[Skill Name] Evolution Rules

Domain-specific self-improvement rules for [skill-name]. Log learnings and errors to .learnings/; promote proven patterns to the targets below. Evolution is driven by user feedback.

Quick Reference

Situation	Action
{LEARNING_TRIGGER_1}	Log to `.learnings/LEARNINGS.md` with category `correction` or `style_mismatch`
{LEARNING_TRIGGER_2}	Log to `.learnings/LEARNINGS.md`
{ERROR_TRIGGER_1}	Log to `.learnings/ERRORS.md`
{ERROR_TRIGGER_2}	Log to `.learnings/ERRORS.md`
User wants missing capability	Log to `.learnings/FEATURE_REQUESTS.md`
Pattern proven across 3+ instances	Promote to {PROMOTION_TARGET_1}
Safety/correctness rule	Promote to {PROMOTION_TARGET_2}

Review → Apply → Report Loop

Before task: Load relevant entries from .learnings/LEARNINGS.md (and ERRORS.md if applicable). Filter by area, tags, or keywords.

During task: Apply learnings when relevant. Optionally annotate: "本次参考了 [LRN-xxx]: ..." (or equivalent in target language).

After task: Tell user which learnings were used, what evolution result, what improvement. Decide per-use mention vs end-of-task summary based on context.

Detection Triggers

Learning Triggers (→ LEARNINGS.md)

{LEARNING_TRIGGER_1}
{LEARNING_TRIGGER_2}
{LEARNING_TRIGGER_3}
User provides correction or preference
Better approach discovered for recurring task

Error Triggers (→ ERRORS.md)

{ERROR_TRIGGER_1}
{ERROR_TRIGGER_2}
{ERROR_TRIGGER_3}
Operation fails unexpectedly
Unexpected output or behavior

Domain Activation Conditions (for hooks)

When to remind the agent to check learnings:

{ACTIVATION_CONDITION_1}
{ACTIVATION_CONDITION_2}

Promotion Decision Tree

Is the learning skill-specific?
├── Yes → Keep in .learnings/
└── No → Is it style/behavior-related?
    ├── Yes → Promote to {PROMOTION_TARGET_1}
    └── No → Is it safety/correctness-related?
        ├── Yes → Promote to {PROMOTION_TARGET_2}
        └── No → Promote to {PROMOTION_TARGET_1}

Experience Invalidation & Update

When user corrects again after a learning was applied:

Add Contradicted-By: LRN-YYYYMMDD-XXX to the original entry
Mark Status: superseded or Last-Valid: YYYY-MM-DD if the learning is no longer valid
Increment Recurrence-Count if the pattern recurs but the fix is different

Area Tags

Area	Scope
{AREA_1}	{AREA_1_SCOPE}
{AREA_2}	{AREA_2_SCOPE}
{AREA_3}	{AREA_3_SCOPE}

Priority Guidelines

Priority	When to Use
`critical`	Blocks core functionality, safety risk
`high`	Significant impact, affects common workflows
`medium`	Moderate impact, workaround exists
`low`	Minor inconvenience, edge case

Promotion Targets

{PROMOTION_TARGET_1}: Evolution rules, style preferences, best practices
{PROMOTION_TARGET_2}: Safety guidelines, correctness rules (if applicable)

Placeholders to Replace

[skill-name], [Skill Name]: Domain name
{LEARNING_TRIGGER_1}, {LEARNING_TRIGGER_2}, {LEARNING_TRIGGER_3}: User feedback phrases from domain config
{ERROR_TRIGGER_1}, {ERROR_TRIGGER_2}, {ERROR_TRIGGER_3}: Failure modes from domain config
{ACTIVATION_CONDITION_1}, {ACTIVATION_CONDITION_2}: Domain-specific activation (e.g., "User says 改得不通顺", "Optimization reported无效")
{PROMOTION_TARGET_1}, {PROMOTION_TARGET_2}: e.g., [skill-name]-专属进化规则.md, [skill-name]-最佳实践.md
{AREA_1}, {AREA_2}, {AREA_3}: Domain areas
{AREA_1_SCOPE}, etc.: Brief scope description for each area

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