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Get Started Free →Meta-skill for internal codebase exploration at varying depths (quick/deep/architecture)
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 141% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 186% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 180% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 71% | 0% |
| case-13 | ✓→✗ | ▼ Worse | 324% | 0% |
Meta-skill for exploring an internal codebase at varying depths. READ-ONLY workflow - no code changes.
/explore <depth> [options]If the user types just /explore with no or partial arguments, guide them through this question flow. Use AskUserQuestion for each phase.
yamlquestion: "How would you like to explore?" header: "Explore" options: - label: "Help me choose (Recommended)" description: "I'll ask questions to pick the right exploration depth" - label: "Quick - fast overview" description: "Chain: tldr tree → tldr structure (~1 min)" - label: "Deep - comprehensive analysis" description: "Chain: onboard → tldr → research → document (~5 min)" - label: "Architecture - layers & dependencies" description: "Chain: tldr arch → call graph → layer mapping (~3 min)"
Mapping:
If Answer is Unclear (via "Other"):
yamlquestion: "I want to understand how deep you want to explore. Did you mean..." header: "Clarify" options: - label: "Help me choose" description: "Not sure - guide me through questions" - label: "Quick - fast overview" description: "Just want to see what's here" - label: "Deep - comprehensive analysis" description: "Need thorough understanding" - label: "Neither - let me explain differently" description: "I'll describe what I need"
yamlquestion: "What are you trying to understand?" header: "Goal" options: - label: "Get oriented in the codebase" description: "Quick overview of structure" - label: "Understand how something works" description: "Deep dive into specific area" - label: "Map the architecture" description: "Layers, dependencies, patterns" - label: "Find where something is" description: "Locate specific code/functionality"
Mapping:
yamlquestion: "What area should I focus on?" header: "Focus" options: - label: "Entire codebase" description: "Explore everything" - label: "Specific directory or module" description: "I'll specify the path" - label: "Specific concept/feature" description: "e.g., 'authentication', 'API routes'"
If "Specific directory" or "Specific concept" → ask follow-up for the path/keyword.
yamlquestion: "What should I produce?" header: "Output" options: - label: "Just tell me what you find" description: "Interactive summary in chat" - label: "Create a documentation file" description: "Write to thoughts/shared/docs/" - label: "Create handoff for implementation" description: "Prepare context for coding agent"
Mapping:
If architecture depth selected:
yamlquestion: "Where should I start the analysis?" header: "Entry point" options: - label: "Auto-detect (main, cli, app)" description: "Find common entry points" - label: "Specific function/file" description: "I'll specify the entry point"
Based on your answers, I'll run:
**Depth:** deep
**Focus:** "authentication"
**Output:** handoff
**Path:** src/
Proceed? [Yes / Adjust settings]| Depth | Time | What it does | |-------|------|--------------| | quick | ~1 min | tldr-explorer only - fast structure overview | | deep | ~5 min | onboard + tldr-explorer + research-codebase + write doc | | architecture | ~3 min | tldr arch + call graph + layer mapping + circular dep detection |
| Option | Description | Example | |--------|-------------|---------| | --focus "area" | Focus on specific area | --focus "auth", --focus "api" | | --output handoff | Create handoff for next agent | --output handoff | | --output doc | Create documentation file | --output doc | | --entry "func" | Start from specific entry point | --entry "main", --entry "process_request" |
bash# Quick structure overview /explore quick # Deep exploration focused on auth /explore deep --focus "auth" --output doc # Architecture analysis from specific entry /explore architecture --entry "cli" --output handoff # Quick focused exploration /explore quick --focus "hooks"
Fast structure overview using tldr-explorer. Best for:
Steps:
tldr tree for file structuretldr structure for codemaps--focus provided, run tldr search for targeted resultsCommands:
bash# 1. File tree tldr tree ${PATH:-src/} --ext .py # 2. Code structure tldr structure ${PATH:-src/} --lang python # 3. Focused search (if --focus provided) tldr search "${FOCUS}" ${PATH:-src/}
Comprehensive exploration with documentation output. Best for:
Steps:
.claude/cache/tldr/), if not run onboardSubprocess:
# 1. Onboard check
if [ ! -f .claude/cache/tldr/arch.json ]; then
# Spawn onboard agent
fi
# 2. Structure analysis
tldr structure src/ --lang python
tldr calls src/
# 3. Research patterns (via scout agent)
Task: research-codebase → "Document existing patterns in ${FOCUS:-codebase}"
# 4. Write output
→ thoughts/shared/research/YYYY-MM-DD-explore-{focus}.md
→ OR thoughts/shared/handoffs/{session}/explore-{focus}.yamlArchitecture-focused analysis with layer detection. Best for:
Steps:
tldr arch for layer detectiontldr calls for cross-file call graphCommands:
bash# 1. Architecture detection tldr arch ${PATH:-src/} # Returns: entry_layer, middle_layer, leaf_layer, circular_deps # 2. Call graph tldr calls ${PATH:-src/} # Returns: edges, nodes # 3. Impact analysis from entry point (if --entry provided) tldr impact ${ENTRY} ${PATH:-src/} --depth 3
Output Structure:
yamllayers: entry: [routes.py, cli.py, main.py] # Controllers/handlers middle: [services.py, auth.py] # Business logic leaf: [utils.py, helpers.py] # Utilities call_graph: total_edges: 142 hot_paths: [process_request → validate → authorize] circular_deps: - [module_a, module_b] # A imports B, B imports A boundaries: - name: API layer files: [src/api/*] calls_to: [src/services/*]
Creates: thoughts/shared/research/YYYY-MM-DD-explore-{focus}.md
markdown--- date: {ISO timestamp} type: exploration depth: {quick|deep|architecture} focus: {focus area or "full"} commit: {git hash} --- # Codebase Exploration: {focus} ## Summary {High-level findings} ## Structure {File tree / codemaps} ## Architecture {Layer analysis - for architecture depth} ## Key Components {Important files and their roles} ## Patterns Found {Existing patterns - for deep depth} ## References - `path/to/file.py:line` - Description
Creates: thoughts/shared/handoffs/{session}/explore-{focus}.yaml
yaml--- type: exploration ts: {ISO timestamp} depth: {quick|deep|architecture} focus: {focus area} commit: {git hash} --- summary: {One-line summary of findings} structure: entry_points: [{main.py}, {cli.py}] key_modules: [{auth.py}, {routes.py}] test_coverage: [{tests/}] architecture: layers: entry: [{files}] middle: [{files}] leaf: [{files}] circular_deps: [{pairs}] findings: - {key finding with file:line} next_steps: - {Recommended action based on exploration} refs: - path: {file.py} role: {what it does}
The explore skill is designed to feed into /build brownfield:
bash# Step 1: Explore to understand /explore architecture --output handoff # Step 2: Build with context from exploration /build brownfield --from-handoff thoughts/shared/handoffs/session/explore-full.yaml
When user invokes /explore <depth> [options]:
pythondepth = args[0] # quick | deep | architecture focus = extract_option(args, "--focus") output = extract_option(args, "--output") # handoff | doc entry = extract_option(args, "--entry")
Quick:
bash# Just tldr commands, no agents tldr tree ${src_dir} --ext .py tldr structure ${src_dir} --lang python if [ -n "$focus" ]; then tldr search "$focus" ${src_dir} fi
Deep:
bash# 1. Check/run onboard if [ ! -f .claude/cache/tldr/meta.json ]; then # Spawn onboard agent via Task tool fi # 2. Structure tldr structure src/ --lang python # 3. Research (spawn scout agent) # Task tool with subagent_type: "scout" # Prompt: "Research patterns in ${focus:-codebase}" # 4. Write output # → doc or handoff based on --output
Architecture:
bash# 1. Arch detection arch_output=$(tldr arch ${src_dir}) # 2. Call graph calls_output=$(tldr calls ${src_dir}) # 3. Impact from entry (if provided) if [ -n "$entry" ]; then impact_output=$(tldr impact $entry ${src_dir} --depth 3) fi # 4. Synthesize and write output
scout; Codex keeps the parent luna_worker model and does not route to Sonnet/Haiku tiersthoughts/shared/research/ or handoff directory| Skill | When to Use | |-------|-------------| | tldr-explorer | Direct tldr commands (used internally by explore) | | tldr-code | Specific analysis commands (cfg, dfg, slice) | | onboard | First-time project setup (used by deep depth) | | research-codebase | Pattern documentation (used by deep depth) | | create_handoff | Handoff format (used by --output handoff) |
tldr not found:
bash# Check if installed which tldr # Install if missing uv tool install llm-tldr # or: pip install llm-tldr
No Python files found:
bash# Check language, adjust --lang tldr structure src/ --lang typescript # or go, rust
Empty architecture output:
bash# May need to specify src directory tldr arch ./ # Current directory tldr arch src/ # Explicit src
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 20,697 | 34,401 | +66% | 1 | 1 | 0% | 2,306 | 5,557 | +141% | 0 | 0 | — |
case-02 | fail→fail | 15,149 | 5,747 | -62% | 1 | 1 | 0% | 3,006 | 3,608 | +20% | 0 | 0 | — |
case-03 | fail→fail | 6,739 | 4,983 | -26% | 1 | 1 | 0% | 1,311 | 3,486 | +166% | 0 | 0 | — |
case-04 | fail→fail | 17,397 | 6,059 | -65% | 1 | 1 | 0% | 3,052 | 3,516 | +15% | 0 | 0 | — |
case-18 | fail→fail | 8,432 | 5,758 | -32% | 1 | 1 | 0% | 1,596 | 3,610 | +126% | 0 | 0 | — |
case-05 | fail→fail | 7,684 | 7,165 | -7% | 1 | 1 | 0% | 1,411 | 3,725 | +164% | 0 | 0 | — |
case-06 | pass→pass | 3,516 | 7,167 | +104% | 1 | 1 | 0% | 579 | 4,046 | +599% | 0 | 0 | — |
case-07 | fail→fail | 9,287 | 6,031 | -35% | 1 | 1 | 0% | 1,611 | 3,617 | +125% | 0 | 0 | — |
case-08 | fail→fail | 8,820 | 27,794 | +215% | 1 | 1 | 0% | 1,587 | 3,420 | +116% | 0 | 0 | — |
case-09 | pass→pass | 3,094 | 9,985 | +223% | 1 | 1 | 0% | 404 | 5,095 | +1161% | 0 | 0 | — |
case-10 | fail→fail | 9,931 | 5,522 | -44% | 1 | 1 | 0% | 1,717 | 3,435 | +100% | 0 | 0 | — |
case-11 | fail→pass | 8,890 | 10,245 | +15% | 1 | 1 | 0% | 1,468 | 4,204 | +186% | 0 | 0 | — |
case-12 | fail→pass | 9,178 | 7,253 | -21% | 1 | 1 | 0% | 1,556 | 4,353 | +180% | 0 | 0 | — |
case-19 | fail→pass | 15,036 | 7,702 | -49% | 1 | 1 | 0% | 2,739 | 4,678 | +71% | 0 | 0 | — |
case-13 | pass→fail | 5,298 | 3,736 | -29% | 1 | 1 | 0% | 854 | 3,622 | +324% | 0 | 0 | — |
case-14 | fail→fail | 5,858 | 5,544 | -5% | 1 | 1 | 0% | 1,030 | 3,571 | +247% | 0 | 0 | — |
case-15 | fail→fail | 9,494 | 6,464 | -32% | 1 | 1 | 0% | 1,800 | 3,592 | +100% | 0 | 0 | — |
case-16 | fail→fail | 10,890 | 5,397 | -50% | 1 | 1 | 0% | 1,898 | 3,512 | +85% | 0 | 0 | — |
case-17 | fail→fail | 28,193 | 5,157 | -82% | 1 | 1 | 0% | 1,201 | 3,470 | +189% | 0 | 0 | — |
case-20 | pass→fail | 3,234 | 3,938 | +22% | 1 | 1 | 0% | 502 | 3,359 | +569% | 0 | 0 | — |
case-21 | fail→fail | 7,458 | 7,378 | -1% | 1 | 1 | 0% | 699 | 3,850 | +451% | 0 | 0 | — |
case-22 | pass→fail | 10,599 | 5,516 | -48% | 1 | 1 | 0% | 1,819 | 3,476 | +91% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 9 counted toward the lift figure. The other 13 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +5 percentage points is the difference between those two pass rates over the 9 comparable cases. 6 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 8/2/2026 | +50% |
| gemini-3.6-flash | verified | 7/31/2026 | — |
Other measured skills in the registry, with their headline benchmark lift.