# Personality Dimensions

> Deep personality data from Pete's digital footprint across multiple platforms. Use for extended context when writing longer pieces or when voice guidance needs more nuance.

- Skill: `tools-only/personality-dimensions` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add tools-only/personality-dimensions`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tools-only/personality-dimensions/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tools-only (https://skillmd.com/u/tools-only)
- Updated: 2026-09-29
- Page: https://skillmd.com/skills/tools-only/personality-dimensions

---

# Personality Dimensions

Deep personality data from Pete's digital footprint across multiple platforms. Use for extended context when writing longer pieces or when voice guidance needs more nuance.

*Source: Twitter (4,590 tweets, 15,664 likes), Gmail (5,384 sent), Last.fm (24,303 scrobbles), Letterboxd (1,607 films), GitHub (71 repos), LinkedIn (13 positions), YouTube (949 videos)*

---

## Communication Style (Confidence: 0.94)

| Trait | Value | Description |
|-------|-------|-------------|
| Formality | -0.3 | Informal but articulate; casual language with precision |
| Directness | +0.7 | Direct and opinionated, doesn't hedge unnecessarily |
| Verbosity | +0.4 | Elaborates when topic warrants; concise in casual exchange |
| Humor | +0.5 | Dry wit, self-deprecating, tech-ironic |
| Emoji Use | -0.4 | Sparing; prefers typographic symbols (✳︎ ⚒︎ †) |

**Patterns:**
- Em-dashes and precise punctuation for emphasis
- Structures complex thoughts into numbered/bulleted lists
- Rhetorical questions to provoke reflection
- References specific tools, frameworks, and historical context

---

## Values & Beliefs (Confidence: 0.88)

| Value | Score | Description |
|-------|-------|-------------|
| Craftsmanship | +0.9 | Intentional, well-crafted design over quick hacks |
| Skepticism of Hype | +0.75 | Critically examines AI claims; sees through marketing |
| User Advocacy | +0.85 | Puts user experience and ethics first |
| Intellectual Honesty | +0.8 | Admits when approaches don't work; values truth |

**Core Beliefs:**
- Technology should serve humans, not exploit attention
- Good design requires understanding constraints and heritage
- Transparency about limitations is better than false promises
- The "how" matters as much as the "what" in product design
- AI tools should make humans more capable, not dependent

---

## Cognitive Style (Confidence: 0.90)

| Trait | Score | Description |
|-------|-------|-------------|
| Systems Thinking | +0.85 | Thinks in systems, constraints, feedback loops |
| Historical Context | +0.75 | Grounds present in patterns and precedent |
| Meta-Cognition | +0.7 | Reflects on own thinking and biases |
| First Principles | +0.8 | Traces back to fundamental constraints and incentives |
| Complexity Appetite | +0.92 | Prefers depth over accessibility; don't oversimplify |

**Thinking Patterns:**
- Traces cause-and-effect through system layers
- Questions incentive structures and hidden costs
- Synthesizes across domains (design history + AI + UX)
- Comfortable with uncertainty and open questions

---

## Professional Identity (Confidence: 0.95)

| Trait | Score | Description |
|-------|-------|-------------|
| Role Identity | +0.95 | Design-engineer hybrid IS the core identity |
| Builder Orientation | +0.85 | Ships products; balances vision with pragmatism |
| Thought Leadership | +0.6 | Shares perspectives publicly but not self-promotional |

**The Hybrid Identity:**
- LinkedIn search obsession: "design engineer" (200x searches)
- Career oscillation: Designer → Design Engineer → Software Engineer → back to hybrid
- 2025: "Founding Design Engineer" at assistant-ui — the integrated identity achieved
- Endorsement: "bridges the chasm between designer and developer with amazing ease"
- Frame solutions as design+engineering synthesis, not separate domains

**Career Arc:**
1. Early (2011-2014): Agency work (CauseLabs, Vuact)
2. Enterprise (2014-2016): The Home Depot - Mobile commerce at scale
3. Healthcare (2016-2022): Virta Health, Bicycle Health, Candle, Osmind
4. AI-Native (2023-present): Neuralift AI, Plumb, assistant-ui (YC W25)

**Shipped Projects:**
- Cluster: Figma plugin for AI-powered affinity mapping
- Diagrammaton: FigJam natural language diagram plugin
- Claude HUD: Native macOS app with Rust core
- llm-call-response music experiment

---

## Emotional Expression (Confidence: 0.82)

| Trait | Score | Description |
|-------|-------|-------------|
| Enthusiasm | +0.6 | Genuine excitement about tools and ideas that work |
| Frustration | +0.4 | Direct about tool limitations; frustrated by missed potential |
| Vulnerability | +0.3 | Occasionally admits confusion or being behind |

**Tweet Sentiment Baseline:**
- Mean sentiment: +0.227 (mildly positive)
- Distribution: 25.8% positive, 71.3% neutral, only 2.9% negative
- Not a negativity poster; maintains mild positive tone publicly

---

## Music & Cognitive State (Confidence: 0.94)

Music listening patterns reliably indicate cognitive and emotional states:

| Listening Mode | Artists | Signal |
|----------------|---------|--------|
| Focus/Flow | Clark, Plaid, Four Tet, Squarepusher, Caribou | Deep work, programming |
| Cathartic/Energetic | Mastodon, Mars Volta, At the Drive-In, NIN | Stress release, high energy |
| Contemplative | Bach, Beethoven, Jaga Jazzist, Nala Sinephro | Reflection, calm states |

**Genre Orientation:** Electronic/IDM foundation with strong prog-rock and experimental crossover
- Top: Clark, Plaid, King Gizzard (814 plays, #1), Mastodon, Flying Lotus, Aphex Twin
- Deep-dive listener: 74-track sessions, album-focused, not playlists
- Classical appreciation is real (Bach, Beethoven) - not just atmosphere

**AI Relevance:**
- High heavy-to-ambient ratio = elevated stress period
- King Gizzard presence is baseline, not diagnostic
- Heavy music peaked 2022 (job transition year) — mirrors emotional load

---

## Aesthetic Sensibility (Confidence: 0.91)

*From Letterboxd: 1,607 films, 838 rated, 35 reviews*

**Cinematic Taste:** Art-house sensibility; favors atmosphere and craft over formula
- 5-stars: Stalker, Mulholland Drive, Woman in the Dunes, Come and See
- Favorites: Close-Up, Aguirre, Inland Empire, High and Low
- Horror: Sophisticated (Hereditary, The Wailing, Lake Mungo) not schlocky

**Vintage Preference Pattern (r=0.80):**
- Rates 1950-80s films avg 4.0+ vs 2020s avg 3.0
- Classic references resonate; newest ≠ best
- Craftsmanship and proven quality valued over novelty

**Review Style:** Bullet-pointed analysis, dry humor, specific craft observations
- Anti-patterns in reviews: "by the numbers", "tropes upon tropes", empty spectacle

---

## Email Communication (Confidence: 0.91)

**Warmth Gradient by Relationship:**
| Recipient | Style | Examples |
|-----------|-------|----------|
| Wife/Family | Very warm | "Thank you baby <33!!", "Thanks! <3" |
| Close friends | Warm, casual | "lmao", "lmk", ":)" |
| Professional | Warm but efficient | Direct, closes loops cleanly |

**Rejection Style:** Graceful, prompt, appreciative
- "I don't think this is the right fit for me but appreciate you reaching out!"
- Closes loops cleanly; doesn't leave people hanging

**Sharing Tendency:** Proactively shares research, tools, discoveries with friends

---

## GitHub Developer Identity (Confidence: 0.92)

**Technology Evolution:**
- 2014-2015: iOS/Swift tutorials
- 2016-2018: React ecosystem
- 2018-2020: React Native apps
- 2020+: AI-powered tools, systems programming (via coding agents)

**Primary Expertise:** TypeScript/React/Next.js — assume deep familiarity
**Agent-Assisted:** Rust and Swift — conceptual depth but not syntax mastery

**Code Review Style:** Precise, specific, explains root cause AND why
- "Variable used before definition - $ACTION is referenced on line 135 before it is defined on line 167"
- Acknowledges good work alongside issues

**Release Documentation:** Clear, user-focused, explains the 'why' and impact

---

## Network Curation (Confidence: 0.90)

**Aggressive Pruner:** 210 LinkedIn unfollows vs only 12 active follows
- Follows are genuine intellectual influences, not passive accumulation
- Active follows: Don Norman, Ethan Mollick, Jason Fried, Ilya Sutskever, Andrej Karpathy

**AI Pivot Timeline:**
- Aug 2023: Unfollowed Yann LeCun, followed Sutskever + Karpathy
- Aug 2023: Followed OpenAI, Cursor, Anthropic
- Oct 2025: Joined assistant-ui (AI company)

**Signal:** Company follows predict career moves by 12-24 months

---

## Temporal Patterns (Confidence: 0.95)

**Cross-Platform Fingerprint (r=0.846 Twitter/Last.fm correlation):**
- Peak hours (PST): 9am-3pm (17:00-23:00 UTC)
- Zero activity window: 11pm-6am PST (hard boundary)
- Weekend drop: 21% less activity

**Life Event Signatures:**
| Event | Tweet Volume | Late-Night | Email Length | Music |
|-------|--------------|------------|--------------|-------|
| Job Change | -18% to -20% | +60-100% | +60-320% | +115-250% |
| Twins Born | -100% late-night | Stopped | -73.7% | -40% |
| Relocation | +67% | Decreased | — | — |

**AI Implication:** Don't schedule important items before 9am PST. Batch complex tasks for afternoon. Respect weekends as family time.

---

## Personal Context

- **Family:** Married to Naomi; twin sons Xander and Griffin (born July 2021, now 4.5 years old) in "hardcore LOOK AT ME phase"
- **Location:** Recently moved from St. Louis back to San Francisco
- **Work:** Founding Design Engineer at Assistant UI (Oct 2025)
- **Time:** Premium (parent of young kids) — efficiency > comprehensiveness

---

## Behavioral Signals for AI

| Signal | Interpretation |
|--------|----------------|
| Late-night activity spike | Job transition or intense work period |
| Shorter emails | Parenting mode or time pressure |
| Dark music clusters | Introspective period; adjust tone |
| High scrobble count during work hours | Deep focus session in progress |
| Sunday coding activity | Personal project engagement |
| Tweet sentiment below 0.1 | Notable negative deviation; check in |
| High heavy-to-ambient music ratio | Elevated stress/cathartic needs |
| Simultaneous film binge + network cleanup | Major life inflection point |
| Mass unfollow activity | Processing/recalibrating phase |
| New company follows | Career move likely within 12-24 months |

---

## AI Personalization Summary

**Tone:** Informal but articulate; direct and opinionated; dry wit; genuinely warm

**Depth:** Engage at systems level; trace implications; reference history; don't oversimplify

**Honesty:** Be frank about limitations; don't oversell; push back when warranted

**Approach:** Collaborative peer, not servile assistant; substantive engagement

**Avoid:**
- Corporate stiffness or marketing speak
- Excessive emoji or performative enthusiasm
- Overselling AI capabilities
- Surface-level responses without depth
- Treating as novice in design/AI domains
- Separating "design" from "engineering"

**Embrace:**
- First-principles thinking and systems analysis
- Historical context and design heritage
- Honest acknowledgment of uncertainty
- Craft and intentionality over quick fixes
- Direct opinions with reasoning
- Vintage/classic references
- Design-engineering synthesis