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functional-core-imperative-shell功能核心命令式外壳

Agent Skill

functional-core-imperative-shell 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

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来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:functional-core-imperative-shell(功能核心命令式外壳)
来源仓库:https://github.com/ed3dai/ed3d-plugins
仓库路径:skills/functional-core-imperative-shell
安装命令:
npx skills add https://github.com/ed3dai/ed3d-plugins --skill functional-core-imperative-shell
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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skills.shnpx skills
npx skills add https://github.com/ed3dai/ed3d-plugins --skill functional-core-imperative-shell

简介

FCIS 的三个规则:

  • 功能核心:仅限纯功能。除日志记录外没有 I/O。易于测试。
  • 命令式 Shell:仅 I/O 协调。最少的逻辑。呼叫核心。
  • 根据运行时行为对每个文件进行分类。仅类型文件、常量、桶、测试和生成的文件除外。
  • 当有疑问时:它可以在没有外部依赖的情况下运行吗? -> 功能核心。否则 -> 命令式外壳。
  • 日志记录例外:任何地方都允许记录器。通过无操作记录器进行单元测试。
  • 混合关注点 = 需要重构。提取、分离、分类。现在就做,不要稍后。
  • 每周安装量
  • 79
  • 存储库
  • ed3dai/ed3d-插件
  • GitHub 之星
  • 176
  • 第一次看到
  • 1 天前
  • 安全审计
  • Gen Agent Trust Hub 通行证
  • 套接字通行证
  • 斯尼克通行证

SKILL.md

Functional Core, Imperative Shell (FCIS)

Overview

Core principle: Separate pure business logic (Functional Core) from side effects (Imperative Shell). Pure functions go in one file, I/O operations in another.

Why this matters: Pure functions are trivial to test (no mocks needed). I/O code is isolated to thin shells. Bugs become structurally impossible when business logic has no side effects.

When to Use

Use FCIS when:

  • Writing any new code file
  • Refactoring existing code
  • Reviewing code for architectural decisions
  • Deciding where logic belongs

Trigger symptoms:

  • "Where should this function go?"
  • Creating a new file
  • Adding database calls to logic
  • Adding file I/O to calculations
  • Writing tests that need complex mocking

MANDATORY: File Classification

YOU MUST add pattern comment to every file containing runtime behavior:

// pattern: Functional Core
// pattern: Imperative Shell
// pattern: Mixed (needs refactoring)

If file genuinely cannot be separated (rare), document why:

// pattern: Mixed (unavoidable)
// Reason: [specific technical justification]
// Example: Performance-critical path where separating I/O causes unacceptable overhead

No file with runtime behavior without classification. If you create a file that contains functions, classes with methods, or orchestration logic without this comment, you have violated the requirement.

Exempt: Files Without Runtime Behavior

DO NOT add pattern comments to:

  • Type-only files - files exporting only types, interfaces, or type aliases (no runtime code)
  • Constants/enum-like files - static data declarations, no functions
  • Barrel/index files - re-exports only (export * from './foo')
  • Test files - tests exercise core/shell code but aren't themselves core or shell
  • Generated files - machine-generated code
  • Bash/shell scripts (.sh,.bash) - inherently imperative
  • Configuration files (eslint.config.js, tsconfig.json,.env, etc.)
  • Markdown documentation (.md)
  • HTML files (.html)
  • Task runner files (justfile, Makefile, etc.)
  • Package manifests (package.json, pyproject.toml, etc.)
  • Data files (JSON, YAML, CSV, etc.)

Note: If an exempt file grows to include runtime logic (e.g., a "types" file gains helper functions, or a constants file gains factory functions), it crosses the threshold and MUST be classified.

Classification applies to application source files containing runtime behavior (functions with logic, classes with methods, I/O orchestration).

File Type Definitions

Functional Core Files

Contains ONLY:

  • Pure functions (same input -> same output, always)
  • Business logic, validations, calculations, transformations
  • Data structure operations
  • Logging (EXCEPTION: loggers are permitted in Functional Core)

NEVER contains:

  • File I/O (reading, writing files)
  • Database operations (queries, updates, connections)
  • HTTP requests or responses
  • Environment variable access
  • Date.now(), Math.random(), or other non-deterministic functions
  • State mutations outside function scope

Logging exception: Functions MAY accept and use loggers. For unit tests, pass no-op loggers. This is the ONLY permitted side effect in Functional Core.

Test signature: Simple assertions, no mocks except logger (if used).

Imperative Shell Files

Contains ONLY:

  • I/O operations: file system, database, HTTP, environment
  • Orchestration: gather data -> call Functional Core -> persist results
  • Error handling for I/O failures
  • Minimal business logic (coordination only)

NEVER contains:

  • Complex calculations
  • Business rule validations
  • Data transformations beyond format conversion

Test signature: Integration tests with real dependencies or test doubles.

Code Flow Pattern

1. GATHER (Shell):  Collect data from external sources
2. PROCESS (Core):  Transform input to output (pure)
3. PERSIST (Shell): Save results externally

Every operation follows this sequence. No exceptions.

Decision Framework

Before writing a function, ask:

digraph fcis_decision {
    "Writing a function" [shape=ellipse];
    "Can run without external dependencies?" [shape=diamond];
    "Does it coordinate I/O?" [shape=diamond];
    "Functional Core" [shape=box, style=filled, fillcolor=lightblue];
    "Imperative Shell" [shape=box, style=filled, fillcolor=lightgreen];
    "STOP: Refactor or escalate" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];

    "Writing a function" -> "Can run without external dependencies?";
    "Can run without external dependencies?" -> "Functional Core" [label="yes"];
    "Can run without external dependencies?" -> "Does it coordinate I/O?" [label="no"];
    "Does it coordinate I/O?" -> "Imperative Shell" [label="yes"];
    "Does it coordinate I/O?" -> "STOP: Refactor or escalate" [label="no"];
}

Questions to ask:

  • Can this logic run without file system, database, network, or environment?

- YES -> Functional Core - NO -> Does it coordinate I/O or contain business logic? - I/O coordination -> Imperative Shell - Business logic + I/O -> STOP. Refactor or escalate to user.

Common Mistakes and Rationalizations

Excuse/Thought PatternRealityWhat To Do
"Just one file read in this calculation"File I/O = side effect. Not Functional Core.Extract to Shell. Pass data as parameter.
"Database is passed as parameter, so it's pure"Database operations are I/O. Not pure.Move to Shell. Core receives data, not DB connection.
"This validation needs to check if file exists"File system check = I/O. Not Functional Core.Shell checks file, passes boolean to Core validation.
"Small HTTP call, won't hurt"HTTP = side effect. Breaks purity guarantee.Shell makes request, Core processes response data.
"Need Date.now() for timestamp calculation"Non-deterministic. Not pure.Shell passes timestamp as parameter.
"Logging is a side effect, should remove"WRONG. Logging is explicitly permitted.Keep logger. This is the exception.
"This function does both logic and I/O, but it's simpler"Mixed concerns = untestable without mocks.Split into Core (logic) + Shell (I/O). Test Core simply.
"File classification is overhead"Prevents entire classes of bugs. Non-negotiable.Add classification comment. Takes 10 seconds.
"I'll refactor later"Later never comes. Do it now.Classify and separate now.
"Performance requires mixing"Prove it with benchmarks. Usually wrong.Separate first. Optimize with evidence. Mark Mixed (unavoidable) with justification.

Red Flags - STOP and Refactor

If you catch yourself doing ANY of these, STOP:

  • File I/O in a "pure" function (open, read, write, exists checks)
  • Database passed as parameter to Functional Core (queries, updates, connections)
  • HTTP requests in business logic (fetch, axios, requests)
  • Environment variables in calculations (process.env, os.getenv)
  • Math.random() or Date.now() in Functional Core (non-deterministic)
  • Creating a file with runtime behavior without pattern classification comment
  • Thinking "just this once" about mixing concerns

All of these mean: Extract I/O to Shell. Pass data to Core. Classify file correctly.

Implementation Patterns

Functional Core Pattern

# pattern: Functional Core

def calculate_total_with_tax(items, tax_rate, logger=None):
    """Pure calculation: same inputs always produce same output."""
    if logger:
        logger.debug(f"Calculating total for {len(items)} items")

    subtotal = sum(item['price'] * item['quantity'] for item in items)
    tax = subtotal * tax_rate
    total = subtotal + tax

    return {
        'subtotal': subtotal,
        'tax': tax,
        'total': total
    }

No I/O. No database. No file system. Only computation.

Imperative Shell Pattern

# pattern: Imperative Shell

def process_order(order_id, db, logger):
    """Orchestrates: gather -> process -> persist."""

    # GATHER: Collect data from external sources
    items = db.get_order_items(order_id)
    tax_rate = db.get_tax_rate_for_order(order_id)

    # PROCESS: Call Functional Core (pure logic)
    result = calculate_total_with_tax(items, tax_rate, logger)

    # PERSIST: Save results externally
    db.update_order_total(order_id, result['total'])

    return result

Shell is thin. Core does heavy lifting. Testable separately.

Mixed (Needs Refactoring) - Bad Example

# pattern: Mixed (needs refactoring)

def calculate_and_save_total(order_id, db):
    """BAD: Mixes calculation with I/O. Hard to test."""
    items = db.get_order_items(order_id)  # I/O
    subtotal = sum(item['price'] for item in items)  # Logic
    tax_rate = db.get_tax_rate_for_order(order_id)  # I/O
    tax = subtotal * tax_rate  # Logic
    total = subtotal + tax  # Logic
    db.update_order_total(order_id, total)  # I/O
    return total

Testing this requires database mocks. Fragile. Refactor using patterns above.

Logger Exception Details

Loggers are EXPLICITLY PERMITTED in Functional Core.

# pattern: Functional Core

def validate_order(order_data, logger=None):
    """Pure validation with logging."""
    if logger:
        logger.info(f"Validating order {order_data.get('id')}")

    errors = []

    if not order_data.get('items'):
        errors.append("Order must have items")

    if order_data.get('total', 0) < 0:
        errors.append("Total cannot be negative")

    if logger and errors:
        logger.warning(f"Validation failed: {errors}")

    return {'valid': len(errors) == 0, 'errors': errors}

For unit tests: Pass no-op logger or None. Function remains pure for testing.

Refactoring Patterns

Common patterns for separating concerns:

Extract Pure Core from Impure Functions

Symptom: Function mixes I/O with logic

# BEFORE - hard to test
def process_order(order_id: str) -> None:
    order = db.fetch(order_id)           # I/O
    discount = calculate_discount(order)  # Pure logic
    total = apply_discount(order, discount)  # Pure logic
    db.save(order_id, total)             # I/O

# AFTER - pure core extracted
def calculate_order_total(order: Order, rules: DiscountRules) -> Decimal:
    """Pure function - easy to test."""
    discount = calculate_discount(order, rules)
    return apply_discount(order, discount)

def process_order(order_id: str) -> None:
    """Thin I/O wrapper."""
    order = db.fetch(order_id)
    total = calculate_order_total(order, get_discount_rules())
    db.save(order_id, total)

Return Values Instead of Mutating

Symptom: Methods mutate in place, making before/after comparison hard

# BEFORE - mutation
def sort_tasks(tasks: list[Task]) -> None:
    tasks.sort(key=lambda t: t.priority)

# AFTER - returns new value
def sorted_tasks(tasks: list[Task]) -> list[Task]:
    return sorted(tasks, key=lambda t: t.priority)

Add Missing Inverse Operations

Symptom: One-way operation exists but no inverse for testing roundtrips

# BEFORE - only encode exists
def encode_message(msg: dict) -> bytes:
    return msgpack.packb(msg)

# AFTER - add decode for roundtrip testing
def decode_message(data: bytes) -> dict:
    return msgpack.unpackb(data)

Replace Hardcoded Dependencies

Symptom: Functions use globals or hardcoded config, can't test edge cases

# BEFORE - uses global
def validate_input(data: str) -> bool:
    return len(data) <= CONFIG.max_length

# AFTER - dependency injected
def validate_input(data: str, max_length: int) -> bool:
    return len(data) <= max_length

Refactoring Priority

PatternImpactEffortPriority
Extract pure coreHIGHMediumDo first
Add missing inverseHIGHLowQuick win
Return instead of mutateMEDIUMLowEasy improvement
Inject dependenciesMEDIUMMediumWhen testing blocked

Refactoring Checklist

When you find mixed concerns:

  • Identify pure computations (logic, calculations, validations)
  • Extract pure code to Functional Core file
  • Identify I/O operations (file, database, HTTP, environment)
  • Keep I/O in Imperative Shell file
  • Shell gathers data, calls Core, persists results
  • Add pattern classification comments to both files
  • Test Core with simple assertions (no mocks except logger)
  • Test Shell with integration tests

If you cannot separate: Escalate to user with specific technical justification. Don't assume mixed is necessary.

Summary

FCIS in three rules:

  1. Functional Core: Pure functions only. No I/O except logging. Easy to test.
  2. Imperative Shell: I/O coordination only. Minimal logic. Calls Core.
  3. Classify every file with runtime behavior. Type-only files, constants, barrels, tests, and generated files are exempt.

When in doubt: Can it run without external dependencies? -> Functional Core. Otherwise -> Imperative Shell.

Logging exception: Loggers permitted everywhere. Pass no-op logger for unit tests.

Mixed concerns = refactoring needed. Extract, separate, classify. Do it now, not later.

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平台分布

Codex

34.58%
按下载量换算212

Claude

29.96%
按下载量换算184

Cursor

19.38%
按下载量换算119

Gemini CLI

9.31%
按下载量换算57

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