insights（insights 搜索）

Insights Skill

When to Use This Skill

IMPORTANT: You MUST activate this skill when you detect ANY of the following signals from the user. Do NOT ask for confirmation — just start executing the orchestration steps below.

Trigger Phrases (any language)

Use this skill when the user:

• Asks to analyze sessions: "analyze my sessions", "세션 분석해줘", "look at my sessions"
• Asks for a report: "generate a report", "리포트 만들어줘", "give me a report"
• Asks about usage patterns: "how have I been using you?", "사용 패턴 보여줘", "what are my patterns?"
• Asks about statistics: "show my stats", "통계 보여줘", "how many sessions?"
• Mentions workflow insights: "insights on my workflow", "워크플로우 분석", "what's working well?"
• Asks about productivity: "am I productive?", "내 생산성은?", "how efficient am I?"
• Uses keywords: "insights", "인사이트", "analytics", "분석", "report", "리포트", "stats", "통계", "sessions", "세션"
• Asks vaguely about history: "what have we been doing?", "그동안 뭐했지?", "show me my history"

What NOT to Trigger On

Do NOT use this skill when the user:

• Asks about a specific coding task (not session analysis)
• Wants to read a single session's content (use session tools directly)
• Asks about this skill's code itself (just read the files)

Overview

The insights skill generates a comprehensive HTML report analyzing your AI coding assistant usage patterns. It automatically detects which CLI you're using (Claude Code, OpenCode, or Codex), collects session data, performs 8 categories of analysis, and produces a styled HTML report with actionable insights.

What it produces:

• HTML report with 8 analysis sections
• Quantitative statistics (sessions, messages, duration, tools used)
• Qualitative insights (workflow patterns, friction points, suggestions)
• CLI-specific recommendations
• Self-contained file:// URL (no external dependencies)

Prerequisites

Required:

• bash 4+ (check: bash --version)
• jq (JSON processor)

Supported CLIs:

• Claude Code 2.1+
• OpenCode 1.1+
• Codex

Verify dependencies:

./scripts/check-deps.sh

If dependencies are missing, the script provides install instructions.

Orchestration Steps

Follow these steps in order. Each step depends on the previous one.

Step 1: Check Dependencies

Run: scripts/check-deps.sh

Purpose: Verify jq and bash 4+ are installed.

Action:

• If exit code 0: Continue to Step 2
• If exit code 1: Show user the install instructions from stderr, then abort

Example:

cd skills/insights
./scripts/check-deps.sh

Step 2: Detect CLI Type

Run: scripts/detect-cli.sh

Purpose: Auto-detect which AI coding CLI the user is running.

Output: Single line: claude-code, opencode, codex, or unknown

Action:

• Capture the output as $CLI_TYPE
• If output is unknown: Ask user which CLI they're using, or abort
• Otherwise: Continue to Step 3

Example:

CLI_TYPE=$(./scripts/detect-cli.sh)
echo "Detected CLI: $CLI_TYPE"

Override: User can specify CLI manually:

CLI_TYPE=$(./scripts/detect-cli.sh --cli claude-code)

Step 3: Collect Session Metadata

Run: scripts/collect-sessions.sh --cli $CLI_TYPE

Purpose: Collect session metadata from the CLI's storage directory.

Output: JSON array of session objects (stdout)

Action:

• Capture output as $SESSIONS_JSON
• Verify it's valid JSON: echo "$SESSIONS_JSON" | jq. > /dev/null
• If empty array []: Inform user no sessions found, abort
• Otherwise: Continue to Step 4

Example:

SESSIONS_JSON=$(./scripts/collect-sessions.sh --cli "$CLI_TYPE" --days 30)
echo "$SESSIONS_JSON" | jq 'length'  # Show session count

Options:

• --limit N: Limit to N most recent sessions (default: unlimited, filtered by --days)
• --days N: Only include sessions from the last N days (default: 30)
• --session-dir <path>: Override default session directory

Step 4: Aggregate Statistics

Run: scripts/aggregate-stats.sh (reads from stdin)

Purpose: Compute quantitative statistics from session metadata.

Input: Session metadata JSON array (from Step 3)

Output: Aggregated stats JSON object (stdout)

Action:

• Pipe $SESSIONS_JSON to aggregate-stats.sh
• Capture output as $STATS_JSON
• Verify valid JSON
• Continue to Step 5

Example:

STATS_JSON=$(echo "$SESSIONS_JSON" | ./scripts/aggregate-stats.sh)
echo "$STATS_JSON" | jq '.total_sessions, .total_messages'

Stats included:

• total_sessions, total_messages, total_duration_hours
• date_range (start, end)
• tool_counts, languages, projects
• git_commits, git_pushes
• days_active, messages_per_day
• message_hours (24-element array)

Step 5: Extract Session Facets (Optional but Recommended)

Purpose: Extract qualitative facets from individual sessions for richer analysis.

Limit: Up to 20 sessions (to manage token cost)

Prompt: Use the facet extraction prompt from references/facet-extraction.md

Action:

1. Select up to 20 sessions from $SESSIONS_JSON (prioritize recent, diverse sessions)
2. For each session:

- Read the full session data (messages, tool calls, outcomes) - Execute the facet extraction prompt with session context - Parse the JSON response

1. Aggregate facets into $FACETS_JSON

Facet fields:

• goal_categories (debugging, feature_implementation, refactoring, etc.)
• user_satisfaction_counts (happy, satisfied, frustrated, etc.)
• friction_counts (misunderstood_request, buggy_code, etc.)
• outcome_level (success, partial_success, blocked, abandoned)

Cache: Store extracted facets in ~/.agent-insights/cache/facets/<session-id>.json to avoid re-extraction.

Example:

# Pseudo-code (agent executes this logic)
for session in (first 20 sessions):
  cache_file="~/.agent-insights/cache/facets/${session.session_id}.json"
  if cache_file exists:
    facet = read cache_file
  else:
    facet = execute_facet_extraction_prompt(session)
    write facet to cache_file
  facets.append(facet)

Step 6: Run 8 Analysis Prompts

Purpose: Generate qualitative insights across 8 categories.

Prompts: All 8 prompts are in references/analysis-prompts.md

Context: Provide each prompt with:

• $STATS_JSON (aggregated statistics)
• $FACETS_JSON (extracted facets, if available)
• $CLI_TYPE (for CLI-specific suggestions)

Prompts to execute:

1. project_areas - What the user works on (4-5 areas)
2. interaction_style - How the user interacts (narrative + key_pattern)
3. what_works - Impressive workflows (3 items)
4. friction_analysis - Pain points (3 categories × 2 examples)
5. suggestions - CLI-agnostic + CLI-specific features (use references/suggestions-by-cli.md)
6. on_the_horizon - Future opportunities (3 items with copyable_prompt)
7. fun_ending - Memorable moment (headline + detail)
8. at_a_glance - Executive summary (4 fields: whats_working, whats_hindering, quick_wins, ambitious_workflows)

Execution:

• Run all 8 prompts in parallel if possible (faster)
• Each prompt returns a JSON object
• Combine all 8 responses into $INSIGHTS_JSON

Example:

{
  "project_areas": {...},
  "interaction_style": {...},
  "what_works": {...},
  "friction_analysis": {...},
  "suggestions": {...},
  "on_the_horizon": {...},
  "fun_ending": {...},
  "at_a_glance": {...}
}

Important: Each prompt includes "RESPOND WITH ONLY A VALID JSON OBJECT" instruction. Parse responses carefully.

Step 7: Generate HTML Report

Run: scripts/generate-report.sh --stats <stats-file> --cli $CLI_TYPE --output <path>

Purpose: Inject JSON data into HTML template and create final report.

Input:

• $INSIGHTS_JSON (from Step 6, via stdin)
• $STATS_JSON (from Step 4, via --stats file)
• $CLI_TYPE (via --cli flag)

Output: Path to generated HTML file (stdout)

Action:

1. Write $STATS_JSON to a temp file
2. Pipe $INSIGHTS_JSON to generate-report.sh
3. Capture output path as $REPORT_PATH
4. Continue to Step 8

Example:

STATS_FILE=$(mktemp)
echo "$STATS_JSON" > "$STATS_FILE"

REPORT_PATH=$(echo "$INSIGHTS_JSON" | ./scripts/generate-report.sh \
  --stats "$STATS_FILE" \
  --cli "$CLI_TYPE" \
  --language "${LANGUAGE:-en}" \
  --output ~/.agent-insights/reports/report-$(date +%Y-%m-%d).html)

echo "Report generated: $REPORT_PATH"

Default output: ./insights-report.html

Recommended output: ~/.agent-insights/reports/report-YYYY-MM-DD.html

Step 8: Present to User

Purpose: Show summary and provide file:// URL.

Action:

1. Read key stats from $STATS_JSON:

- total_sessions - total_messages - total_duration_hours - date_range

1. Read at-a-glance summary from $INSIGHTS_JSON
2. Present to user:

Example output:

✅ Insights Report Generated

📊 Summary:
- Sessions analyzed: 42
- Total messages: 1,247
- Time period: 2026-01-15 to 2026-02-06
- Total duration: 18.5 hours

🎯 At a Glance:
- What's working: You're effectively using Claude for rapid prototyping...
- What's hindering: Frequent context resets when switching between projects...
- Quick wins: Try using /compact to reduce token usage...
- Ambitious workflows: Explore multi-file refactoring with LSP tools...

📄 Full report: file://$REPORT_PATH

Open the report in your browser to see detailed insights across 8 categories.

Output Format

The generated HTML report includes:

Header:

• Title: "Insights Report"
• CLI type badge
• Generation date
• Stats bar (sessions · messages · hours · commits)

8 Sections:

1. At a Glance - 4-item executive summary
2. What You Work On - Project areas with session counts
3. Your Style - Interaction style narrative
4. What's Working Well - Impressive workflows
5. Friction Points - Categorized pain points
6. Suggestions - Features and usage patterns to try
7. On the Horizon - Future opportunities with copyable prompts
8. Fun Moment - Memorable headline

Features:

• Self-contained (no external resources)
• Dark/light theme support (auto-detects via prefers-color-scheme)
• Responsive design (mobile-friendly)
• Print-friendly styles

Reference Files

All supporting documentation is in references/:

• analysis-prompts.md - Complete text of all 8 analysis prompts with expected JSON schemas
• facet-extraction.md - Session facet extraction prompt and enums
• schema.md - JSON schemas for session metadata, stats, facets, and insights
• cli-formats.md - Detailed documentation of session storage formats for each CLI
• suggestions-by-cli.md - CLI-specific feature suggestions (MCP servers, custom skills, hooks, etc.)

Troubleshooting

"jq: command not found"

Solution: Install jq:

• macOS: brew install jq
• Linux: apt install jq or yum install jq

"Bash version too old"

Solution: Upgrade to bash 4+:

• macOS: brew install bash (then restart terminal)
• Linux: Usually already 4+

"No sessions found"

Possible causes:

1. CLI not detected correctly

- Run: ./scripts/detect-cli.sh - Override: ./scripts/detect-cli.sh --cli claude-code

1. Session directory empty

- Check: ls ~/.claude/projects/ (Claude Code) - Check: ls ~/.local/share/opencode/storage/session/ (OpenCode) - Check: ls ~/.codex/sessions/ (Codex)

1. Sessions filtered out (<2 messages, <1 minute)

- Review filtering logic in scripts/collect-sessions.sh

"Report generation fails"

Possible causes:

1. Invalid JSON from analysis prompts

- Verify: echo "$INSIGHTS_JSON" | jq. - Check: Each prompt response is valid JSON

1. Missing template file

- Verify: ls scripts/templates/report.html

1. Python not available

- generate-report.sh uses Python for JSON injection - Verify: python3 --version

"Analysis prompts return non-JSON"

Solution: Ensure each prompt includes "RESPOND WITH ONLY A VALID JSON OBJECT" instruction. If the model returns markdown code blocks, strip them:

response=$(echo "$response" | sed 's/^```json//; s/^```//; s/```$//')

Examples

Basic Usage

cd skills/insights

# 1. Check dependencies
./scripts/check-deps.sh || exit 1

# 2. Detect CLI
CLI_TYPE=$(./scripts/detect-cli.sh)

# 3. Collect sessions
SESSIONS=$(./scripts/collect-sessions.sh --cli "$CLI_TYPE" --days 30)

# 4. Aggregate stats
STATS=$(echo "$SESSIONS" | ./scripts/aggregate-stats.sh)

# 5. Extract facets (agent logic, not shown)

# 6. Run analysis prompts (agent logic, not shown)

# 7. Generate report
STATS_FILE=$(mktemp)
echo "$STATS" > "$STATS_FILE"
REPORT=$(echo "$INSIGHTS" | ./scripts/generate-report.sh --stats "$STATS_FILE" --cli "$CLI_TYPE")

# 8. Present
echo "Report: file://$REPORT"

Override CLI Detection

# Force Claude Code
CLI_TYPE=$(./scripts/detect-cli.sh --cli claude-code)

Limit Sessions

# Analyze only last 10 sessions
SESSIONS=$(./scripts/collect-sessions.sh --cli "$CLI_TYPE" --limit 10)

Custom Output Path

# Save to specific location
mkdir -p ~/reports
REPORT=$(echo "$INSIGHTS" | ./scripts/generate-report.sh \
  --stats stats.json \
  --cli claude-code \
  --output ~/reports/insights-$(date +%Y%m%d).html)

Notes

• Token cost: Facet extraction (Step 5) and analysis prompts (Step 6) consume tokens. Limit facet extraction to 20 sessions.
• Caching: Cache extracted facets in ~/.agent-insights/cache/facets/ to avoid re-extraction on subsequent runs.
• Parallelization: Run the 8 analysis prompts in parallel for faster execution.
• Privacy: All data stays local. No external API calls. Report is self-contained HTML.
• Extensibility: To add a new CLI, create an adapter in collect-sessions.sh following the existing pattern.

Language Support

The insights skill supports multi-language report generation.

Supported Languages

• Built-in: English (en), Korean (ko)
• Dynamic: Any language via AI translation

How to Specify Language

1. CLI flag: --language <code> (e.g., --language ko)
2. Environment variable: LANG or LC_ALL (e.g., LANG=ko_KR.UTF-8)
3. Default: English (en)

What Gets Translated

• HTML report UI strings: Section titles, labels (26 strings)
• Analysis content: Insights JSON values (via prompt instruction)

What Stays in English

• JSON keys: Always English for consistency
• Shell script output: Help messages, errors

Version

This skill targets:

• Claude Code 2.1+
• OpenCode 1.1+
• Codex (latest)

For older versions, session formats may differ. Check references/cli-formats.md for compatibility notes.