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