #-prefix (R, Python, Shell) or ---prefix (SQL, Lua). Line comments only those. Block-originated no backslash continuation across lines.

Cross-file data flow (connect scripts via file-based I/O):

# Script 1: extract.R
# put id:'extract', label:'Extract Data', output:'raw_data.internal, raw_data.rds'
data <- read.csv("source.csv")
saveRDS(data, "raw_data.rds")

# Script 2: transform.R
# put id:'transform', label:'Transform Data', input:'raw_data.rds', output:'clean_data.parquet'
data <- readRDS("raw_data.rds")
arrow::write_parquet(clean, "clean_data.parquet")

→ Annotations refined w/ accurate IDs, labels, I/O reflecting actual data flow.

If err: Unsure I/O → .internal ext for in-memory intermediates + explicit file names for persisted.

Step 4: Insert Annotations

Place at top of file or immediately above relevant code block.

Placement conventions:

  1. File-level: Top after shebang or header comment
  2. Block-level: Immediately above code block it describes
  3. Multi per file: Distinct workflow phases

Example in R:

#!/usr/bin/env Rscript
# ETL Extract Script
#
# put id:'read_source', label:'Read Source Data', input:'raw_data.csv', output:'df.internal'

df <- read.csv("raw_data.csv")

# put id:'clean_data', label:'Clean and Validate', input:'df.internal', output:'clean.rds'

df_clean <- df[complete.cases(df), ]
saveRDS(df_clean, "clean.rds")

Edit tool → insert into existing files no disturb surrounding.

→ Annotations inserted at appropriate locations per file.

If err: Break syntax highlighting → verify prefix correct for lang. PUT = std comments + should not affect exec.

Step 5: Validate

Run putior validation → syntax + connectivity.

# Scan annotated files
workflow <- put("./src/", validate = TRUE)

# Check for validation issues
print(workflow)
cat(sprintf("Total nodes: %d\n", nrow(workflow)))

# Verify connections by checking input/output overlap
inputs <- unlist(strsplit(workflow$input, ",\\s*"))
outputs <- unlist(strsplit(workflow$output, ",\\s*"))
connected <- intersect(inputs, outputs)
cat(sprintf("Connected data flows: %d\n", length(connected)))

# Generate diagram to visually inspect
cat(put_diagram(workflow, theme = "github", show_source_info = TRUE))

# Merge with auto-detected for maximum coverage
merged <- put_merge("./src/", merge_strategy = "supplement")
cat(put_diagram(merged, theme = "github"))

→ All annotations parse no err. Diagram shows connected workflow. put_merge() fills gaps from auto-detection.

If err: Common issues:

  • Missing close quote: id:'name → id:'name'
  • Double quotes inside: id:"name" → id:'name'
  • Duplicate IDs across files: each id must be unique across entire scanned dir
  • Backslash continuation wrong line: \ must be last char before newline

Check

  • Every annotated file has syntactically valid PUT annotations
  • put("./src/") returns df w/ expected node count
  • No duplicate id values across scanned dir
  • put_diagram() produces connected flowchart (not all isolated)
  • Multiline annotations (if used) parse correct w/ backslash continuation
  • .internal vars appear only outputs, never cross-file ins
  • Files excluded via exclude no appear in workflow (e.g., put("./src/", exclude = "test_") skips test helpers)

Traps

  • Quote nesting: PUT uses single quotes: id:'name'. Double quotes → parsing issues when annotation in string ctx.
  • Duplicate IDs: Every id must be globally unique within scanned scope. Naming: <script>_<step> (e.g., extract_read, transform_clean).
  • .internal as cross-file in: .internal exists only during script exec. Pass data between scripts → persisted file format (.rds, .csv, .parquet) as out of one + in of next.
  • Missing connections: Disconnected nodes → check out filenames in 1 annotation exactly match in filenames in another (including exts).
  • Wrong prefix: # in SQL or // in Python → annotation treated as code not comment. Always verify get_comment_prefix().
  • Forget multiline continuation: Every continued line must end \ + next line must start w/ comment prefix.
  • Python triple-quote strings: putior no scan (''' ''', """ """). Always # for Python PUT.
  • Meta-pipeline annotations: Annotate build script that also scans for annotations (e.g., script calling put() + put_diagram()) → script's own annotations appear in generated diagram. Exclude file from scanning (see generate-workflow-diagram Traps) or no PUT in build script itself.

→

  • analyze-codebase-workflow — prereq: produces annotation plan this follows
  • generate-workflow-diagram — next: generate final from annotations
  • install-putior — putior installed before annotating
  • configure-putior-mcp — MCP tools interactive annotation assistance
Skills enregistrées