detect-writing

name	detect-writing
description	Writing system extraction with NNg tone dimensions, UI copy classification, and i18n maturity. Use when auditing content systems.
allowed-tools	Read, Glob, Grep, Write($JAAN_OUTPUTS_DIR/**), Edit(jaan-to/config/settings.yaml), Edit($JAAN_CONTEXT_DIR/**)
argument-hint	[repo] [--full]
context	fork
license	PROPRIETARY

detect-writing

Detect the current writing system using multi-signal extraction and output a canonical writing-system spec.

Context Files

• $JAAN_LEARN_DIR/jaan-to-detect-writing.learn.md - Past lessons (loaded in Pre-Execution)
• $JAAN_CONTEXT_DIR/tech.md - Tech stack (for framework-aware i18n scanning)
• $JAAN_TEMPLATES_DIR/jaan-to-detect-writing.template.md - Output template
• ${CLAUDE_PLUGIN_ROOT}/docs/extending/language-protocol.md - Language resolution protocol

Output path: $JAAN_OUTPUTS_DIR/detect/writing/ — flat files, overwritten each run (no IDs).

Input

Arguments: $ARGUMENTS — parsed in Step 0.0. Repository path and mode determined there.

---

Pre-Execution Protocol

MANDATORY — Read and execute ALL steps in: ${CLAUDE_PLUGIN_ROOT}/docs/extending/pre-execution-protocol.md Skill name: detect-writing Execute: Step 0 (Init Guard) → A (Load Lessons) → B (Resolve Template) → C (Offer Template Seeding)

Language Settings

Read and apply language protocol: ${CLAUDE_PLUGIN_ROOT}/docs/extending/language-protocol.md Override field for this skill: language_detect-writing

---

Standards Reference

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/detect-shared-reference.md for Evidence Format (SARIF), Evidence ID Generation, Confidence Levels, Frontmatter Schema, Platform Detection, Document Structure, and Codebase Content Safety.

This skill's namespace: E-WRT-* (e.g., E-WRT-001, E-WRT-WEB-001) Tool name in frontmatter: detect-writing

---

PHASE 1: Detection (Read-Only)

Step 0.0: Parse Arguments

Arguments: $ARGUMENTS

Argument	Effect
(none)	Light mode (default): String inventory + i18n maturity, single summary file
[repo]	Scan specified repo (applies to both modes)
--full	Full mode: All detection steps, 6 output files (current behavior)

Mode determination:

• If $ARGUMENTS contains --full as a standalone token → set run_depth = "full"
• Otherwise → set run_depth = "light"

Strip --full token from arguments. Set repo_path to remaining arguments (or current working directory if empty).

Thinking Mode

If run_depth == "full": ultrathink If run_depth == "light": megathink

Use extended reasoning for:

• NNg tone dimension scoring across string corpus
• UI copy classification and quality assessment
• i18n maturity level determination
• Terminology consistency analysis

Step 0: Detect Platforms

Purpose: Auto-detect platform structure and determine analysis scope (full vs partial).

Use Glob and Bash to identify platform folders:

Platform Patterns

(Same as detect-dev - see detect-dev Step 0 for full patterns table)

Detection Process

1. Check for monorepo markers: pnpm-workspace.yaml, lerna.json, nx.json, turbo.json
2. List top-level directories: ls -d */ | grep -Ev "node_modules|\.git|dist|build|\.next"
3. Match against platform patterns: Apply disambiguation rules
4. Handle detection results:
   • No platforms → Single-platform: platforms = [{ name: 'all', path: '.' }]
   • Platforms detected → Multi-platform: Ask user to select all or specific platforms

Writing System Applicability

For each platform, determine analysis scope:

Platform Type	Analysis Scope	Rationale
web, mobile, androidtv, ios, android, desktop	Full	UI copy, error messages, tone, localization
backend, api, services	Partial	Error messages only (API errors, logs, validation messages)
cli, cmd	Partial	Error messages + CLI help text only

Partial analysis includes:

• Error message detection and scoring (Step 4)
• Glossary extraction from error messages (Step 5 - partial)
• Localization detection for error messages (Step 6 - partial)
• Skips: UI copy classification (Step 2), full tone analysis (Step 3 reduced to error messages only)

UI Presence Check

# Check for UI component files
ui_files=$(find {platform.path} -type f \( -name "*.jsx" -o -name "*.tsx" -o -name "*.vue" -o -name "*.svelte" \) 2>/dev/null | head -n 1)

if [ -z "$ui_files" ]; then
  # No UI files - partial analysis mode
  analysis_mode = "partial"  # Error messages only
else
  analysis_mode = "full"     # Full writing system analysis
fi

Analysis Loop

For each platform in platforms:

1. Set current_platform = platform.name
2. Set base_path = platform.path
3. Determine analysis mode based on platform type and UI presence
4. Run detection steps per run_depth and analysis_mode:
   • If run_depth == "full" AND analysis_mode == "full": Run Steps 1-7
   • If run_depth == "full" AND analysis_mode == "partial": Run Steps 1, 3 (reduced), 4, 5, 6 (reduced). Skip Step 2, 7 unless content linting detected.
   • If run_depth == "light" AND analysis_mode == "full": Run Steps 1, 5 only (skip Steps 2, 3, 4, 6, 7)
   • If run_depth == "light" AND analysis_mode == "partial": Run Steps 1, 4, 5 only (skip Steps 2, 3, 6, 7)
5. Use platform-specific output paths in Step 9

Partial Analysis Output Notes:

• writing-system.md: Tone dimensions based on error messages only, with note about scope limitation
• ui-copy.md: Minimal "Not Applicable" file with informational finding
• samples.md: Minimal "Not Applicable" file or error message samples only

Note: If single-platform mode (platform.name == 'all'), output paths have NO suffix. If multi-platform mode, output paths include -{platform} suffix.

Step 1: String Inventory

i18n / Locale Files

Use framework-specific glob patterns:

Framework	Glob Patterns
React i18next	**/locales/**/*.json, **/i18n/**/*.json, **/public/locales/**/*.json
Vue i18n	**/locales/*.json, **/i18n/**/*.json, **/lang/**/*.{json,yml}
Angular	**/src/locale/messages.*.xlf
Next.js	**/public/locales/**/*.json, **/messages/*.json
Flutter/Dart	**/lib/l10n/*.arb, **/l10n/app_*.arb
Android	**/res/values/strings.xml, **/res/values-*/strings.xml
iOS/macOS	**/*.lproj/Localizable.strings
Rails	**/config/locales/**/*.yml
Django	**/locale/*/LC_MESSAGES/django.po
Java	**/resources/messages*.properties
.NET	**/Resources/*.resx
PHP/Laravel	**/resources/lang/**/*.php, **/lang/**/*.php
GNU gettext	**/po/*.po, **/po/*.pot

Component Inline Text

• Grep for text in component props: label, title, message, description, placeholder, helperText, errorMessage
• Grep for JSX/TSX inline text between tags

If run_depth == "light" AND analysis_mode == "full": Skip Steps 2-4, 6-7. Proceed directly to Step 5 (i18n Maturity Assessment).

If run_depth == "light" AND analysis_mode == "partial": Skip Steps 2-3. Proceed directly to Step 4 (Error Message Quality Scoring), then Step 5, then skip Steps 6-7.

Step 2: UI Copy Classification

Classify discovered strings into 8 categories (Buttons/CTAs, Error messages, Empty states, Confirmation dialogs, Notifications/toasts, Onboarding, Form labels/helper, Loading states) using component-name glob patterns and variant/severity props.

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/detect-writing-reference.md — "UI Copy Classification" for category detection patterns and props to extract.

Step 3: NNg Tone Dimension Scoring

Score strings across 4 primary dimensions (Formality, Humor, Respectfulness, Enthusiasm) and 5 extended dimensions (Technical complexity, Verbosity, Directness, Empathy, Confidence), each on a 1-5 scale. Calculate consistency scores via standard deviation per dimension; flag outliers deviating >1.5 standard deviations.

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/detect-writing-reference.md — "NNg Tone Dimension Scoring" for dimension scales, detection signals, and consistency calculation.

Step 4: Error Message Quality Scoring

Apply 5-dimension weighted rubric (Clarity 25%, Specificity 20%, Actionability 25%, Tone 15%, Accessibility 15%) to each error message found. Flag messages matching automated heuristic thresholds (complexity, length, passive voice, blame language, visible error codes, missing action verbs).

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/detect-writing-reference.md — "Error Message Quality Scoring" for rubric details and heuristic flag criteria.

Step 5: i18n Maturity Assessment

Use the glob patterns from Step 1 to identify which i18n framework is in use. Assess ICU MessageFormat usage, RTL support, hardcoded string prevalence, string interpolation quality, and centralization. Rate maturity on a 0-5 scale (None through Excellence).

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/detect-writing-reference.md — "i18n Maturity Assessment" for ICU regex patterns, RTL detection methods, hardcoded string grep patterns, interpolation quality levels, centralization scoring rules, and the 0-5 maturity scale.

If run_depth == "light": Skip Steps 6-7. Proceed directly to Step 8 (Present Detection Summary).

Step 6: Terminology Extraction

Build a glossary using ISO-704-inspired methodology. Discover terms via TF-IDF and C-value analysis, detect semantic/syntactic/frequency-based inconsistencies, and output entries with preferred/admitted/deprecated statuses.

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/detect-writing-reference.md — "Terminology Extraction" for term discovery methods, inconsistency detection rules, and glossary entry YAML format.

Step 7: Content Governance Detection

Check for content governance signals: CODEOWNERS locale ownership, content linting tools, i18n keywords in PR templates, and CI translation checks.

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/detect-writing-reference.md — "Content Governance Detection" for specific tools and patterns to check.

---

HARD STOP — Detection Summary & User Approval

Step 8: Present Detection Summary

If run_depth == "light":

WRITING SYSTEM DETECTION COMPLETE (Light Mode)
-------------------------------------------------

PLATFORM: {platform_name or 'all'}
ANALYSIS MODE: {Full/Partial (error messages only)}

STRING CORPUS: {n} strings analyzed across {n} files
LOCALES DETECTED: {list}

i18n MATURITY: Level {0-5} ({name})
{if analysis_mode == "partial":}
ERROR MESSAGE SCORE: {avg_score}/10

SEVERITY SUMMARY
  Critical: {n}  |  High: {n}  |  Medium: {n}  |  Low: {n}  |  Info: {n}

OVERALL SCORE: {score}/10

OUTPUT FILE (1):
  $JAAN_OUTPUTS_DIR/detect/writing/summary{-platform}.md

Note: Run with --full for NNg tone dimensions, UI copy classification,
glossary, and governance analysis (6 output files).

"Proceed with writing summary to $JAAN_OUTPUTS_DIR/detect/writing/? [y/n]"

If run_depth == "full":

WRITING SYSTEM DETECTION COMPLETE
-----------------------------------

PLATFORM: {platform_name or 'all'}
ANALYSIS MODE: {Full/Partial (error messages only)}

STRING CORPUS: {n} strings analyzed across {n} files
LOCALES DETECTED: {list}

TONE DIMENSIONS (NNg) {scope note if partial: "based on error messages only"}
  Formality:      {score}/5    Consistency: {stddev}
  Humor:          {score}/5    Consistency: {stddev}
  Respectfulness: {score}/5    Consistency: {stddev}
  Enthusiasm:     {score}/5    Consistency: {stddev}

UI COPY COVERAGE {show "N/A" if partial analysis}
  Buttons:      {n} strings    Error messages: {n} strings
  Empty states: {n} strings    Dialogs:        {n} strings
  Toasts:       {n} strings    Onboarding:     {n} strings
  Form labels:  {n} strings    Loading:        {n} strings

i18n MATURITY: Level {0-5} ({name})
ERROR MESSAGE SCORE: {avg_score}/10

SEVERITY SUMMARY
  Critical: {n}  |  High: {n}  |  Medium: {n}  |  Low: {n}  |  Info: {n}

OVERALL SCORE: {score}/10

OUTPUT FILES (6):
  $JAAN_OUTPUTS_DIR/detect/writing/writing-system{-platform}.md  - Voice + tone + consistency
  $JAAN_OUTPUTS_DIR/detect/writing/glossary{-platform}.md        - Terminology glossary
  $JAAN_OUTPUTS_DIR/detect/writing/ui-copy{-platform}.md         - UI copy classification {or "N/A" if partial}
  $JAAN_OUTPUTS_DIR/detect/writing/error-messages{-platform}.md  - Error message audit
  $JAAN_OUTPUTS_DIR/detect/writing/localization{-platform}.md    - i18n maturity assessment
  $JAAN_OUTPUTS_DIR/detect/writing/samples{-platform}.md         - Representative samples {or "N/A" if partial}

Note: {-platform} suffix only if multi-platform mode (e.g., -web, -backend). Single-platform mode has no suffix.
      Partial analysis mode (backend/cli) produces minimal "Not Applicable" files for ui-copy.md and samples.md.

"Proceed with writing 6 output files to $JAAN_OUTPUTS_DIR/detect/writing/? [y/n]"

Do NOT proceed to Phase 2 without explicit approval.

---

PHASE 2: Write Output Files

Step 9: Write to $JAAN_OUTPUTS_DIR/detect/writing/

Create directory $JAAN_OUTPUTS_DIR/detect/writing/ if it does not exist.

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/detect-shared-reference.md sections "Output Path Logic" and "Stale File Cleanup" for platform-specific suffix convention and run_depth cleanup rules.

If run_depth == "light": Write Single Summary File

Write one file: $JAAN_OUTPUTS_DIR/detect/writing/summary{suffix}.md

Contents:

1. Universal YAML frontmatter with platform field, findings_summary, and overall_score
2. Executive Summary — BLUF of writing system findings
3. String Corpus Overview — total strings, file count, categories found (from Step 1)
4. i18n Maturity — level (0-5), locales detected, evidence (from Step 5)
5. If analysis_mode == "partial": Error Message Quality Scores — rubric scoring results (from Step 4)
6. Top Findings — up to 5 highest-severity findings with evidence blocks
7. "Run with --full for NNg tone dimensions, UI copy classification, glossary, and governance analysis (6 output files)."

If run_depth == "full": Write 6 Output Files

Write 6 output files:

File	Content	Partial Analysis Handling
$JAAN_OUTPUTS_DIR/detect/writing/writing-system{suffix}.md	Voice definition, tone spectrum (NNg dimensions), consistency score	If partial: Note scope limitation ("based on error messages only")
$JAAN_OUTPUTS_DIR/detect/writing/glossary{suffix}.md	Terminology glossary with ISO-704 statuses	If partial: Error terminology only
$JAAN_OUTPUTS_DIR/detect/writing/ui-copy{suffix}.md	UI copy classification across 8 categories	If partial: Minimal "Not Applicable" file
$JAAN_OUTPUTS_DIR/detect/writing/error-messages{suffix}.md	Error message quality audit with rubric scoring	Always included (core finding)
$JAAN_OUTPUTS_DIR/detect/writing/localization{suffix}.md	i18n maturity assessment (0-5) with evidence	If partial: Error message i18n only
$JAAN_OUTPUTS_DIR/detect/writing/samples{suffix}.md	Representative string samples per category	If partial: Minimal "Not Applicable" or error samples only

Note: {suffix} is empty for single-platform mode, or -{platform} for multi-platform mode.

Partial Analysis "Not Applicable" Files:

For platforms with analysis_mode == "partial" (backend/cli), create minimal files for ui-copy.md and samples.md:

---
findings_summary:
  informational: 1
overall_score: 10.0  # Nothing to assess
---

## Executive Summary

Platform '{platform}' does not contain UI components. Full writing system analysis is not applicable. This audit focuses on error messages only.

## Findings

### E-WRT-{PLATFORM}-001: UI Copy Analysis Not Applicable

**Severity**: Informational
**Confidence**: Confirmed (1.0)

**Description**: Platform type '{platform}' (backend/CLI) does not have UI copy. Writing system analysis is limited to error messages, validation strings, and API responses.

Each file MUST include:

1. Universal YAML frontmatter with platform field and findings_summary/overall_score
2. Executive Summary (with scope note if partial analysis)
3. Scope and Methodology (clearly state "Partial Analysis" if applicable)
4. Findings with evidence blocks (using E-WRT-{PLATFORM}-NNN or E-WRT-NNN IDs)
5. Recommendations

---

Step 9a: Seed Reconciliation

Reference: See ${CLAUDE_PLUGIN_ROOT}/docs/extending/seed-reconciliation-reference.md for comparison rules, discrepancy format, and auto-update protocol.

1. Read domain-relevant seed files: $JAAN_CONTEXT_DIR/tone-of-voice.template.md, $JAAN_CONTEXT_DIR/localization.template.md
2. Compare detection results against seed content (tone dimensions, voice characteristics, error message guidelines, i18n maturity, supported languages)
3. If discrepancies found:
   • Display discrepancy table to user
   • Offer auto-updates for non-destructive changes: [y/n]
   • Suggest /jaan-to:learn-add commands for patterns worth documenting
4. If no discrepancies: display "Seed files are aligned with detection results."

---

Step 10: Capture Feedback

"Any feedback on the writing system detection? [y/n]"

If yes:

• Run /jaan-to:learn-add detect-writing "{feedback}"

---

Skill Alignment

• Two-phase workflow with HARD STOP for human approval
• Evidence-based findings with confidence scoring
• Fork-isolated execution (context: fork)
• Output to standardized $JAAN_OUTPUTS_DIR path

Definition of Done

If run_depth == "light":

• Single summary file written to $JAAN_OUTPUTS_DIR/detect/writing/summary{suffix}.md
• Universal YAML frontmatter with overall_score
• String corpus overview and i18n maturity included
• If partial analysis: error message quality scores included
• "--full" upsell note included
• User approved output

If run_depth == "full":

• All 6 output files written to $JAAN_OUTPUTS_DIR/detect/writing/
• Universal YAML frontmatter with platform field in every file
• Every finding has evidence block with correct ID format (E-WRT-NNN for single-platform, E-WRT-{PLATFORM}-NNN for multi-platform)
• NNg tone dimensions scored with consistency analysis (note scope if partial)
• UI copy classified into 8 categories (or "Not Applicable" if partial analysis)
• Error messages scored with weighted rubric (always included)
• i18n maturity rated 0-5 with evidence (scoped to error messages if partial)
• Glossary uses ISO-704 statuses (error terminology if partial)
• Output filenames match platform suffix convention (no suffix for single-platform, -{platform} suffix for multi-platform)
• If partial analysis mode (backend/cli), minimal "Not Applicable" files created for ui-copy.md and samples.md
• Confidence scores assigned to all findings
• User approved output
• Seed reconciliation check performed (discrepancies reported or alignment confirmed)