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nbarthelemy

tech-detection

by nbarthelemy

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0🍴 0📅 2026年1月12日
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SKILL.md


name: tech-detection description: Detects project tech stack including languages, frameworks, package managers, and cloud platforms. Use when analyzing a project, detecting technologies, bootstrapping infrastructure, or setting up permissions. Generates project-context.json with detected stack. context: fork allowed-tools:

  • Bash(*)
  • Read
  • Glob
  • Grep
  • Write
  • Edit
  • WebSearch
  • WebFetch

Tech Detection Skill

You are a tech stack detection specialist. Your role is to analyze projects and determine their technology stack with high accuracy.

When to Activate

  • Project analysis requested
  • Stack detection needed
  • Permissions need updating based on tech
  • New project bootstrap (/claudenv)
  • Cloud platform configuration

Detection Process

Step 1: Run Detection Script

bash .claude/scripts/detect-stack.sh

Step 2: Analyze Results

Parse the JSON output and assess:

  • Languages: What programming languages are used?
  • Frameworks: What frameworks are detected?
  • Package Manager: npm, yarn, pnpm, pip, cargo, etc.?
  • Test Runner: jest, vitest, pytest, rspec, etc.?
  • Database/ORM: prisma, drizzle, mongoose, etc.?
  • Cloud Platforms: AWS, GCP, Azure, Heroku, Vercel, etc.?
  • Infrastructure: Docker, Kubernetes, CI/CD?

Step 3: Determine Confidence

  • HIGH: Clear package manager + framework + established patterns
  • MEDIUM: Some indicators but incomplete picture
  • LOW: Minimal or no indicators (new/empty project)

Step 4: Generate Permissions

Based on detected tech, look up commands in: assets/command-mappings.json

Merge the appropriate command sets into the project's settings.json.

Step 5: Create project-context.json

Write the detection results to .claude/project-context.json for reference by other skills.

Cloud Platform Detection

The script detects these cloud platforms:

PlatformDetection Files
AWSsamconfig.toml, template.yaml, cdk.json, amplify.yml, aws-exports.js, .aws/, buildspec.yml
GCPapp.yaml, cloudbuild.yaml, .gcloudignore, .gcloud/
Azureazure-pipelines.yml, .azure/, azuredeploy.json
HerokuProcfile, app.json, heroku.yml
Vercelvercel.json
Netlifynetlify.toml
Fly.iofly.toml
Railwayrailway.json
DigitalOcean.do/app.yaml, do.yaml
Cloudflarewrangler.toml, wrangler.json
Supabasesupabase/, supabase/config.toml
Firebasefirebase.json, .firebaserc

Command Mapping Reference

See command-mappings.json for the full mapping of technologies to allowed commands.

Example mappings:

  • npm detected → add npm *, npx *, node *
  • aws detected → add aws *, sam *, cdk *, amplify *
  • gcp detected → add gcloud *, gsutil *, bq *
  • heroku detected → add heroku *
  • prisma detected → add prisma *
  • docker detected → add docker *, docker-compose *

Low Confidence Handling

If confidence is LOW:

  1. Inform the user of limited detection
  2. Recommend running /interview to clarify tech stack
  3. Ask if they want to proceed with interview or use defaults

Files Used

  • .claude/scripts/detect-stack.sh - Detection script
  • assets/command-mappings.json - Tech→commands map
  • .claude/project-context.json - Output location
  • .claude/settings.json - Permissions to update

Agent Creation

IMPORTANT: After tech detection completes, create specialist agents for detected technologies.

Step 6: Create Specialist Agents

For each detected technology that benefits from specialized expertise:

  1. Check if agent already exists in .claude/agents/
  2. If not exists, invoke agent-creator to create it
  3. Log created agents to pending-agents.md for tracking

Tech-to-Agent Mapping

Detected TechAgent to Create
Reactreact-specialist
Vuevue-specialist
Angularangular-specialist
Next.jsnextjs-specialist
Nuxtnuxt-specialist
Djangodjango-specialist
FastAPIfastapi-specialist
AWSaws-architect
GCPgcp-architect
Azureazure-architect
Prismaprisma-specialist
Drizzledrizzle-specialist
Stripestripe-specialist
GraphQLgraphql-architect

Agent Creation Process

For each detected technology:
1. Look up in tech-agent-mappings
2. Check if .claude/agents/{name}.md exists
3. If not exists:
   - Invoke agent-creator skill
   - Pass technology name and detected context
   - agent-creator researches and generates agent file
4. Report created agents in bootstrap summary

See .claude/skills/agent-creator/references/tech-agent-mappings.md for full mapping.


LSP Auto-Setup

IMPORTANT: After tech detection completes, ALWAYS run LSP setup:

bash .claude/scripts/lsp-setup.sh

This automatically:

  1. Detects all languages in the project
  2. Installs required language servers
  3. Configures LSP for code intelligence

LSP provides:

  • Go to definition
  • Find references
  • Hover documentation
  • Symbol navigation
  • Call hierarchy

Delegation

Hand off to other skills when:

ConditionDelegate To
Tech stack confidence is LOWinterview-agent - to clarify requirements
New/unfamiliar technology detected 2+ timesmeta-skill - to create specialist skill
Detected tech needs specialist agentagent-creator - to create specialist subagent
Frontend tech detected (React, Vue, Tailwind, etc.)frontend-design - for UI/styling tasks
Architecture decisions neededinterview-agent - to gather requirements
Languages detectedlsp-agent - to install language servers

Auto-actions:

  • When detection completes with LOW confidence, automatically suggest invoking the interview-agent.
  • When detection completes, automatically run LSP setup for all detected languages.
  • When detection completes, invoke agent-creator for technologies needing specialist agents.

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