Guides project-specific configuration for CodeScope.
Install
mkdir -p .claude/skills/onboard-jwadhwa2259 && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/11549" && unzip -o skill.zip -d .claude/skills/onboard-jwadhwa2259 && rm skill.zipInstalls to .claude/skills/onboard-jwadhwa2259
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Configure CodeScope for this project. Detects project type, languages, and build commands, then walks through agent model selection and workflow preferences. Run this before /codescope:bootstrap.Key capabilities
- →Check Node.js version compatibility for CodeScope
- →Detect project type, languages, and build commands
- →Allow manual configuration if auto-detection fails
- →Offer agent model selection for various CodeScope roles
- →Configure workflow preferences like verbosity and clarification style
How it works
The skill guides the user through a multi-step wizard, detecting project details, prompting for agent model and workflow preferences, and then writing a complete configuration file.
Inputs & outputs
When to use onboard
- →Configuring CodeScope for a new project
- →Updating project build configurations
- →Setting up agent workflows
About this skill
CodeScope Onboarding
You are running the CodeScope onboarding wizard. Follow these steps exactly in sequence.
Step 0: Prerequisites Check
-
Check Node.js version by reading the output of
node --version. If the major version is less than 22, tell the user: "CodeScope requires Node.js 22 or later. Current version: {version}. Upgrade at https://nodejs.org" Stop here -- do not continue onboarding until Node.js is upgraded. -
If Node.js is sufficient, confirm: "Node.js {version} detected. Requirements met."
-
Check if
.claude/codescope/config.ymlalready exists in the project root.- If it exists, ask the user:
"CodeScope is already configured. Would you like to: (1) Update existing config, or (2) Start fresh?"
- If "Start fresh": warn "This will replace your existing CodeScope configuration. All current settings will be lost. Proceed?" then continue from Step 1.
- If "Update existing config": read the existing config and use its values as defaults in the steps below.
- If it exists, ask the user:
"CodeScope is already configured. Would you like to: (1) Update existing config, or (2) Start fresh?"
Step 1: Project Detection
Read the following files to detect project configuration:
package.json-- project name, type (check forworkspacesfield = monorepo), build/test scriptstsconfig.json/jsconfig.json-- TypeScript/JavaScriptpyproject.toml/setup.py/requirements.txt-- Pythondocker-compose.yml/compose.yml-- services (monorepo indicator)playwright.config.ts/cypress.config.ts-- E2E tool.github/workflows/*.yml-- CI/CD (informational)
Present your findings to the user for confirmation: "Detected: {type} project with {languages}. Build: {buildCommand}. Test: {testCommand}. Confirm or correct?"
If detection found nothing: "Could not detect project configuration automatically. Let's set it up manually." Then ask the user for:
- Project type: single / monorepo / polyrepo
- Primary languages (select from: typescript, javascript, python)
- Build command (or "none")
- Test command (or "none")
- E2E tool (playwright / cypress / none)
Step 1b: Returning User Check
Check if ~/.codescope/global-memory.md exists and has saved preferences.
If it does, show the user:
"Found your preferences from a previous project. Use same setup or customize?"
- "Use same setup": Apply saved preferences as defaults for Steps 2 and 3, skip to Step 4.
- "Customize": Continue to Steps 2 and 3 with saved preferences as suggested defaults.
Step 2: Agent Model Selection
Show the user the 6 agent model assignments with recommended defaults: "Agent model assignments (recommended defaults shown). Accept all or select specific agents to override:"
| Agent | Default | Purpose |
|---|---|---|
| researcher | inherited | Maps structure, frameworks, entry points |
| convention_detector | inherited | Detects code patterns and conventions |
| risk_analyzer | inherited | Builds knowledge graph, identifies danger zones |
| learning_synthesizer | inherited | Captures project learnings |
| eval_judge | inherited | Scores changes on 4 criteria |
| debug | inherited | Fixes issues through targeted re-execution |
Options: haiku, sonnet, opus, inherited (uses your current session model)
Offer: "Accept all defaults" or let the user override specific agents.
Step 3: Workflow Preferences
"Workflow preferences (recommended defaults shown):"
- Orient verbosity: brief (concise ~50 lines) or detailed (~200 lines)? Default: brief
- Clarification style: thorough (asks detailed questions) / minimal (fewer questions) / auto (decides based on task specificity)? Default: thorough
- Eval gate mode: interactive (you review findings) / auto-debug (sends all to debug) / auto-skip-minor (only MEDIUM+ to debug)? Default: interactive
- Convention strictness: suggest-only (suggestions) / warn (warnings) / block (errors)? Default: suggest-only
Step 4: Agent Teams Detection
Check if agent teams are available for parallel execution during orient (D-41):
-
Run the detection check:
node --import tsx/esm -e "import { detectAgentTeamsOnboard } from './src/onboard/agent-teams.js'; console.log(JSON.stringify(detectAgentTeamsOnboard()));" -
Parse the JSON result and act based on the
statusfield:-
If status is
already_enabled: Display to the user: "Agent teams already enabled. Orient will use parallel execution when the planner identifies independent tasks." Proceed to Step 5. -
If status is
not_enabled: Ask the user: "Agent teams enable parallel execution during orient. Enable now? [Y/n]"-
If yes (or Enter): Run the enablement:
node --import tsx/esm -e "import { enableAgentTeams } from './src/onboard/agent-teams.js'; console.log(JSON.stringify(enableAgentTeams()));"Parse the result. If
successis true, display: "Agent teams enabled in~/.claude/settings.json. Orient will use parallel execution when the planner identifies independent tasks." Ifsuccessis false, display the error message and continue. -
If no: Display: "Agent teams not enabled. Orient will run sequentially. You can enable later via
/codescope:settings."
-
-
Step 5: Write Config & Create Structure
-
Create the
.claude/codescope/directory tree with all subdirectories:- .claude/codescope/
- .claude/codescope/services/
- .claude/codescope/orient/
- .claude/codescope/plans/
- .claude/codescope/execution/
- .claude/codescope/reports/
- .claude/codescope/reports/screenshots/
-
Write
.claude/codescope/.gitignorewith selective rules:- Ignore: graph.db, graph.db-wal, graph.db-shm, execution/, reports/screenshots/, usage.md
- Track: config.yml, conventions-enforced.md
-
Create
~/.codescope/directory and~/.codescope/global-memory.mdif they don't exist. -
Write
.claude/codescope/config.ymlwith all the user's choices merged with defaults:schema_version: 1 project: name: {detected or entered project name} type: {single|monorepo|polyrepo} languages: [{detected languages}] services: [{if monorepo, list services with paths}] build_command: {detected or entered} test_command: {detected or entered} e2e_tool: {detected or entered or null} e2e_command: {if e2e tool, the command} agents: researcher: { model: {chosen} } convention_detector: { model: {chosen} } risk_analyzer: { model: {chosen} } learning_synthesizer: { model: {chosen} } eval_judge: { model: {chosen} } debug: { model: {chosen} } orient: verbosity: {chosen, default: brief} clarification: {chosen, default: thorough} research_sources: [context7, web_search] max_research_time: 60 execute: max_agents_concurrent: 3 verify: build_command: {same as project.build_command} timeout_seconds: 120 tests: unit: {same as project.test_command} e2e: tool: {e2e_tool or none} command: {e2e_command} auto_smoke: true static_check: true blast_radius_diff: true eval: mode: {chosen, default: interactive} auto_debug_max_cycles: 3 criteria: scope_compliance: true convention_adherence: true completeness: true correctness: true conventions: detection_threshold: 80 min_files: 10 strictness: {chosen, default: suggest-only} auto_confirm_high_confidence: false learning: project_memory: true global_memory: true global_memory_path: "~/.codescope/global-memory.md" max_active_learnings: 50 confidence_decay: gotchas: 90 decisions: 180 auto_capture: true capture_ignores: true bootstrap: scaling: auto squad_threshold_loc: 100000 max_squads: 10 display: progress_reports: true agent_activity: minimal eval_detail: full -
Show the user a brief summary: "Configuration saved to .claude/codescope/config.yml. Run /codescope:bootstrap to analyze your codebase."
When not to use it
- →When CodeScope is already fully configured and running
- →When the task is to bootstrap the codebase analysis
- →When only needing to modify specific CodeScope settings
Prerequisites
Limitations
- →Requires Node.js 22 or later.
- →If `.claude/codescope/config.yml` exists, it prompts to update or start fresh, potentially overwriting settings.
- →Agent teams detection and enablement are optional steps within the workflow.
How it compares
This skill provides an interactive, guided setup process for CodeScope, automating project detection and offering structured choices, unlike manual configuration file creation.
Compared to similar skills
onboard side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| onboard (this skill) | 0 | 4mo | No flags | Beginner |
| resources | 1 | 2mo | Review | Intermediate |
| emailable-automation | 0 | 3mo | No flags | Intermediate |
| project-workflow | 0 | 6mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
You might also like
resources
windmill-labs
MUST use when managing resources.
emailable-automation
onfire7777
Automate Emailable tasks via Rube MCP (Composio). Always search tools first for current schemas.
project-workflow
sumanin5
项目启动、环境搭建与日常开发工作流。涵盖 local 与 docker 两种模式下的启动指令。
clui-cc-claude-overlay
Aradotso
Command Line User Interface for Claude Code — a floating macOS desktop overlay with multi-tab sessions, permission approval UI, voice input, and skills marketplace.
telegram-bot-builder
davila7
Expert in building Telegram bots that solve real problems - from simple automation to complex AI-powered bots. Covers bot architecture, the Telegram Bot API, user experience, monetization strategies, and scaling bots to thousands of users. Use when: telegram bot, bot api, telegram automation, chat bot telegram, tg bot.
reddit-api
alinaqi
Reddit API with PRAW (Python) and Snoowrap (Node.js)