* fix(#2402): honor response_language across orchestrator output + UAT checkpoint renderer Replays the in-flight bot branch fix/2402-response-language-orchestrator-coverage (seven commits, never pushed) onto current origin/next as a single squashed commit. The original work was substantial and correct; this commit preserves its full scope, trimmed where rebase conflicts + workflow size budgets required it. Three independent layers where response_language was being dropped are closed: Layer 1 — orchestrator-facing directives across workflows. Adds the strong "All user-facing output in this workflow MUST be presented in {response_language}; technical terms, code, paths, and subagent prompts stay in English" directive to ~40 workflows that previously either lacked it entirely (verify-work, new-project, new-milestone, quick, manager, and ~35 more) or carried only the weak subagent-prompt-only form (plan-phase, execute-phase). The directive covers narration between tool calls and banner output, not just the AskUserQuestion prompts. Layer 2 — UAT checkpoint renderer (src/uat.cts). buildCheckpoint now accepts an optional responseLanguage parameter and renders the frame strings ("CHECKPOINT: Verification Required", "Type `pass` or describe what's wrong.") in any of 9 languages (English/Spanish/French/German/Portuguese/Japanese/ Chinese/Korean/Italian) with an alias table covering ~30 input variants (en, es, español, ja, 日本語, etc.). cmdRenderCheckpoint reads config.response_language via loadConfig(cwd) and passes it through, so the byte-for-byte block verify-work.md reprints verbatim is already localized when written — preserving the anti-injection hygiene rule at verify-work.md (the model is forbidden to translate after the fact). CJK display width is computed by East Asian Width property ranges (W/F) so the right ║ border of the banner stays aligned for full-width characters. English fallback is byte-identical to the pre-fix behavior when response_language is unset or unrecognized. Layer 3 — literal English report templates in execute-phase. The top-of- workflow directive covers all template sites (templates are a structural source, not literal output). Inline render-language notes that previously sat at each template site were removed during the squash because they pushed execute-phase.md over its frozen pre-phase-6 byte ceiling (93600 — ADR-857 Phase 6 capstone). The single top directive covers the same surface with fewer bytes. Also extends src/docs.cts and src/init.cts to propagate response_language into the init JSON bundle of the additional workflows so the directive can read it. Tests added: - tests/uat.test.cjs: buildCheckpoint with unset/unrecognized language falls back to English default; recognized language swaps only the two frame strings while structural lines stay untouched; CJK display-width regression (independent recomputation of East Asian Width W/F ranges). - tests/workspace.test.cjs, tests/docs-update.test.cjs: response_language wiring through docs.cts/init.cts. References: #2402; reporter's three-layer triage + Layer-4 follow-up; the byte-for-byte anti-injection hygiene rule at verify-work.md (the reason Layer 2 must be renderer-side, not model-translated). This is a squash of the in-flight bot branch — seven commits representing the original implementation plus its subsequent fix/CJK-padding/test/ changeset/regen cycles, none of which were ever pushed or PR'd. The squash captures the final coherent state. * chore(#2402): backfill pr:2457 in .changeset/2402-response-language-orchestrator-coverage.md * chore(#2402): regen golden + size baseline after rebase against #2315 (PR #2451) Rebase conflicts were entirely in generated artifacts (golden-install-parity fixtures + workflow-size-baseline.json). After taking theirs during rebase, regenerated cleanly against the merged source tree.
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This workflow wires Phase 1 (session pipeline) and Phase 2 (profiling engine) into a cohesive user-facing experience. All heavy lifting is done by existing gsd-tools.cjs query handlers (with legacy gsd-tools.cjs parity where needed) and the gsd-user-profiler agent -- this workflow orchestrates the sequence, handles branching, and provides the UX.
<required_reading> Read all files referenced by the invoking prompt's execution_context before starting.
Key references:
- @$HOME/.claude/gsd-core/references/ui-brand.md (display patterns)
- @$HOME/.claude/agents/gsd-user-profiler.md (profiler agent definition)
- @$HOME/.claude/gsd-core/references/user-profiling.md (profiling reference doc) </required_reading>
If response_language is set: All user-facing questions, prompts, and explanations in this workflow MUST be presented in {response_language}. Technical terms, code, file paths, and subagent prompts stay in English — only user-facing output is translated.
1. Initialize
Parse flags from $ARGUMENTS:
- Detect
--questionnaireflag (skip session analysis, questionnaire-only) - Detect
--refreshflag (rebuild profile even when one exists)
Check for existing profile:
PROFILE_PATH="$HOME/.claude/gsd-core/USER-PROFILE.md"
[ -f "$PROFILE_PATH" ] && echo "EXISTS" || echo "NOT_FOUND"
If profile exists AND --refresh NOT set AND --questionnaire NOT set:
Text mode (workflow.text_mode: true in config or --text flag): Set TEXT_MODE=true if --text is present in $ARGUMENTS OR text_mode from init JSON is true. When TEXT_MODE is active, replace every AskUserQuestion call with a plain-text numbered list and ask the user to type their choice number. This is required for non-Claude runtimes (OpenAI Codex, Gemini CLI, etc.) where AskUserQuestion is not available.
Use AskUserQuestion:
- header: "Existing Profile"
- question: "You already have a profile. What would you like to do?"
- options:
- "View it" -- Display summary card from existing profile data, then exit
- "Refresh it" -- Continue with --refresh behavior
- "Cancel" -- Exit workflow
If "View it": Read USER-PROFILE.md, display its content formatted as a summary card, then exit. If "Refresh it": Set --refresh behavior and continue. If "Cancel": Display "No changes made." and exit.
If profile exists AND --refresh IS set:
Backup existing profile:
cp "$HOME/.claude/gsd-core/USER-PROFILE.md" "$HOME/.claude/USER-PROFILE.backup.md"
Display: "Re-analyzing your sessions to update your profile." Continue to step 2.
If no profile exists: Continue to step 2.
2. Consent Gate (ACTV-06)
Skip if --questionnaire flag is set (no JSONL reading occurs -- jump directly to step 4b).
Display consent screen:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
GSD > PROFILE YOUR CODING STYLE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Claude starts every conversation generic. A profile teaches Claude
how YOU actually work -- not how you think you work.
## What We'll Analyze
Your recent Claude Code sessions, looking for patterns in these
8 behavioral dimensions:
| Dimension | What It Measures |
|----------------------|---------------------------------------------|
| Communication Style | How you phrase requests (terse vs. detailed) |
| Decision Speed | How you choose between options |
| Explanation Depth | How much explanation you want with code |
| Debugging Approach | How you tackle errors and bugs |
| UX Philosophy | How much you care about design vs. function |
| Vendor Philosophy | How you evaluate libraries and tools |
| Frustration Triggers | What makes you correct Claude |
| Learning Style | How you prefer to learn new things |
## Data Handling
✓ Reads session files locally (read-only, nothing modified)
✓ Analyzes message patterns (not content meaning)
✓ Stores profile at $HOME/.claude/gsd-core/USER-PROFILE.md
✗ Nothing is sent to external services
✗ Sensitive content (API keys, passwords) is automatically excluded
If --refresh path: Show abbreviated consent instead:
Re-analyzing your sessions to update your profile.
Your existing profile has been backed up to USER-PROFILE.backup.md.
Use AskUserQuestion:
- header: "Refresh"
- question: "Continue with profile refresh?"
- options:
- "Continue" -- Proceed to step 3
- "Cancel" -- Exit workflow
If default (no --refresh) path:
Use AskUserQuestion:
- header: "Ready?"
- question: "Ready to analyze your sessions?"
- options:
- "Let's go" -- Proceed to step 3 (session analysis)
- "Use questionnaire instead" -- Jump to step 4b (questionnaire path)
- "Not now" -- Display "No worries. Run /gsd:profile-user when ready." and exit
3. Session Scan
Display: "◆ Scanning sessions..."
Run session scan:
SCAN_RESULT=$(gsd_run query scan-sessions --json 2>/dev/null)
Parse the JSON output to get session count and project count.
Display: "✓ Found N sessions across M projects"
Determine data sufficiency:
- Count total messages available from the scan result (sum sessions across projects)
- If 0 sessions found: Display "No sessions found. Switching to questionnaire." and jump to step 4b
- If sessions found: Continue to step 4a
4a. Session Analysis Path
Display: "◆ Sampling messages..."
Run profile sampling:
SAMPLE_RESULT=$(gsd_run query profile-sample --json 2>/dev/null)
Parse the JSON output to get the temp directory path and message count.
Display: "✓ Sampled N messages from M projects"
Display: "◆ Analyzing patterns..."
Spawn gsd-user-profiler agent using Task tool:
Use the Task tool to spawn the gsd-user-profiler agent. Provide it with:
- The sampled JSONL file path from profile-sample output
- The user-profiling reference doc at
$HOME/.claude/gsd-core/references/user-profiling.md
The agent prompt should follow this structure:
Read the profiling reference document and the sampled session messages, then analyze the developer's behavioral patterns across all 8 dimensions.
Reference: @$HOME/.claude/gsd-core/references/user-profiling.md
Session data: @{temp_dir}/profile-sample.jsonl
Analyze these messages and return your analysis in the <analysis> JSON format specified in the reference document.
Parse the agent's output:
- Extract the
<analysis>JSON block from the agent's response - Save analysis JSON to a temp file (in the same temp directory created by profile-sample)
ANALYSIS_PATH="{temp_dir}/analysis.json"
Write the analysis JSON to $ANALYSIS_PATH.
Display: "✓ Analysis complete (N dimensions scored)"
Check for thin data:
- Read the analysis JSON and check the total message count
- If < 50 messages were analyzed: Note that a questionnaire supplement could improve accuracy. Display: "Note: Limited session data (N messages). Results may have lower confidence."
Continue to step 5.
4b. Questionnaire Path
Display: "Using questionnaire to build your profile."
Get questions:
QUESTIONS=$(gsd_run query profile-questionnaire --json 2>/dev/null)
Parse the questions JSON. It contains 8 questions, one per dimension.
Present each question to the user via AskUserQuestion:
For each question in the questions array:
- header: The dimension name (e.g., "Communication Style")
- question: The question text
- options: The answer options from the question definition
Collect all answers into an answers JSON object mapping dimension keys to selected answer values.
Save answers to temp file:
# BSD/macOS mktemp only randomizes XXXXXX when it is the final path component, so make a
# suffixless temp then append the extension — portable across BSD + GNU (#1520).
ANSWERS_PATH=$(mktemp "${TMPDIR:-/tmp}/gsd-profile-answers-XXXXXX") && mv "$ANSWERS_PATH" "${ANSWERS_PATH}.json" && ANSWERS_PATH="${ANSWERS_PATH}.json" || exit 1
Write the answers JSON to $ANSWERS_PATH.
Convert answers to analysis:
ANALYSIS_RESULT=$(gsd_run query profile-questionnaire --answers "$ANSWERS_PATH" --json 2>/dev/null)
Parse the analysis JSON from the result.
Save analysis JSON to a temp file:
# BSD/macOS mktemp only randomizes XXXXXX when it is the final path component, so make a
# suffixless temp then append the extension — portable across BSD + GNU (#1520).
ANALYSIS_PATH=$(mktemp "${TMPDIR:-/tmp}/gsd-profile-analysis-XXXXXX") && mv "$ANALYSIS_PATH" "${ANALYSIS_PATH}.json" && ANALYSIS_PATH="${ANALYSIS_PATH}.json" || exit 1
Write the analysis JSON to $ANALYSIS_PATH.
Continue to step 5 (skip split resolution since questionnaire handles ambiguity internally).
5. Split Resolution
Skip if questionnaire-only path (splits already handled internally).
Read the analysis JSON from $ANALYSIS_PATH.
Check each dimension for cross_project_consistent: false.
For each split detected:
Use AskUserQuestion:
- header: The dimension name (e.g., "Communication Style")
- question: "Your sessions show different patterns:" followed by the split context (e.g., "CLI/backend projects -> terse-direct, Frontend/UI projects -> detailed-structured")
- options:
- Rating option A (e.g., "terse-direct")
- Rating option B (e.g., "detailed-structured")
- "Context-dependent (keep both)"
If user picks a specific rating: Update the dimension's rating field in the analysis JSON to the selected value.
If user picks "Context-dependent": Keep the dominant rating in the rating field. Add a context_note to the dimension's summary describing the split (e.g., "Context-dependent: terse in CLI projects, detailed in frontend projects").
Write updated analysis JSON back to $ANALYSIS_PATH.
6. Profile Write
Display: "◆ Writing profile..."
gsd_run query write-profile --input "$ANALYSIS_PATH" --json
Display: "✓ Profile written to $HOME/.claude/gsd-core/USER-PROFILE.md"
7. Result Display
Read the analysis JSON from $ANALYSIS_PATH to build the display.
Show report card table:
## Your Profile
| Dimension | Rating | Confidence |
|----------------------|----------------------|------------|
| Communication Style | detailed-structured | HIGH |
| Decision Speed | deliberate-informed | MEDIUM |
| Explanation Depth | concise | HIGH |
| Debugging Approach | hypothesis-driven | MEDIUM |
| UX Philosophy | pragmatic | LOW |
| Vendor Philosophy | thorough-evaluator | HIGH |
| Frustration Triggers | scope-creep | MEDIUM |
| Learning Style | self-directed | HIGH |
(Populate with actual values from the analysis JSON.)
Show highlight reel:
Pick 3-4 dimensions with the highest confidence and most evidence signals. Format as:
## Highlights
- **Communication (HIGH):** You consistently provide structured context with
headers and problem statements before making requests
- **Vendor Choices (HIGH):** You research alternatives thoroughly -- comparing
docs, GitHub activity, and bundle sizes before committing
- **Frustrations (MEDIUM):** You correct Claude most often for doing things
you didn't ask for -- scope creep is your primary trigger
Build highlights from the evidence array and summary fields in the analysis JSON. Use the most compelling evidence quotes. Format each as "You tend to..." or "You consistently..." with evidence attribution.
Offer full profile view:
Use AskUserQuestion:
- header: "Profile"
- question: "Want to see the full profile?"
- options:
- "Yes" -- Read and display the full USER-PROFILE.md content, then continue to step 8
- "Continue to artifacts" -- Proceed directly to step 8
8. Artifact Selection (ACTV-05)
Use AskUserQuestion with multiSelect:
- header: "Artifacts"
- question: "Which artifacts should I generate?"
- options (ALL pre-selected by default):
- "/gsd-dev-preferences command file" -- "Load your preferences in any session"
- "CLAUDE.md profile section" -- "Add profile to this project's CLAUDE.md"
- "Global CLAUDE.md" -- "Add profile to $HOME/.claude/CLAUDE.md for all projects"
If no artifacts selected: Display "No artifacts generated. Your profile is saved at $HOME/.claude/gsd-core/USER-PROFILE.md" and jump to step 10.
9. Artifact Generation
Generate selected artifacts sequentially (file I/O is fast, no benefit from parallel agents):
For /gsd-dev-preferences (if selected):
gsd_run query generate-dev-preferences --analysis "$ANALYSIS_PATH" --json
Display: "✓ Generated /gsd-dev-preferences at $HOME/.claude/skills/gsd-dev-preferences/SKILL.md"
For CLAUDE.md profile section (if selected):
gsd_run query generate-claude-profile --analysis "$ANALYSIS_PATH" --json
Display: "✓ Added profile section to CLAUDE.md"
For Global CLAUDE.md (if selected):
gsd_run query generate-claude-profile --analysis "$ANALYSIS_PATH" --global --json
Display: "✓ Added profile section to $HOME/.claude/CLAUDE.md"
Error handling: If any gsd-tools.cjs query or gsd-tools.cjs call fails, display the error message and use AskUserQuestion to offer "Retry" or "Skip this artifact". On retry, re-run the command. On skip, continue to next artifact.
10. Summary & Refresh Diff
If --refresh path:
Read both old backup and new analysis to compare dimension ratings/confidence.
Read the backed-up profile:
BACKUP_PATH="$HOME/.claude/USER-PROFILE.backup.md"
Compare each dimension's rating and confidence between old and new. Display diff table showing only changed dimensions:
## Changes
| Dimension | Before | After |
|-----------------|-----------------------------|-----------------------------|
| Communication | terse-direct (LOW) | detailed-structured (HIGH) |
| Debugging | fix-first (MEDIUM) | hypothesis-driven (MEDIUM) |
If nothing changed: Display "No changes detected -- your profile is already up to date."
Display final summary:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
GSD > PROFILE COMPLETE ✓
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Your profile: $HOME/.claude/gsd-core/USER-PROFILE.md
Then list paths for each generated artifact:
Artifacts:
✓ /gsd-dev-preferences $HOME/.claude/skills/gsd-dev-preferences/SKILL.md
✓ CLAUDE.md section <resolved claude_md_path, default ./.claude/CLAUDE.md>
✓ Global CLAUDE.md $HOME/.claude/CLAUDE.md
(Show the claude_md_path actually returned by the command — it defaults to ./.claude/CLAUDE.md but may be overridden by config or --output.)
(Only show artifacts that were actually generated.)
Clean up temp files:
Remove the temp directory created by profile-sample (contains sample JSONL and analysis JSON):
rm -rf "$TEMP_DIR"
Also remove any standalone temp files created for questionnaire answers:
rm -f "$ANSWERS_PATH" 2>/dev/null
rm -f "$ANALYSIS_PATH" 2>/dev/null
(Only clean up temp paths that were actually created during this workflow run.)
<success_criteria>
- Initialization detects existing profile and handles all three responses (view/refresh/cancel)
- Consent gate shown for session analysis path, skipped for questionnaire path
- Session scan discovers sessions and reports statistics
- Session analysis path: samples messages, spawns profiler agent, extracts analysis JSON
- Questionnaire path: presents 8 questions, collects answers, converts to analysis JSON
- Split resolution presents context-dependent splits with user resolution options
- Profile written to USER-PROFILE.md via write-profile subcommand
- Result display shows report card table and highlight reel with evidence
- Artifact selection uses multiSelect with all options pre-selected
- Artifacts generated sequentially via gsd-tools.cjs query (or gsd-tools.cjs) subcommands
- Refresh diff shows changed dimensions when --refresh was used
- Temp files cleaned up on completion </success_criteria>