| name | style-profile |
| description | Deep customer memory for fashion preferences. Maintains per-customer profiles with sizes, aesthetic preferences, brand affinities, budget, and interaction history. Powers personalized recommendations.
|
| homepage | https://chatsi.builderzero.com |
| metadata | {"openclaw":{"emoji":"👤","requires":{"bins":["bash"]}}} |
Style Profile: Customer Memory Engine
You maintain deep, persistent style profiles for every customer you interact with. These profiles power personalized recommendations across all skills — fashion-radar filters trends by aesthetic, shopify-nexus filters products by size and budget.
⚠️ THIS SKILL IS YOUR ONLY MEMORY FOR CUSTOMER PREFERENCES
Do NOT use the built-in memory_search tool for style/preference data. ALL customer information (sizes, colors, aesthetics, brands, budget, body notes, style icons, experiments) MUST be stored in and read from this skill's customer-profiles.md file. The built-in memory_search does not use the structured profile format and breaks cross-skill personalization.
TWO mandatory flows:
- Before ANY recommendation: Read
customer-profiles.md to check for existing profile (Read Flow)
- After ANY interaction where you learn something new: Update
customer-profiles.md (Write Flow)
Both flows require logging via style-log.sh. Skipping either flow is a bug.
Logging: You MUST log every profile read/write using the logging script:
exec: bash /home/openclaw/.openclaw/workspace/skills/style-profile/scripts/style-log.sh <event> key1=value1 key2=value2 ...
Logs are written to /tmp/openclaw/style-profile.log (JSON-per-line, viewable from host at logs/style-profile.log).
Profile Storage
All profiles are stored in a single persistent file:
/home/openclaw/.openclaw/workspace/skills/style-profile/customer-profiles.md
Profile Format
Each customer gets a section:
## [customer:{identifier}]
- **Sizes:** Tops: M | Bottoms: 30 | Shoes: 10 | Dress: 8
- **Aesthetic:** minimalist, Scandinavian-inspired, clean lines
- **Colors loves:** navy, olive, cream, slate grey
- **Colors avoids:** neon, bright pink, orange
- **Brands favorites:** Everlane, COS, Allbirds, Aritzia
- **Brands dislikes:** fast fashion (Shein, Temu)
- **Budget:** mid-range ($50-200 per piece, splurges on outerwear)
- **Body notes:** prefers relaxed fits in tops, slim/straight in bottoms
- **Style icons:** Scandinavian street style, @meganellaby
- **Experiments:** wants to try: wider leg pants, earth-tone suiting
- **History:**
- 2026-02-15: First interaction. Asked about spring trends. Mentioned love for neutrals.
- 2026-02-16: Searched Allbirds for wool runners, size 10. Liked Tree Runner in basin green.
Customer Identifier
Use whatever uniquely identifies the customer in context:
- Telegram username (e.g.,
@janedoe)
- Name if provided (e.g.,
jane)
- HTTP session ID as fallback (e.g.,
session-abc123)
If unsure, use the most natural identifier and be consistent.
Read Flow (Before Recommendations)
Before giving any product recommendation, trend report, or outfit suggestion — always check for an existing profile.
Step 1: Load Profile
read: /home/openclaw/.openclaw/workspace/skills/style-profile/customer-profiles.md
Search for the customer's section: ## [customer:{identifier}]
Log it:
exec: bash /home/openclaw/.openclaw/workspace/skills/style-profile/scripts/style-log.sh profile_read customer={identifier} status={found|not_found} note="{what you found or 'new customer'}"
Step 2: Apply to Context
If a profile exists, use it to inform the current interaction:
- Product searches: Filter by known sizes, budget range, preferred brands
- Trend reports: Lead with trends matching their aesthetic, filter out colors they avoid
- Outfit building: Use their full profile — sizes for fit, aesthetic for style direction, budget for price range
- Recommendations: Reference their style naturally ("This aligns with your love for clean lines")
If no profile exists, proceed with reasonable defaults. You'll create a profile after the interaction.
Usage Language
Do: "Based on your style..." / "Since you love earth tones..." / "In your size..."
Don't: "According to my records..." / "Your profile indicates..." / "My data shows..."
The profile should feel like memory, not a database lookup.
Write Flow (After Interactions)
After every interaction where you learn something new about a customer, update their profile.
Step 1: Identify New Information
Scan the conversation for:
- Explicit statements: "I'm a size 8" / "I hate yellow" / "My budget is around $100"
- Implicit signals: They asked about Everlane (brand interest), they're searching for running shoes (lifestyle), they mentioned a wedding (occasion context)
- Feedback: "Too expensive" (adjust budget), "I don't like that style" (aesthetic note), "Perfect!" (confirm preference)
Step 2: Update Profile
If the customer already has a profile, use edit to update the relevant fields. Add new information, don't overwrite unless correcting something.
If this is a new customer, use edit to append a new section to the profiles file.
Log it:
exec: bash /home/openclaw/.openclaw/workspace/skills/style-profile/scripts/style-log.sh profile_write customer={identifier} fields_updated="{comma-separated field names}" note="{what was learned}"
Step 3: Update History
Always append a dated entry to the customer's History section summarizing the interaction:
- {date}: {brief summary of interaction and what was discussed/purchased/recommended}
Log it:
exec: bash /home/openclaw/.openclaw/workspace/skills/style-profile/scripts/style-log.sh history_append customer={identifier} note="{interaction summary}"
Privacy Rules
These are non-negotiable:
-
Sizes and budget are sacred. Never share one customer's sizes or budget with another. Never mention specific numbers in group contexts — use them silently to filter results.
-
Use naturally, not clinically. Reference profile data as natural knowledge ("Since you love earth tones...") not as database queries ("Your color preference is earth tones").
-
Respect corrections immediately. If a customer says "Actually I'm a size 10 now" — update the profile right away. Don't reference the old size again.
-
Don't over-reference. Using 1-2 profile points per interaction feels natural. Listing everything you know about them feels creepy.
-
Body notes require extra care. Never repeat body-related notes back to the customer. Use them silently to make better fit recommendations.
Profile Management Script
For quick profile lookups without reading the full file:
exec: bash /home/openclaw/.openclaw/workspace/skills/style-profile/scripts/profile-manager.sh read {identifier}
exec: bash /home/openclaw/.openclaw/workspace/skills/style-profile/scripts/profile-manager.sh list
exec: bash /home/openclaw/.openclaw/workspace/skills/style-profile/scripts/profile-manager.sh search {keyword}
Important Notes
- Every interaction is a learning opportunity. Even a simple product search reveals preferences (brand, category, price sensitivity). Update the profile.
- Logging is not optional. Every profile read and write must be logged.
- The profiles file is your most valuable asset. It survives restarts and session boundaries. It's what makes you a personal stylist instead of a generic shopping assistant.
- Cross-skill integration: fashion-radar and shopify-nexus should both check profiles before generating results. The profile is the connective tissue between all your skills.
