event4u-app/agent-config

project-analyzer

ONLY when user asks for single-pass tech-stack detection or `agents/evidence/analysis/` write-up. Deep multi-pass audit → `universal-project-analysis`. Raw primitives → `project-analysis-core`.

97Collecting
See how to use itView GitHub source
npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/project-analyzer"

Quick start

Start using it in three steps

Install it or open the source, trigger it with a clear task, then follow the source workflow.

1

Install the Skill

npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/project-analyzer"
2

Describe the task

Use project-analyzer to help me with: [describe your task]. Before you begin, tell me what input you need, the steps you will follow, and the expected output.

3

Follow the workflow

5 key workflow steps, examples, and cautions are distilled below.

Continue to the workflow

Direct answers

Answers to review before you install

What is project-analyzer?

ONLY when user asks for single-pass tech-stack detection or `agents/evidence/analysis/` write-up. Deep multi-pass audit → `universal-project-analysis`.

Who should use project-analyzer?

It is relevant to workflows involving Documentation, Engineering, Research.

How do you install project-analyzer?

SkillSignal detected this source-specific command: npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/project-analyzer". Inspect the repository and command before running it.

Which Agent platforms does it support?

The upstream source does not declare a dedicated Agent platform.

What permissions or risks should you review?

No obvious permission action was detected by the static rules. This is not proof that the Skill is safe.

What are the current evidence limits?

This page combines upstream documentation with deterministic repository, quality, and static-risk signals. It is not described as a manual test or security review.

SkillSignal brief

Decide whether it fits your work first

ONLY when user asks for single-pass tech-stack detection or `agents/evidence/analysis/` write-up. Deep multi-pass audit → `universal-project-analysis`.

Useful in these contexts

Not yet included in a workflow collection

Core capabilities

DocumentationEngineeringResearch

Distilled from the source

Understand this Skill in one minute

About 7 min · 12 sections

When it is worth using

  1. Starting work on an unfamiliar project

  2. Onboarding to a new codebase

  3. Auditing the current state of agent docs, contexts, and features

  4. Creating a baseline understanding of the project for future work

Core workflow

  1. 1

    Ask scope: Full analysis or specific area (e.g. only domains, only API)?

  2. 2

    Run phases incrementally — show findings after each phase, ask before continuing.

  3. 3

    Write files after each phase — don't batch all writing to the end.

  4. 4

    Ask before creating each file with numbered options:

  5. 5

    Update existing files if re-running analysis — don't create duplicates.

Examples and typical usage

  1. Structured analysis document in agents/evidence/analysis/

  2. Tech stack inventory with versions and dependencies

  3. Architecture diagram or module map

Repository stars
7
Repository forks
1
Quality
97/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

97/100
Documentation30/30
Specificity25/25
Maintenance20/20
Trust signals22/25

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View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 7 min

project-analyzer

When to use

Use this skill when:

  • Starting work on an unfamiliar project
  • Onboarding to a new codebase
  • Auditing the current state of agent docs, contexts, and features
  • Creating a baseline understanding of the project for future work
  • Generating comprehensive project documentation for knowledge transfer

Do NOT use when:

  • Small, focused code changes
  • Regular feature development

Procedure: Analyze a project

A project analysis is a systematic walkthrough of the entire codebase that:

  1. Detects — framework, language, tech stack, patterns, legacy vs. modern
  2. Inventories — modules, services, models, endpoints, tests
  3. Analyzes — business domains, data flows, API contracts, dependencies
  4. Documents — writes structured analysis files to agents/evidence/analysis/
  5. Assesses — identifies gaps, technical debt, missing docs

It orchestrates other skills and commands to produce a comprehensive picture.

Analysis output

All analysis results are written to agents/evidence/analysis/ in a structured directory layout. The goal: someone could rebuild the project from these documents alone.

Directory structure

agents/evidence/analysis/
├── overview.md                  ← Project profile, tech stack, architecture summary
├── architecture/
│   ├── database.md              ← Schema, connections, multi-tenancy, migrations
│   ├── api.md                   ← Versioning, routes, middleware, auth flow
│   ├── infrastructure.md        ← Docker, CI/CD, deployment, AWS, monitoring
│   └── patterns.md              ← Design patterns used (Repository, Service, Pipeline, etc.)
├── domains/
│   ├── {domain}.md              ← One file per business domain (see below)
│   └── ...
├── modules/
│   ├── {module}.md              ← One file per module (see below)
│   └── ...
├── models/
│   ├── api-database.md          ← All api_database models, relationships, key columns
│   └── customer-database.md     ← All customer_database models, relationships, key columns
├── services/
│   └── service-map.md           ← All services with purpose, dependencies, key methods
├── api/
│   ├── endpoints-v1.md          ← All v1 endpoints: route, controller, request, resource
│   ├── endpoints-v2.md          ← All v2 endpoints: route, controller, request, resource
│   └── contracts.md             ← API contracts: request/response shapes, validation rules
└── testing/
    └── test-map.md              ← Test suites, coverage areas, test data strategy

Domain analysis files

Each business domain gets its own file in agents/evidence/analysis/domains/. A domain groups related models, services, controllers, jobs, and events around a business concept:

DomainWhat it covers
projects.mdConstruction sites, positions, project status, geocoding
planning.mdAppointments, crew assignments, capacity planning
users.mdEmployees, roles, permissions, authentication
equipment.mdMachines, vehicles, repairs, time registration
working-times.mdTime tracking, absences, wage types, logs
reports.mdDaily reports, images, measured quantities
files.mdFile uploads, file links, storage
customers.mdTenant management, customer config, modules
webhooks.mdWebhook dispatching, retry logic
imports.mdClient software imports (cross-reference with module)
gps.mdGPS tracking, geofencing
notifications.mdEmail, push, private messages, Slack
dashboard.mdDashboard widgets, statistics

Not every project has all domains. Only create files for domains that actually exist.

Domain file template

Each domain file should contain:

# Domain: {Name}

## Purpose

{What this domain does in 2-3 sentences}

## Models

| Model | Table | Connection | Key Relationships |
|---|---|---|---|

## Services

| Service | Purpose | Key Methods |
|---|---|---|

## Controllers (API Endpoints)

| Endpoint | Controller | Request | Resource |
|---|---|---|---|

## Jobs & Events

| Class | Type | Trigger | What it does |
|---|---|---|---|

## Business Rules

- {Rule 1: e.g. "A project can only be deleted if it has no working times"}
- {Rule 2}

## Data Flow

{Describe how data moves through this domain — from input to storage to output}

## Dependencies

- Depends on: {other domains}
- Depended on by: {other domains}

Module analysis files

Each module gets its own file in agents/evidence/analysis/modules/. Format:

# Module: {Name}

## Purpose

{What this module does}

## Structure

{Directory tree with key files}

## Public API

{What other parts of the app use from this module: Services, Events, Models}

## Internal Components

{Controllers, Jobs, Commands, Listeners that are module-internal}

## Configuration

{Config files, .env variables, feature flags}

## Testing

{Test suites, test data, stubs}

Detection checklist

Framework & language (multi-stack)

CheckHow to detect
PHP runtime + versioncomposer.jsonrequire.php
Laravel applicationartisan file at repo root + laravel/framework in composer.json
Symfony applicationbin/console + symfony/framework-bundle in composer.json
Composer packagecomposer.json without artisan / bin/console
Node.js runtimepackage.json exists
TypeScripttsconfig.json exists
Frontend frameworkpackage.jsonreact, vue, svelte, solid, astro, @angular/core
Meta-frameworkpackage.jsonnext, nuxt, remix, sveltekit, astro
Python runtimepyproject.toml, requirements.txt, setup.py, or Pipfile
Python frameworkpyproject.toml / requirements.txtdjango, fastapi, flask
Go modulego.mod exists
Rust crate / workspaceCargo.toml exists
Ruby appGemfilerails, sinatra
.NET project*.csproj, *.fsproj, or global.json
Java / Kotlinpom.xml, build.gradle, or build.gradle.kts

After detecting any match, record the stack in the analysis output and select the matching project-analysis-* sub-skill (Laravel, Symfony, Next.js, React, Node/Express, Zend/Laminas) — fall back to project-analysis-core if no framework-specific sub-skill applies.

Project type

SignalType
artisan + laravel/frameworkLaravel application
bin/console + symfony/framework-bundleSymfony application
composer.json without artisan / bin/consoleComposer package or legacy PHP
package.json with next / nuxt / remix / sveltekit / astroMeta-framework SSR/SSG app
package.json with express / fastify / koa / hapiNode HTTP service
package.json with @nestjs/coreNestJS application
pyproject.toml with django / fastapi / flaskPython web app
go.mod with gin-gonic/gin / labstack/echo / gofiber/fiberGo HTTP service
Module system (app/Modules/, src/modules/, packages/*)Modular monolith / monorepo
Multi-tenant signal (customer_database, tenant middleware, RLS)Multi-tenant SaaS
apps/* + packages/* + turbo.json / nx.json / pnpm-workspaceMonorepo

Legacy indicators (stack-aware)

SignalMeaning
PHP: no declare(strict_types=1) in most filesPre-modern PHP style
PHP: no typed properties / return typesLegacy PHP (< 7.4)
PHP: no phpstan.neon / rector.phpNo static analysis
TS: // @ts-ignore / // @ts-nocheck density; any widespreadUntyped TypeScript
TS: no tsconfig.json strict: trueLoose TypeScript
JS: no ESLint config or eslint.config.*No linting
Python: no type hints in most signatures; no py.typedUntyped Python
Python: no mypy.ini / pyrightconfig.json / ruff.tomlNo static analysis
Go: no golangci.ymlNo lint pipeline
Rust: no clippy.toml and warnings ignoredNo lint hygiene
var_dump() / console.log() / print() / fmt.Println() left in codeLegacy debugging patterns
No tests or very few testsLow test coverage
Mixed naming conventions across the same moduleInconsistent standards

Build & tooling (stack-agnostic)

CheckHow to detect
Task runnerMakefile, Taskfile.yml, justfile, package.json scripts, composer.json scripts
Dockerdocker-compose.yml, compose.yaml, Dockerfile
CI/CD.github/workflows/, .gitlab-ci.yml, .circleci/config.yml, azure-pipelines.yml
Quality toolsPHP: phpstan.neon, ecs.php, rector.php. TS/JS: eslint.config.*, .prettierrc*, tsconfig.json. Python: ruff.toml, mypy.ini. Go: .golangci.yml. Rust: clippy.toml
Editor config.editorconfig
Code reviewCODEOWNERS, PR templates (.github/pull_request_template.md)
DependenciesLockfile presence: composer.lock, package-lock.json, pnpm-lock.yaml, yarn.lock, poetry.lock, uv.lock, go.sum, Cargo.lock

Analysis phases

Phase 1: Project overview

  • Read AGENTS.md, .github/copilot-instructions.md, README.md
  • Detect framework, version, tech stack
  • Identify build tools and quality tooling
  • Classify: legacy vs. modern, monolith vs. modular
  • Output: agents/evidence/analysis/overview.md

Phase 2: Architecture

  • Map directory structure (top 3 levels)
  • Identify architectural patterns (MVC, modules, services, repositories)
  • Detect multi-tenancy, queue system, caching
  • Count: models, controllers, services, jobs, commands
  • Output: agents/evidence/analysis/architecture/*.md

Phase 3: Data layer

  • List all models with their connections, tables, and key relationships
  • Map database schema: tables, foreign keys, indexes
  • Document multi-tenant split (which tables in which DB)
  • Output: agents/evidence/analysis/models/api-database.md, customer-database.md

Phase 4: Business domains

  • Identify domains from models, services, routes, and directory structure
  • For each domain: map models → services → controllers → jobs → events
  • Document business rules and data flows
  • Document inter-domain dependencies
  • Output: agents/evidence/analysis/domains/{domain}.md (one per domain)

Phase 5: API surface

  • List all endpoints with controller, request, resource, OpenAPI attributes
  • Document request/response contracts (field names, types, validation rules)
  • Map version differences (v1 vs v2)
  • Output: agents/evidence/analysis/api/endpoints-v1.md, endpoints-v2.md, contracts.md

Phase 6: Service map

  • List all services with purpose, key methods, and dependencies
  • Map service → repository → model relationships
  • Identify God services (too many responsibilities)
  • Output: agents/evidence/analysis/services/service-map.md

Phase 7: Module inventory (if modules exist)

  • List all modules with purpose
  • For each module: structure, public API, internal components, tests
  • Check for module-level agent docs
  • Output: agents/evidence/analysis/modules/{module}.md (one per module)

Phase 8: Infrastructure & testing

  • Docker setup, CI/CD pipelines, deployment
  • Test suites, coverage areas, test data strategy
  • Output: agents/evidence/analysis/architecture/infrastructure.md, agents/evidence/analysis/testing/test-map.md

Phase 9: Agent docs audit

  • List all existing docs in agents/reference/docs/, agents/settings/contexts/, module agents/
  • Check for outdated docs (reference deleted files/classes)
  • Identify undocumented areas
  • Check for stale roadmaps

Phase 10: Gap analysis & action plan

  • Modules without context docs → offer /context-create
  • Complex services without docs → offer /context-create
  • Existing docs that reference deleted code → offer /context-refactor
  • Stale roadmaps (all steps done) → suggest archiving

Integration with other skills

SkillHow it's used
project-docsRead existing docs before analyzing each area
module-managementDetect and inventory modules
context-createCreate/update context documents
feature-planningIdentify planned but undocumented features
agent-docs-writingAudit and maintain agent documentation
roadmap-managementReview roadmap status
api-endpointUnderstand endpoint structure for API analysis
databaseUnderstand schema and multi-tenancy for data layer analysis

Workflow

  1. Ask scope: Full analysis or specific area (e.g. only domains, only API)?
  2. Run phases incrementally — show findings after each phase, ask before continuing.
  3. Write files after each phase — don't batch all writing to the end.
  4. Ask before creating each file with numbered options:
    > 1. Create — {filename}
    > 2. Skip
    
  5. Update existing files if re-running analysis — don't create duplicates.

Output format

  1. Structured analysis document in agents/evidence/analysis/
  2. Tech stack inventory with versions and dependencies
  3. Architecture diagram or module map

Auto-trigger keywords

  • project analysis
  • codebase analysis
  • architecture analysis

Gotcha

  • Full project analysis can take several minutes — warn the user about the time investment.
  • Don't analyze parts of the codebase that the user hasn't asked about — respect scope.
  • Analysis documents go in agents/evidence/analysis/, not in .augment/.

Do NOT

  • Do NOT create analysis files without asking — always confirm each creation.
  • Do NOT modify existing code — this is analysis only.
  • Do NOT commit or push.
  • Do NOT overwhelm the user — present findings incrementally, one phase at a time.
  • Do NOT analyze third-party code in vendor/ or node_modules/.
  • Do NOT duplicate content that already exists in agents/reference/docs/ or agents/settings/contexts/ — reference it instead. Analysis files complement existing docs, they don't replace them.
Skill path
src/skills/project-analyzer/SKILL.md
Commit SHA
0adf49a8ae84
Repository license
MIT
Data collected