Dotforge learn-project
Scan project code to detect patterns, dependencies, and conventions. Propose domain rules based on what the code actually does.
git clone https://github.com/luiseiman/dotforge
T=$(mktemp -d) && git clone --depth=1 https://github.com/luiseiman/dotforge "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/learn-project" ~/.claude/skills/luiseiman-dotforge-learn-project && rm -rf "$T"
skills/learn-project/SKILL.mdLearn Project
Scan the current project's source code to detect patterns, classify tooling, and propose domain rules. Unlike
/forge domain extract (which reads dotforge's internal memory), this skill reads the CODE directly.
Step 1: Detect dependency files
Read whichever exist (skip missing):
— extractpackage.json
+dependencies
keysdevDependencies
— extractpyproject.toml
and[project.dependencies]
sections[tool.*]
— read all linesrequirements.txt
— extractgo.mod
blockrequire
— read all linesPodfile
— read all linesGemfile
/pom.xml
/build.gradle
— extract dependency declarationsbuild.gradle.kts
Collect a flat list of dependency names.
Step 2: Scan imports
Find the top 20 most-imported libraries across the codebase:
# Python grep -rh "^import \|^from " --include="*.py" . 2>/dev/null | sed 's/import //;s/from //;s/ .*//' | sort | uniq -c | sort -rn | head -20 # TypeScript/JavaScript grep -rh "from ['\"]" --include="*.ts" --include="*.tsx" --include="*.js" --include="*.jsx" . 2>/dev/null | sed "s/.*from ['\"]//;s/['\"].*//" | grep -v '^\.' | sort | uniq -c | sort -rn | head -20 # Go grep -rh "\"" --include="*.go" . 2>/dev/null | grep -E '^\s+"' | sed 's/.*"//;s/".*//' | sort | uniq -c | sort -rn | head -20 # Swift grep -rh "^import " --include="*.swift" . 2>/dev/null | sed 's/import //' | sort | uniq -c | sort -rn | head -20
Step 3: Scan project structure
# Directory structure (2 levels deep, ignore hidden/vendor) find . -maxdepth 2 -type d ! -path '*/\.*' ! -path '*/node_modules*' ! -path '*/.venv*' ! -path '*/vendor*' ! -path '*/__pycache__*' | sort # Config files present ls -1 .eslintrc* .prettierrc* ruff.toml pyproject.toml tsconfig.json biome.json jest.config* vitest.config* vite.config* webpack.config* Makefile Dockerfile docker-compose* .env.example 2>/dev/null
Step 4: Classify patterns
From Steps 1-3, classify into categories. Only report categories with HIGH CONFIDENCE (direct evidence in code):
ORM/Database:
- SQLAlchemy (import sqlalchemy, from sqlalchemy)
- Prisma (@prisma/client)
- TypeORM (import { Entity } from "typeorm")
- GORM (gorm.io/gorm)
- Supabase (@supabase/supabase-js, supabase-py)
- Raw SQL (psycopg2, pg, mysql2)
Auth:
- JWT (python-jose, jsonwebtoken, @auth/core)
- OAuth (authlib, passport, next-auth)
- Session-based (express-session, flask-session)
- Supabase Auth (@supabase/auth-helpers)
Test framework:
- pytest, vitest, jest, mocha, go test, XCTest
- Detect test directory: tests/, tests/, spec/, test/
Build system:
- Vite, webpack, esbuild, rollup, turbopack
- setuptools, poetry, hatch
- Make (Makefile targets)
API framework:
- FastAPI, Express, Koa, Fastify, Gin, Echo, Fiber
- REST vs GraphQL (detect graphql imports/schema files)
State management:
- Zustand, Redux, MobX, Recoil, Jotai
- SwiftUI @Observable, @State, @Binding
Deployment:
- Docker (Dockerfile, docker-compose)
- Serverless (serverless.yml, sam template)
- Cloud Run (app.yaml, cloudbuild.yaml)
- Vercel (vercel.json)
- VPS/SSH (grep shell scripts and CI for
/ssh
/scp
targeting a host — see Step 4b)rsync
Step 4b: Scan for remote-host usage (SSH/VPS)
Extract remote-host deployment info from shell scripts, Makefiles, and CI:
# Find ssh/scp/rsync invocations in project scripts and CI grep -rEn "(^|[^a-z])(ssh|scp|rsync) [^|&;]*(@|--[a-z-]+=)" \ --include="*.sh" --include="Makefile" --include="*.mk" \ --include="*.yml" --include="*.yaml" --include="*.toml" \ . 2>/dev/null | head -30 # Also check ~/.ssh/config for host aliases that might match the project test -f ~/.ssh/config && awk '/^Host /{h=$2} /HostName/{print h" -> "$2}' ~/.ssh/config 2>/dev/null
From the matches, extract:
- Host (alias from
or raw~/.ssh/config
)user@host - User (before
)@ - IdentityFile (from
or~/.ssh/config
flag in the command)-i - Remote path (argument after
in scp/rsync, or inside quoted remote command): - Command pattern (what
runs — deploy, restart, health check, log tail)ssh host '...'
If any match found, this project needs the
vps-ssh stack. Flag it in the proposal and generate .claude/rules/domain/infra.md with the extracted fields. NEVER paste private key content into the rule — only reference the IdentityFile path.
Naming conventions:
# Function naming: snake_case vs camelCase grep -rh "def [a-z]" --include="*.py" . 2>/dev/null | head -5 # snake_case grep -rh "function [a-z]" --include="*.ts" --include="*.js" . 2>/dev/null | head -5 # camelCase
Step 5: Present proposals
Show detected patterns grouped by category. For each, propose a domain rule:
═══ /forge learn — [project-name] ═══ Detected patterns (high confidence only): 1. ORM: SQLAlchemy 2.x (async sessions detected in 8 files) Proposed rule: .claude/rules/domain/orm-patterns.md Content: async session lifecycle, model conventions, migration patterns → Create? [approve/skip/edit] 2. Auth: Supabase Auth (auth-helpers in 4 files) Proposed rule: .claude/rules/domain/auth-flow.md Content: session management, RLS policies, token refresh → Create? [approve/skip/edit] 3. Testing: vitest (vitest.config.ts found, 23 test files) Proposed rule: .claude/rules/domain/testing.md Content: test patterns, mock conventions, coverage targets → Create? [approve/skip/edit] 4. Naming: snake_case (Python), camelCase (TypeScript) Proposed rule: .claude/rules/domain/naming.md Content: per-language conventions detected → Create? [approve/skip/edit]
Wait for user approval on each before creating files.
Step 6: Generate approved rules
For each approved proposal, create a rule file in
.claude/rules/domain/:
--- globs: "<relevant file patterns>" description: "<what this rule covers>" domain: "<project-name>" last_verified: "<today YYYY-MM-DD>" source: "/forge learn" --- # <Title> <Factual observations from the scan — imperative mood, concise>
Rules must be:
- Under 40 lines
- Factual (observed in code, not assumed)
- Actionable (tell Claude what to do, not what exists)
- English only
Step 7: Report summary
═══ Learn complete ═══ Scanned: <N> dependency files, <N> imports, <N> config files Detected: <N> patterns across <N> categories Created: <N> domain rules in .claude/rules/domain/ Skipped: <N> proposals Tip: run /forge domain extract to capture session-learned knowledge too.
What this skill does NOT do
- Does not read dotforge memory, errors, or agent memory (use
for that)/forge domain extract - Does not modify existing rules (only creates new ones in domain/)
- Does not run any code or install dependencies
- Does not guess — only reports patterns with direct evidence in the codebase