Fp Pipe Ref

pipe & flow Quick Reference

pipe - Transform a Value

import { pipe } from 'fp-ts/function'

// pipe(startValue, fn1, fn2, fn3)
// = fn3(fn2(fn1(startValue)))

const result = pipe(
  '  hello world  ',
  s => s.trim(),
  s => s.toUpperCase(),
  s => s.split(' ')
)
// ['HELLO', 'WORLD']

flow - Create Reusable Pipeline

import { flow } from 'fp-ts/function'

// flow(fn1, fn2, fn3) returns a new function
const process = flow(
  (s: string) => s.trim(),
  s => s.toUpperCase(),
  s => s.split(' ')
)

process('  hello world  ') // ['HELLO', 'WORLD']
process('  foo bar  ')     // ['FOO', 'BAR']

When to Use

With fp-ts Types

import * as O from 'fp-ts/Option'
import * as A from 'fp-ts/Array'

// Option chain
pipe(
  O.fromNullable(user),
  O.map(u => u.email),
  O.getOrElse(() => 'no email')
)

// Array chain
pipe(
  users,
  A.filter(u => u.active),
  A.map(u => u.name)
)

Common Pattern

// Data last enables partial application
const getActiveNames = flow(
  A.filter((u: User) => u.active),
  A.map(u => u.name)
)

// Reuse anywhere
getActiveNames(users1)
getActiveNames(users2)

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior design decisions (color palettes, typography, spacing scales) to maintain visual consistency across sessions. Cache generated design tokens.

# Check for prior frontend/design context before starting
python3 execution/memory_manager.py auto --query "design system decisions and component patterns for Fp Pipe Ref"

Storing Results

After completing work, store frontend/design decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Design system: adopted 8px grid, Inter font family, HSL color tokens with dark mode support" \
  --type decision --project <project> \
  --tags fp-pipe-ref frontend

Multi-Agent Collaboration

Share design decisions with backend agents (API contract changes) and QA agents (visual regression baselines).

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Implemented UI components — new design system with accessibility compliance (WCAG 2.1 AA)" \
  --project <project>

Design Memory Persistence

Store design system tokens and component decisions in Qdrant so any agent on any platform (Claude, Gemini, Cursor) can retrieve and apply consistent styling.