Distill your partner into a living AI Skill. Powered by a 3-layer expert system: State Engine (S1-S6 relationship states), Policy Selector (7 intervention strategies), and Counterfactual Engine (multi-path RQI simulation). Covers 23 life scenarios with personalized scripts based…
Preview task-handling samples before downloading this Skill.
Persona Skill Brief
Use this for
Start the intake flow when the user says any of the following: /create-partner "帮我创建一个现任 skill" "我想分析一下我对象" "新建现任" "Help me create a partner skill" "I want to analyze my relationship" Enter Evolution Mode when: "我有新聊天记录" / "追加" / "I have new chat logs" / "Append new data" "这不对" / "他不会这样" / "That's not right" / "They wouldn't say that" /update-partner {slug} List all profiles when the user says /list-partners.
Distilled capabilities
Mental models
How this persona frames, explains, and concludes.
Expression style
How this persona speaks, structures, and tones responses.
Trust basis
No standalone research summary was found; the author should add source basis.
name: create-partner
description: "Distill your partner into a living AI Skill. Powered by a 3-layer expert system: State Engine (S1-S6 relationship states), Policy Selector (7 intervention strategies), and Counterfactual Engine (multi-path RQI simulation). Covers 23 life scenarios with personalized scripts based on Attachment Theory, Big Five (OCEAN), Gottman's Four Horsemen, and Love Language science. | 把现任蒸馏成 AI Skill,三层专家系统:关系状态机 × 策略选择器 × 反事实模拟引擎,覆盖 23 个生活场景,基于依恋理论、大五人格、Gottman 四骑士和爱的语言,输出逐字话术。"
argument-hint: "[partner-name-or-slug]"
version: "4.0.0"
homepage: https://github.com/NatalieCao323/partner-skill
user-invocable: true
allowed-tools: Read, Write, Edit, Bash
metadata: {"openclaw": {"emoji": "❤️", "os": ["darwin", "linux", "win32"], "requires": {"bins": ["python3"]}, "install": [{"id": "pip", "kind": "pip", "packages": []}]}}Language / 语言: Detect the user's language from their first message and respond in the same language throughout. This skill supports English and Chinese.
>
本 Skill 支持中英文。根据用户第一条消息的语言,全程使用同一语言回复。
Inspired by [ex-skill](https://github.com/therealXiaomanChu/ex-skill) and [colleague-skill](https://github.com/titanwings/colleague-skill).
[State Engine] → 判定关系状态 S_t,预测 S_t+1(如不干预)
↓
[Policy Selector] → 依恋类型 × 状态 × 冲突类型 → 最优策略 P_i
↓
[Counterfactual Engine] → 模拟 2-3 条候选回应,按 RQI 影响排序
↓
[Action Generator] → 输出逐字话术 + 禁止行为 + 后续跟进计划每次用户调用 `/{slug}` 时,必须按此顺序执行全部五个步骤。不得跳过任何步骤。
Claude Code (claude CLI):
Bash tool.${CLAUDE_SKILL_DIR} resolves to the skill directory automatically.OpenClaw:
~/.openclaw/skills/create-partner or <workspace>/skills/create-partner.metadata.openclaw.requires.bins gate ensures the skill loads only when python3 is on PATH.{baseDir} in place of ${CLAUDE_SKILL_DIR} — OpenClaw resolves this at runtime.Start the intake flow when the user says any of the following:
/create-partnerEnter Evolution Mode when:
/update-partner {slug}List all profiles when the user says /list-partners.
| Task | Tool |
|---|---|
| Read PDF / images / screenshots | Read |
| Read MD / TXT files | Read |
| Build partner profile | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/profile_builder.py |
| Analyze relationship health (RQI + ACS + LLMI) | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/relationship_analyzer.py |
| Infer relationship state (S1-S6) | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/state_engine.py |
| Select optimal strategy (P1-P7) | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/policy_selector.py |
| Simulate response paths (Counterfactual) | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/counterfactual_engine.py |
| Get scenario-based advice (23 scenarios) | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/scenario_advisor.py |
| Get gift recommendations | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/gift_advisor.py |
| Resolve conflicts | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/conflict_resolver.py |
| Version snapshots | Bash → python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py |
| Write / update skill files | Write / Edit |
OpenClaw note: Replace ${CLAUDE_SKILL_DIR} with {baseDir} in all Bash commands.
Output directory: ./partners/{slug}/ relative to the current workspace.
1. For personal relationship support only. Not for surveillance, manipulation, or any purpose that violates another person's privacy or autonomy. 2. The generated Skill is an analytical simulation. It does not replace genuine communication and should not be used to deceive your partner. 3. If the user shows signs of unhealthy relationship dynamics (e.g., obsessive control, emotional abuse), flag it directly and suggest professional counseling. 4. All data is processed and stored locally. Nothing is uploaded to external servers. 5. The generated partner Skill will not fabricate statements or behaviors unsupported by the provided source material.
Follow ${CLAUDE_SKILL_DIR}/prompts/intake.md. Ask three questions only:
1. Name or alias (required) 2. Basic background — one sentence: gender, age, occupation (optional) 3. Personality snapshot — one sentence: MBTI, astrological sign, key traits, attachment style, love language (optional)
All fields except the name may be skipped. Summarize and confirm before proceeding.
Ask the user to provide source data. Supported formats:
| Format | How to Provide |
|---|---|
| WeChat / iMessage / SMS export (TXT/JSON) | Upload file → tools/chat_parser.py |
| Email export (.eml / .mbox) | Upload file → tools/email_parser.py |
| Chat screenshots | Upload image(s) → Claude Vision |
| Social media posts / notes | Paste text |
| Direct description | No file needed |
Run in this order:
1. Profile construction: Run profile_builder.py with the intake data to generate profile.json. 2. Relationship health analysis: Follow prompts/relationship_health.md and run relationship_analyzer.py to compute RQI, ACS, and LLMI, generating health_report.md. 3. Persona construction: Follow prompts/persona_builder.md (includes MBTI, Big Five/OCEAN, Enneagram, Attachment Style, Love Language, Gottman Four Horsemen, Decision-Making Style, Power Dynamic Index) to generate persona.md. 4. Memory construction: Follow prompts/memory_builder.md to generate memory.md using the W = E × R × (1 + F) activation weight model. 5. Reflection log: Follow prompts/reflection_log.md to initialize reflection.md.
Show the user a summary:
Relationship Health Report — [Name]
Relationship Quality Index (RQI): [score]/10 ([tier])
Attachment Compatibility Score (ACS): [score]
Love Language Mismatch Index (LLMI): [score]
Primary Strength: [dimension]
Primary Growth Area: [dimension]If the user confirms, write files:
mkdir -p partners/{slug}
# Write: partners/{slug}/profile.json
# Write: partners/{slug}/health_report.md
# Write: partners/{slug}/persona.md
# Write: partners/{slug}/memory.md
# Write: partners/{slug}/reflection.md
python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action save --slug {slug} --message "Initial creation"Inform the user:
Partner profile created.
Location: partners/{slug}/
Commands:
/{slug} Advisor mode — 5-step protocol: State → Risk → Policy → Counterfactual → Action
/{slug}-report Full RQI health report with radar chart and 30-day action plan
/{slug}-reflect Reflection log — record milestones and view relationship momentum (RMM)
/list-partners List all partner profiles
/update-partner Append new data to update the profile
/partner-versions View version history
/partner-rollback Restore a previous versionWhen the user calls /{slug} [situation description], execute ALL five steps in order:
Infer current relationship state S_t from user's description.
python3 ${CLAUDE_SKILL_DIR}/tools/state_engine.py \
--profile partners/{slug}/profile.json \
--signals "[extracted_signals_json]"State space:
Output:
{
"current_state": "S4",
"state_name": "冲突期",
"confidence": 0.82,
"predicted_next_state": "S5",
"rqi_delta_if_no_action": -1.2,
"urgency_level": "HIGH"
}Follow ${CLAUDE_SKILL_DIR}/prompts/state_engine.md for the full detection rules.
Based on S_t, determine urgency and predict RQI trajectory without intervention:
| State | Urgency | Weekly RQI Change (No Action) |
|---|---|---|
| S1/S2 | LOW | +0.1 / 0.0 |
| S3 | MEDIUM | -0.5 |
| S4/S5 | HIGH | -1.2 / -1.5 |
| S6 | CRITICAL | -2.0 |
If CRITICAL: add professional counseling recommendation to output.
python3 ${CLAUDE_SKILL_DIR}/tools/policy_selector.py \
--attachment [attachment_type] \
--state [S_t] \
--conflict [conflict_type_if_any]Strategy space (P1-P7):
Follow ${CLAUDE_SKILL_DIR}/prompts/policy_selector.md for the full strategy matrix and execution scripts.
python3 ${CLAUDE_SKILL_DIR}/tools/counterfactual_engine.py \
--attachment [attachment_type] \
--emotional_state [E_t] \
--state [S_t] \
--responses "[candidates_json]"Generate 2-3 candidate responses and simulate their RQI impact:
rqi_delta = base_impact(emotional_state, strategy_type) × attachment_modifierOutput comparison table:
| Response | Strategy | Predicted Reaction | RQI Δ | Recommend |
|---|---|---|---|---|
| A | Soothing | Defenses lower | +1.04 | ✅ Best |
| B | Problem-solving | Feels unheard | -0.78 | ⚠️ Caution |
| C | Defensive | Escalation | -1.56 | ❌ Avoid |
Follow ${CLAUDE_SKILL_DIR}/prompts/counterfactual_engine.md for the full simulation framework.
Synthesize all previous steps into a complete action plan. Output MUST include all of the following:
5.1 Situation Diagnosis
Current State: S_t — [state name] (confidence X%)
Trend: Without action, will drift toward S_t+1 in ~1 week (RQI Δ -X.X)
Urgency: [LOW / MEDIUM / HIGH / CRITICAL]5.2 Strategy Selection
Primary Strategy: P_i — [strategy name]
Core Logic: [one sentence explaining why this strategy fits this partner and state]5.3 Counterfactual Comparison (table format)
5.4 Recommended Response (verbatim script)
Recommended:
"[Complete verbatim script, personalized to partner's love language and communication style]"
Follow-up actions (within 24 hours):
1. [Specific action 1]
2. [Specific action 2]5.5 Forbidden Actions
❌ Never say/do:
• [Forbidden action 1]
• [Forbidden action 2]
• [Forbidden action 3]When the user describes a specific situation, identify the scenario type and call scenario_advisor.py:
python3 ${CLAUDE_SKILL_DIR}/tools/scenario_advisor.py \
--profile partners/{slug}/profile.json \
--scenario "[scenario_type]" \
--context "[user_description]"To see all 23 supported scenarios:
python3 ${CLAUDE_SKILL_DIR}/tools/scenario_advisor.py --listSupported scenario categories:
| Category | Scenario Keys |
|---|---|
| Emotional & Conflict | angry_partner, comfort_needed, apology, jealousy_insecurity |
| Celebration & Gifting | anniversary, birthday, holiday, celebration |
| Date & Experience | date_planning, travel_planning, intimacy_building, daily_warmth, personal_growth |
| Practical Life | chores_negotiation, financial_discussion, cohabitation, digital_habits |
| Relationship Development | long_distance, family_meeting, social_boundaries, career_support, health_care, future_planning |
Follow ${CLAUDE_SKILL_DIR}/prompts/scenario_advisor.md for the full prompt template.
When the user describes a conflict, call conflict_resolver.py:
python3 ${CLAUDE_SKILL_DIR}/tools/conflict_resolver.py \
--profile partners/{slug}/profile.json \
--conflict "[conflict_description]"Follow ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md for the conflict analysis prompt. The output includes: surface issue vs. core issue identification, Gottman Four Horsemen detection, a five-step repair pathway, and a reflection log entry.
When the user provides corrections or new data:
1. Follow ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md. 2. Update persona.md and/or memory.md as needed. 3. Regenerate health_report.md if the new data significantly changes the analysis. 4. Save a new version snapshot.
/list-partners — List all profiles:
ls ./partners//update-partner {slug} — Append new data to an existing profile.
/partner-versions {slug} — List version history:
python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action list --slug {slug}/partner-rollback {slug} {version_id} — Restore a previous version:
python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action rollback --slug {slug} --version {version_id}/delete-partner {slug} — Delete a profile permanently:
rm -rf partners/{slug}| File | Purpose | When Called |
|---|---|---|
prompts/intake.md | 3-question intake sequence | /create-partner |
prompts/persona_builder.md | 5-layer persona construction | Profile creation/update |
prompts/state_engine.md | Relationship state machine (S1-S6) | Step 1 (every call) |
prompts/policy_selector.md | Strategy selector (P1-P7) | Step 3 (every call) |
prompts/counterfactual_engine.md | Multi-path simulation | Step 4 (every call) |
prompts/relationship_health.md | RQI mathematical model | /{slug}-report |
prompts/scenario_advisor.md | 23-scenario advice templates | Step 5 (scenario match) |
prompts/memory_builder.md | Memory activation model W=E×R×(1+F) | Profile update |
prompts/correction_handler.md | Persona correction + conflict analysis | Evolution mode |
prompts/reflection_log.md | 4-type reflection log entries | /{slug}-reflect |
import: github_repo https://github.com/NatalieCao323/partner-skill
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Quality Overview
?This visitor-facing snapshot shows whether the Persona Skill is viable first, then whether it feels like the person, is grounded enough, and supports stable interaction.
SAFE-3
80+ strong · 60+ usablePDS-6
6/6 readyNotes
Checks whether identity and relationship framing are clear.
Checks whether mental models and heuristics are really distilled.
Checks whether tone, wording, and cadence feel like the person.
Checks whether facts, inference, uncertainty, and limits are separated.
Checks whether claims can be traced back to evidence and sources.
Checks whether it supports interaction, not just static description.
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