skill-project-overview

name	skill-project-overview
description	Interactive repository analysis and project-overview.md generation via task creation. Invoke for /project-overview command.
allowed-tools	Bash, Read, Write, Edit, Glob, Grep, AskUserQuestion
context	direct

Project Overview Skill (Direct Execution)

Direct execution skill for analyzing a repository and creating a task with research artifact to generate project-overview.md. Uses a 3-stage workflow: auto-scan, interactive interview, and task+artifact creation.

Key behavior: The skill does NOT write project-overview.md directly. It creates a task and research artifact, then guides the user to /plan and /implement for the actual file generation.

Context References

Reference (do not load eagerly):

• Path: @specs/TODO.md - Current task list
• Path: @specs/state.json - Machine state
• Path: @.claude/context/repo/update-project.md - Generation guide (template reference)
• Path: @.claude/context/repo/project-overview.md - Current project overview

---

Execution

Step 1: Generate Session ID

session_id="sess_$(date +%s)_$(od -An -N3 -tx1 /dev/urandom | tr -d ' ')"

Step 2: Check Current State

Read .claude/context/repo/project-overview.md and check if it begins with <!-- GENERIC TEMPLATE:

head -1 .claude/context/repo/project-overview.md 2>/dev/null

If file does not exist or contains the generic template marker, proceed with full generation workflow.

If file exists and is already customized (no generic template marker), notify the user:

Use AskUserQuestion:

{
  "question": "project-overview.md already exists and appears customized. What would you like to do?",
  "header": "Existing Overview",
  "multiSelect": false,
  "options": [
    {"label": "Regenerate from scratch", "description": "Re-scan repository and create new task to replace existing overview"},
    {"label": "Cancel", "description": "Keep existing project-overview.md as-is"}
  ]
}

If "Cancel" selected, display message and exit:

Project overview generation cancelled. Current file preserved at .claude/context/repo/project-overview.md

Step 3: Stage 1 - Auto-Scan Repository

Perform automated repository analysis using bash commands. Collect findings into structured data.

3.1: Directory Structure

# Top-level directory listing
ls -1d */ 2>/dev/null | head -20

# Key directories (check existence)
for dir in src lib pkg lua tests test after doc docs; do
  [ -d "$dir" ] && echo "Found: $dir/"
done

3.2: Language Detection

Count files by extension to identify primary languages:

# Count files by extension (top 10)
find . -type f -name '*.*' \
  -not -path './.git/*' \
  -not -path './node_modules/*' \
  -not -path './.claude/*' \
  -not -path './specs/*' \
  | sed 's/.*\.//' | sort | uniq -c | sort -rn | head -10

3.3: Package Managers and Build Tools

Check for common project configuration files:

# Package managers
for f in package.json Cargo.toml go.mod flake.nix pyproject.toml Gemfile composer.json; do
  [ -f "$f" ] && echo "Package: $f"
done

# Build tools
for f in Makefile justfile Taskfile.yml CMakeLists.txt build.gradle build.sbt; do
  [ -f "$f" ] && echo "Build: $f"
done

3.4: Framework Detection

Identify frameworks from config files and dependencies:

# Framework-specific config files
for f in next.config.js next.config.ts vite.config.ts vite.config.js \
         nuxt.config.ts angular.json tsconfig.json webpack.config.js \
         init.lua lazy-lock.json; do
  [ -f "$f" ] && echo "Framework: $f"
done

# Check package.json dependencies if exists
if [ -f "package.json" ]; then
  jq -r '.dependencies // {} | keys[]' package.json 2>/dev/null | head -10
fi

3.5: Testing Detection

# Test config files
for f in jest.config.js jest.config.ts vitest.config.ts pytest.ini \
         .pytest.ini conftest.py setup.cfg phpunit.xml; do
  [ -f "$f" ] && echo "TestConfig: $f"
done

# Test file patterns
find . -type f \( -name '*_test.*' -o -name '*_spec.*' -o -name 'test_*' \) \
  -not -path './.git/*' -not -path './node_modules/*' | head -5

3.6: CI/CD Detection

# CI/CD config files
for f in .github/workflows .gitlab-ci.yml .travis.yml Jenkinsfile \
         .circleci/config.yml; do
  [ -e "$f" ] && echo "CI: $f"
done

3.7: Key Files

# Important root files
for f in README.md CLAUDE.md LICENSE CHANGELOG.md ROADMAP.md \
         .gitignore .editorconfig .prettierrc .eslintrc*; do
  [ -f "$f" ] && echo "Key: $f"
done

3.8: Entry Points

# Common entry points
for f in main.go main.py main.rs index.ts index.js init.lua \
         app.py app.ts server.ts server.js; do
  [ -f "$f" ] && echo "Entry: $f"
done

# Check src/ for entry points
for f in src/main.* src/index.* src/app.*; do
  [ -f "$f" ] && echo "Entry: $f"
done 2>/dev/null

Compile all findings into a structured summary for display.

Step 4: Stage 2 - Interactive Interview

Present auto-detected findings and ask verification questions.

4.1: Present Findings for Confirmation

Display the scan results in a readable format:

## Repository Scan Results

**Languages detected**: {languages with file counts}
**Build tools**: {list}
**Package managers**: {list}
**Frameworks**: {list or "None detected"}
**Testing**: {test framework/config or "None detected"}
**CI/CD**: {CI system or "None detected"}
**Key directories**: {list}
**Entry points**: {list}

Then ask for confirmation:

Use AskUserQuestion:

{
  "question": "Are these findings accurate? Select any that need correction:",
  "header": "Verify Findings",
  "multiSelect": true,
  "options": [
    {"label": "Languages are correct", "description": "{detected languages}"},
    {"label": "Build/framework is correct", "description": "{detected build tools and frameworks}"},
    {"label": "Testing setup is correct", "description": "{detected test framework}"},
    {"label": "Everything looks correct", "description": "No corrections needed"},
    {"label": "I need to provide corrections", "description": "Will provide corrections in next step"}
  ]
}

If "I need to provide corrections" is selected, use AskUserQuestion with free text:

{
  "question": "What corrections should be made to the scan results?",
  "header": "Corrections"
}

Apply corrections to the findings data.

4.2: Ask About Project Purpose

Use AskUserQuestion:

{
  "question": "What is the primary purpose of this project?",
  "header": "Project Purpose"
}

This is a free-text question. The user provides a description of what the project does.

4.3: Ask About Development Workflow

Use AskUserQuestion:

{
  "question": "What is your typical development workflow? Select all that apply:",
  "header": "Dev Workflow",
  "multiSelect": true,
  "options": [
    {"label": "Edit and test locally", "description": "Direct local development"},
    {"label": "Build then test", "description": "Compile/build step before testing"},
    {"label": "TDD/test-first", "description": "Write tests before implementation"},
    {"label": "CI/CD pipeline", "description": "Automated testing and deployment"},
    {"label": "REPL-driven", "description": "Interactive development environment"},
    {"label": "Other", "description": "Will describe in next step"}
  ]
}

If "Other" selected, ask for free text description.

4.4: Ask About Additional Components (Optional)

Use AskUserQuestion:

{
  "question": "Are there additional components or important details I should include?",
  "header": "Additional Info",
  "multiSelect": false,
  "options": [
    {"label": "Yes, I have more to add", "description": "Will provide additional information"},
    {"label": "No, that covers it", "description": "Proceed with task creation"}
  ]
}

If "Yes" selected, ask for free text.

Step 5: Stage 3 - Create Task and Research Artifact

5.1: Read Current State

next_num=$(jq -r '.next_project_number' specs/state.json)

5.2: Create Task Directory and Research Artifact

Compute task directory:

padded_num=$(printf "%03d" "$next_num")
task_slug="generate_project_overview"
task_dir="specs/${padded_num}_${task_slug}"
mkdir -p "${task_dir}/reports" "${task_dir}/plans" "${task_dir}/summaries"

Write research artifact at ${task_dir}/reports/01_project-overview-scan.md:

# Research Report: Task #{N}

**Task**: {N} - Generate project-overview.md
**Started**: {ISO_DATE}
**Completed**: {ISO_DATE}
**Effort**: Low
**Dependencies**: None
**Sources/Inputs**:
- Repository auto-scan
- User interview responses
**Artifacts**:
- specs/{NNN}_{SLUG}/reports/01_project-overview-scan.md
**Standards**: report-format.md, subagent-return.md

## Executive Summary

- Automated scan identified {language_count} languages, {framework} framework, {build_tool} build system
- User confirmed/corrected findings via interactive interview
- Project purpose: {user_provided_purpose}
- Development workflow: {workflow_description}

## Findings

### Technology Stack

**Primary Language**: {language}
**Framework/Platform**: {framework or "None"}
**Build System**: {build_tool}
**Package Manager**: {package_manager}
**Testing Framework**: {test_framework or "None detected"}
**CI/CD**: {ci_system or "None detected"}

### Directory Structure

{tree output with descriptions}

### Entry Points

{list of detected entry points}

### Key Files

{list of important files}

### Project Purpose

{user-provided purpose description}

### Development Workflow

{user-selected workflow with any additional details}

### Additional Notes

{any additional information from user, or "None"}

## Recommendations

This report provides all information needed to generate `.claude/context/repo/project-overview.md` using the template in `.claude/context/repo/update-project.md`.

Run `/plan {N}` to create an implementation plan, then `/implement {N}` to generate the file.

5.2.5: Assign Topic (Mode A Interactive Picker)

Before writing the task to state.json, offer an interactive topic picker:

# Get existing active topics from state.json
mapfile -t existing_topics < <(bash .claude/scripts/manage-topics.sh list)

# Build options: existing topics + "New topic..." + "Skip (no topic)"

Show picker via AskUserQuestion:

{
  "question": "Assign a topic to this task?",
  "header": "Topic",
  "multiSelect": false,
  "options": ["<existing-topic-1>", "<existing-topic-2>", "New topic...", "Skip (no topic)"]
}

• If user selects an existing topic → topic="$selected"
• If user selects "New topic..." → show free-text follow-up:

  {"question": "Enter new topic name (lowercase, kebab-case, e.g. 'agent-system'):"}
  

  Capture result as topic. Validate: non-empty, no spaces.
• If user selects "Skip (no topic)" → topic=""

5.3: Update state.json

Add new task to active_projects:

jq --argjson num "$next_num" \
   --arg name "$task_slug" \
   --arg topic "$topic" \
   '.active_projects += [{
     "project_number": $num,
     "project_name": $name,
     "status": "researched",
     "task_type": "meta",
     "title": "Generate project-overview.md",
     "description": "Generate .claude/context/repo/project-overview.md from repository scan findings and user interview",
     "topic": (if ($topic == "" | not) then $topic else null end),
     "next_artifact_number": 2
   } | if .topic == null then del(.topic) else . end] | .next_project_number = ($num + 1)' \
   specs/state.json > specs/state.json.tmp && mv specs/state.json.tmp specs/state.json

After the state.json write, assign topic via manage-topics.sh (non-blocking):

if [[ -n "$topic" ]]; then
  bash .claude/scripts/manage-topics.sh set "$next_num" "$topic" \
    2>/dev/null || echo "Warning: manage-topics.sh set failed (non-fatal)" >&2
fi

5.4: (Removed — state.json is authoritative for task entries)

The state.json update in Section 5.3 already writes the task data. TODO.md will be regenerated via generate-todo.sh in Section 5.5.

5.5: Regenerate TODO.md

Regenerate TODO.md from state.json to reflect the newly linked artifact:

bash .claude/scripts/generate-todo.sh || echo "WARNING: generate-todo.sh failed (non-fatal)" >&2

5.6: Git Commit

git add specs/ .claude/
git commit -m "task ${next_num}: create and complete research

Session: ${session_id}"

Step 6: Display Next Steps

Output to user:

## Project Overview Task Created

**Task #{N}**: Generate project-overview.md [RESEARCHED]
**Research artifact**: specs/{NNN}_{SLUG}/reports/01_project-overview-scan.md

The research artifact contains all scan findings and your responses. To generate the actual project-overview.md file:

1. Run `/plan {N}` to create an implementation plan
2. Run `/implement {N}` to generate the file

Alternatively, if you want to skip the plan step:
- Run `/implement {N} --force` to implement directly from the research

Notes

• The skill intentionally does NOT write project-overview.md directly
• It creates a task in [RESEARCHED] status, ready for /plan and /implement
• The task type is "meta" since it modifies .claude/ content
• The auto-scan uses simple bash commands (ls, find, file checks) to keep execution fast
• The interactive interview uses AskUserQuestion for multi-turn dialogue
• If the user cancels at any point, no task is created