skill-resiliency

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Skill Resiliency

Skill 弹性设计

Overview

概述

This skill applies Michael Levin's biological resiliency principles to Agent Skills design. It provides a framework for building robust, self-correcting skills that maintain goal-directed behavior despite perturbations, with resiliency mechanisms scaled proportionally to the skill's determinism requirements.

Core Principle: The degree of resiliency in a skill should be positively correlated with its determinism. More deterministic skills (those requiring precise, repeatable outcomes) need stronger resiliency mechanisms to maintain their target behavior.

Inspired by: Michael Levin's research on anatomical homeostasis, error correction in biological systems, and collective intelligence in cellular networks.

本技能将Michael Levin的生物弹性原则应用于Agent Skill设计。它提供了一个框架，用于构建健壮、可自纠正的技能，这些技能即使在受到干扰时也能保持目标导向的行为，且弹性机制的规模与Skill的determinism要求成正比。

核心原则： Skill的弹性程度应与其determinism呈正相关。determinism更高的Skill（即需要精准、可重复结果的Skill）需要更强的弹性机制来维持其目标行为。

灵感来源： Michael Levin关于解剖学稳态（anatomical homeostasis）、生物系统中的错误纠正以及细胞网络中的集体智能的研究。

When to Use This Skill

适用场景

Apply resiliency patterns when:

Creating skills that require deterministic outcomes
Building skills with complex multi-step workflows
Designing skills that interact with external systems or tools
Improving existing skills that fail under edge cases
Developing skills for critical operations (deployment, data processing, security)

Resiliency Level Guide:

High Determinism (scripts, automation, data validation) → High Resiliency (extensive validation, recovery, monitoring)
Medium Determinism (structured workflows, domain guidance) → Medium Resiliency (checkpoint validation, error detection)
Low Determinism (creative tasks, exploration, ideation) → Low Resiliency (minimal constraints, flexible adaptation)

在以下场景中应用弹性模式：

创建需要determinism输出的Skill
构建具有复杂多步骤工作流的Skill
设计与外部系统或工具交互的Skill
改进在边缘情况下会失败的现有Skill
为关键操作（部署、数据处理、安全）开发Skill

弹性级别指南：

高Determinism（脚本、自动化、数据验证）→ 高弹性（全面验证、恢复、监控）
中Determinism（结构化工作流、领域引导）→ 中弹性（Checkpoint验证、错误检测）
低Determinism（创意任务、探索、构思）→ 低弹性（最小约束、灵活适配）

Biological Resiliency Principles

生物弹性原则

Michael Levin's research reveals how biological systems achieve remarkable robustness through:

Michael Levin的研究揭示了生物系统如何通过以下机制实现卓越的健壮性：

1. Anatomical Homeostasis

1. 解剖学稳态（Anatomical Homeostasis）

Biological systems actively maintain target morphology by continuously reducing error. Example: salamander limb regeneration stops when (and only when) a "correct salamander limb" is complete.

Applied to Skills: Skills should define clear success criteria and include mechanisms to validate progress toward those goals.

生物系统通过持续减少误差来主动维持目标形态。示例：蝾螈肢体再生仅在（且仅当）一个「正确的蝾螈肢体」完全形成时才会停止。

Skill应用： Skill应定义清晰的成功标准，并包含验证目标进展的机制。

2. Error Correction

2. 错误纠正

Systems activate effectors at multiple scales to reduce error relative to target states. Cells coordinate to repair damage and restore function.

Applied to Skills: Skills should include validation checkpoints that detect deviations from expected states and trigger corrective actions.

系统会在多个尺度上激活效应器，以减少与目标状态的误差。细胞协同工作以修复损伤并恢复功能。

Skill应用： Skill应包含验证检查点，用于检测与预期状态的偏差并触发纠正操作。

3. Robustness Through Collective Intelligence

3. 基于集体智能的健壮性

Cell swarms exhibit both robustness (reliable outcomes) and plasticity (multiple valid paths). The system is resilient to perturbations while exploring solution space.

Applied to Skills: Skills should define required outcomes while allowing flexibility in implementation paths. Multiple approaches can achieve the same validated result.

细胞群既表现出健壮性（可靠的结果）又表现出可塑性（多种有效路径）。系统在探索解决方案空间的同时，能抵御干扰。

Skill应用： Skill应定义所需的输出结果，同时允许实现路径的灵活性。多种方法可以达成相同的验证结果。

4. Goal-Directed Behavior

4. 目标导向行为

Biological systems work toward specific outcomes across timescales, using feedback loops to navigate toward target states despite noise and variation.

Applied to Skills: Skills should specify goals explicitly and provide feedback mechanisms to assess progress and adjust course.

生物系统会在不同时间尺度上朝着特定结果努力，利用反馈回路在噪声和变化中导航至目标状态。

Skill应用： Skill应明确指定目标，并提供反馈机制以评估进展和调整方向。

Resiliency Design Framework

弹性设计框架

Step 1: Assess Determinism Requirements

步骤1：评估Determinism要求

Classify your skill's determinism level:

High Determinism Indicators:

Executes scripts or automated processes
Modifies production systems or data
Requires specific file formats or structures
Depends on external tool outputs
Has compliance or security requirements
Must produce bit-perfect reproducible results

Medium Determinism Indicators:

Follows structured workflows with clear phases
Creates artifacts with defined schemas
Interacts with version control or APIs
Requires validation of intermediate states
Has quality gates or checkpoints

Low Determinism Indicators:

Explores problem space creatively
Generates ideas or content
Provides guidance without strict structure
Adapts to user preferences dynamically
Has subjective success criteria

对Skill的determinism级别进行分类：

高Determinism指标：

执行脚本或自动化流程
修改生产系统或数据
需要特定的文件格式或结构
依赖外部工具的输出
有合规或安全要求
必须生成完全可重复的结果

中Determinism指标：

遵循具有清晰阶段的结构化工作流
创建具有定义好的 schema 的工件
与版本控制或API交互
需要验证中间状态
有质量门或检查点

低Determinism指标：

创造性地探索问题空间
生成想法或内容
提供无严格结构的指导
动态适应用户偏好
有主观的成功标准

Step 2: Design Resiliency Mechanisms

步骤2：设计弹性机制

Based on determinism level, implement appropriate resiliency patterns:

根据determinism级别，实施相应的弹性模式：

High Determinism Skills: Comprehensive Resiliency

高Determinism Skill：全面弹性

Pre-Execution Validation:

Validate all inputs against schemas
Check preconditions (file existence, permissions, dependencies)
Verify tool availability and versions
Create backup/snapshot points
Document expected state

Execution Monitoring:

Validate each step's output before proceeding
Log state transitions and decisions
Implement retry mechanisms with exponential backoff
Set timeouts for external operations
Capture error context for debugging

Post-Execution Verification:

Verify final output against success criteria
Run test suites or validation scripts
Check system state consistency
Generate execution report
Provide rollback instructions if validation fails

Recovery Procedures:

Include explicit rollback steps
Document manual recovery procedures
Provide diagnostic scripts
Log all state changes for audit trail

Example Structure:

high-determinism-skill/
├── SKILL.md                    # Core workflow with validation checkpoints
├── scripts/
│   ├── validate-input.py      # Pre-execution validation
│   ├── verify-output.py       # Post-execution verification
│   └── rollback.sh            # Recovery procedure
├── references/
│   ├── schemas.md             # Input/output schemas
│   └── recovery-guide.md      # Detailed recovery procedures
└── examples/
    └── validated-workflow.md  # Example with all checkpoints

执行前验证：

根据schema验证所有输入
检查前置条件（文件存在性、权限、依赖项）
验证工具的可用性和版本
创建备份/快照点
记录预期状态

执行监控：

在进行下一步之前验证每个步骤的输出
记录状态转换和决策
实现带指数退避的重试机制
为外部操作设置超时
捕获错误上下文以用于调试

执行后验证：

根据成功标准验证最终输出
运行测试套件或验证脚本
检查系统状态的一致性
生成执行报告
如果验证失败，提供回滚说明

恢复流程：

包含明确的回滚步骤
记录手动恢复流程
提供诊断脚本
记录所有状态变更以用于审计追踪

示例结构：

high-determinism-skill/
├── SKILL.md                    # 包含验证检查点的核心工作流
├── scripts/
│   ├── validate-input.py      # 执行前验证
│   ├── verify-output.py       # 执行后验证
│   └── rollback.sh            # 恢复流程
├── references/
│   ├── schemas.md             # 输入/输出 schema
│   └── recovery-guide.md      # 详细恢复流程
└── examples/
    └── validated-workflow.md  # 包含所有检查点的示例

Medium Determinism Skills: Balanced Resiliency

中Determinism Skill：平衡弹性

Checkpoint Validation:

Define phase boundaries with clear exit criteria
Validate artifacts at checkpoints
Provide status summaries
Enable phase restart without full restart

Error Detection:

Identify common failure modes
Provide clear error messages with context
Suggest corrective actions
Document troubleshooting steps

State Management:

Create summary files tracking progress
Enable resumption from checkpoints
Document current state clearly
Track key decisions

Example Structure:

medium-determinism-skill/
├── SKILL.md                        # Workflow with checkpoints
├── scripts/
│   └── validate-checkpoint.sh     # Phase validation
├── references/
│   └── troubleshooting.md         # Common issues and fixes
└── examples/
    └── checkpoint-workflow.md     # Example with phase validation

Checkpoint验证：

定义具有清晰退出标准的阶段边界
在Checkpoint验证工件
提供状态摘要
支持无需完全重启的阶段重启

错误检测：

识别常见故障模式
提供带有上下文的清晰错误消息
建议纠正措施
记录故障排除步骤

状态管理：

创建跟踪进度的摘要文件
支持从Checkpoint恢复
清晰记录当前状态
跟踪关键决策

示例结构：

medium-determinism-skill/
├── SKILL.md                        # 包含Checkpoint的工作流
├── scripts/
│   └── validate-checkpoint.sh     # 阶段验证
├── references/
│   └── troubleshooting.md         # 常见问题与修复方案
└── examples/
    └── checkpoint-workflow.md     # 包含阶段验证的示例

Low Determinism Skills: Minimal Resiliency

低Determinism Skill：最小弹性

Guidance and Constraints:

Provide principles, not procedures
Suggest rather than prescribe
Enable exploration within bounds
Document anti-patterns to avoid

Adaptive Feedback:

Ask for user feedback on direction
Offer multiple valid approaches
Adjust based on user preferences
Validate satisfaction, not output

Example Structure:

low-determinism-skill/
├── SKILL.md                    # Principles and guidance
└── references/
    └── examples.md            # Diverse example approaches

指导与约束：

提供原则而非流程
建议而非规定
允许在边界内探索
记录需要避免的反模式

自适应反馈：

询问用户对方向的反馈
提供多种有效方法
根据用户偏好调整
验证满意度而非输出

示例结构：

low-determinism-skill/
├── SKILL.md                    # 原则与指导
└── references/
    └── examples.md            # 多样化示例方法

Step 3: Implement Feedback Loops

步骤3：实现反馈回路

Design homeostatic feedback mechanisms appropriate to determinism level:

For High Determinism:

Automated validation at each step
Fail-fast on validation errors
Required checkpoints before proceeding
Automated rollback on critical failures

For Medium Determinism:

Explicit user confirmation at phase boundaries
Validation with override capability
Warning system for potential issues
Manual recovery guidance

For Low Determinism:

Periodic progress checks
User satisfaction validation
Flexible adaptation to feedback
Optional validation only

设计与determinism级别相适应的稳态反馈机制：

高Determinism场景：

每个步骤的自动验证
验证失败时快速终止
进行下一步前必须通过Checkpoint
关键失败时自动回滚

中Determinism场景：

阶段边界处的明确用户确认
带有覆盖权限的验证
潜在问题的警告系统
手动恢复指导

低Determinism场景：

定期进度检查
用户满意度验证
根据反馈灵活调整
仅可选验证

Step 4: Document Target States

步骤4：记录目标状态

Clearly define success criteria and target states:

For Scripts and Automation:

Exact file structures, formats, schemas
Required tool versions and configurations
Expected output patterns
Performance criteria (timeouts, resource limits)

For Workflows:

Deliverables for each phase
Quality criteria for artifacts
Integration points and dependencies
Completion criteria

For Guidance Skills:

Principles to follow
Anti-patterns to avoid
Subjective quality indicators
User satisfaction metrics

明确定义成功标准和目标状态：

脚本与自动化场景：

精确的文件结构、格式、schema
所需的工具版本和配置
预期的输出模式
性能标准（超时、资源限制）

工作流场景：

每个阶段的交付物
工件的质量标准
集成点和依赖项
完成标准

指导类Skill场景：

需遵循的原则
需要避免的反模式
主观质量指标
用户满意度指标

Implementation Patterns

实现模式

Pattern 1: The Validation Checkpoint

模式1：验证Checkpoint

Insert validation checkpoints at critical boundaries:

markdown

undefined

在关键边界处插入验证Checkpoint：

markdown

undefined

Phase 1: Initialize

阶段1：初始化

[Instructions for phase 1]

Validation Checkpoint: Before proceeding to Phase 2, verify:

Input file exists and is readable
Required tools are available (version >= X.Y)
Output directory has write permissions
No conflicting processes running

Run

scripts/validate-phase1.sh

to check all conditions.

If validation fails, see

references/troubleshooting.md

Section 1.

undefined

[阶段1说明]

验证Checkpoint： 进入阶段2之前، 需验证：

输入文件存在且可读
所需工具可用（版本 >= X.Y）
输出目录有写入权限
无冲突进程在运行

运行

scripts/validate-phase1.sh

检查所有条件。

如果验证失败，请参阅

references/troubleshooting.md

第1节。

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Pattern 2: The Self-Correcting Loop

模式2：自纠正回路

Implement error detection and correction:

markdown

undefined

实现错误检测与纠正：

markdown

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Step 3: Process Data

步骤3：处理数据

Process the input file using the following approach:

Load and validate input schema
Transform data according to rules
Validation: Check output against schema
If validation fails:
- Log specific validation errors
- Attempt automatic correction (see
```
scripts/auto-correct.py
```
  )
- If auto-correction fails, provide manual fix guidance
- Retry validation after fixes
Proceed only after validation passes

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使用以下方法处理输入文件：

加载并验证输入schema
根据规则转换数据
验证： 检查输出是否符合schema
如果验证失败：
- 记录具体的验证错误
- 尝试自动纠正（参见
```
scripts/auto-correct.py
```
  ）
- 如果自动纠正失败，提供手动修复指导
- 修复后重新验证
仅在验证通过后继续

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Pattern 3: The Resilient Script

模式3：弹性脚本

For skills that bundle scripts, add resiliency directly:

python

#!/usr/bin/env python3
"""
Resilient data processor with built-in validation and error handling.
"""

def validate_input(data):
    """Pre-execution validation."""
    # Check schema, types, ranges, etc.
    if not meets_criteria(data):
        raise ValueError("Input validation failed: [specific error]")

def process_with_retry(data, max_retries=3):
    """Process with exponential backoff retry."""
    for attempt in range(max_retries):
        try:
            result = process(data)
            if validate_output(result):
                return result
            else:
                log_warning(f"Output validation failed on attempt {attempt + 1}")
        except Exception as e:
            if attempt == max_retries - 1:
                raise
            wait_time = 2 ** attempt
            log_info(f"Retry in {wait_time}s after error: {e}")
            time.sleep(wait_time)

def validate_output(result):
    """Post-execution validation."""
    # Verify result meets success criteria
    return meets_success_criteria(result)

对于捆绑脚本的Skill，直接添加弹性机制：

python

#!/usr/bin/env python3
"""
Resilient data processor with built-in validation and error handling.
"""

def validate_input(data):
    """Pre-execution validation."""
    # Check schema, types, ranges, etc.
    if not meets_criteria(data):
        raise ValueError("Input validation failed: [specific error]")

def process_with_retry(data, max_retries=3):
    """Process with exponential backoff retry."""
    for attempt in range(max_retries):
        try:
            result = process(data)
            if validate_output(result):
                return result
            else:
                log_warning(f"Output validation failed on attempt {attempt + 1}")
        except Exception as e:
            if attempt == max_retries - 1:
                raise
            wait_time = 2 ** attempt
            log_info(f"Retry in {wait_time}s after error: {e}")
            time.sleep(wait_time)

def validate_output(result):
    """Post-execution validation."""
    # Verify result meets success criteria
    return meets_success_criteria(result)

Pattern 4: The Homeostatic Summary

模式4：稳态摘要

Maintain state awareness through summary files:

markdown

undefined

通过摘要文件保持状态感知：

markdown

undefined

summary.md Template

summary.md 模板

status: in-progress # or: completed, blocked, failed phase: execution determinism: high # high, medium, low last-validated: 2026-01-07T15:30:00Z

status: in-progress # 或: completed, blocked, failed phase: execution determinism: high # high, medium, low last-validated: 2026-01-07T15:30:00Z

Execution Summary

执行摘要

Current State

当前状态

Currently executing Phase 2 of 4. Last checkpoint passed at 15:25.

当前正在执行4个阶段中的第2阶段。最后一个Checkpoint在15:25通过。

Validations Passed

已通过的验证

✅ Input validation (15:20)
✅ Phase 1 completion (15:25)
⏳ Phase 2 in progress

✅ 输入验证（15:20）
✅ 阶段1完成（15:25）
⏳ 阶段2进行中

Known Issues

已知问题

None

无

Next Checkpoint

下一个Checkpoint

Phase 2 validation at step 5

步骤5的阶段2验证

Rollback Point

回滚点

Can rollback to Phase 1 completion using

scripts/rollback.sh phase1

undefined

可以使用

scripts/rollback.sh phase1

回滚到阶段1完成状态

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Resiliency Checklist by Determinism Level

按Determinism级别划分的弹性检查清单

High Determinism Checklist

高Determinism检查清单

Medium Determinism Checklist

中Determinism检查清单

Low Determinism Checklist

低Determinism检查清单

Anti-Patterns to Avoid

需要避免的反模式

Over-Engineering Low Determinism Skills

过度设计低Determinism Skill

Wrong: Adding extensive validation to creative or exploratory skills. Right: Provide principles and guidance, allow flexibility.

错误做法： 为创意或探索性Skill添加大量验证。 正确做法： 提供原则和指导，允许灵活性。

Under-Engineering High Determinism Skills

设计不足的高Determinism Skill

Wrong: Assuming scripts will work without validation. Right: Validate inputs, outputs, and intermediate states comprehensively.

错误做法： 假设脚本无需验证就能正常工作。 正确做法： 全面验证输入、输出和中间状态。

Silent Failures

静默失败

Wrong: Continuing execution after validation failures without alerting. Right: Fail fast and provide clear error context.

错误做法： 验证失败后仍继续执行而不发出警报。 正确做法： 快速终止并提供清晰的错误上下文。

Validation Without Recovery

仅验证无恢复

Wrong: Detecting errors but providing no path forward. Right: Include recovery procedures or rollback instructions for all validation failures.

错误做法： 检测到错误但不提供前进路径。 正确做法： 为所有验证失败情况包含恢复流程或回滚说明。

False Homeostasis

伪稳态

Wrong: Checking that "something happened" without verifying it's correct. Right: Validate against explicit success criteria, not just completion.

错误做法： 仅检查「有事情发生」而不验证其正确性。 正确做法： 根据明确的成功标准进行验证，而非仅检查完成情况。

Testing Resiliency

弹性测试

Validate your skill's resiliency by testing:

Failure Modes:

Missing files or dependencies
Invalid inputs
Interrupted execution
Tool failures or timeouts
Partial completion scenarios

Recovery Paths:

Rollback procedures work correctly
Checkpoints enable restart
Error messages are actionable
Recovery scripts function as documented

Validation Effectiveness:

False positives (flagging valid states as errors)
False negatives (missing actual errors)
Validation coverage (all critical states checked)

通过测试以下内容来验证Skill的弹性：

故障模式：

缺失文件或依赖项
无效输入
执行中断
工具故障或超时
部分完成场景

恢复路径：

回滚流程正常工作
Checkpoint支持重启
错误消息可操作
恢复脚本如文档所述运行

验证有效性：

误报（将有效状态标记为错误）
漏报（遗漏实际错误）
验证覆盖范围（所有关键状态均已检查）

Additional Resources

额外资源

Reference Files

参考文件

For deeper understanding of resiliency concepts:

references/levin-principles.md
- Michael Levin's biological resiliency principles in detail
references/determinism-assessment.md
- Comprehensive guide to assessing skill determinism
references/validation-patterns.md
- Extensive validation pattern library

如需深入了解弹性概念：

references/levin-principles.md
- 详细介绍Michael Levin的生物弹性原则
references/determinism-assessment.md
- 评估Skill determinism的综合指南
references/validation-patterns.md
- 丰富的验证模式库

Example Files

示例文件

Working examples demonstrating resiliency levels:

examples/high-determinism-deployment.md
- Deployment skill with full resiliency
examples/medium-determinism-workflow.md
- Workflow skill with checkpoints
examples/low-determinism-creative.md
- Creative skill with minimal constraints

展示弹性级别的工作示例：

examples/high-determinism-deployment.md
- 具有全面弹性的部署Skill
examples/medium-determinism-workflow.md
- 带有Checkpoint的工作流Skill
examples/low-determinism-creative.md
- 具有最小约束的创意Skill

Scripts

脚本

Utility scripts for implementing resiliency:

scripts/generate-validation.py
- Generate validation scripts from schemas
scripts/test-resiliency.sh
- Test skill under failure conditions

Remember: Resiliency is not about preventing all failures—it's about detecting deviations from target states and providing pathways to correction. Match resiliency mechanisms to determinism requirements: over-engineering adds friction, under-engineering invites failure.

用于实现弹性的实用脚本：

scripts/generate-validation.py
- 从schema生成验证脚本
scripts/test-resiliency.sh
- 在故障条件下测试Skill

注意： 弹性并非要防止所有故障——而是要检测与目标状态的偏差并提供纠正路径。使弹性机制与determinism要求相匹配：过度设计会增加摩擦，设计不足会导致故障。