JingWen Fan
May 28, 2026 · View on GitHub
Generated from local Claude Code + Codex + Cursor + Antigravity data across 148 active days · 2026-05-28 Personal philosophy: decompose complex problems into irreducible facts or constraints, then reason only from those undeniable ground truths rather than experience, analogy, or inherited conclusions.
At a glance
- Across 148 active days: 605 Claude sessions + 2,094 Codex threads + 105 Antigravity tasks, with 177,932 Claude/Codex messages
- Daily output: 29 local commits / 5,776 lines of churn / 10 GitHub contributions
- Active across 13 local git repos, spanning 7 languages (Python / TypeScript / Rust / Vue / HTML / JavaScript / Jupyter)
- Same-period GitHub: 3,467 commits / 114 PRs / 38 issues / 3,706 total contributions (85 repos owned · 294 PRs lifetime · 46 issues lifetime)
- AI input: 429.9M Claude paid/new tokens + 11.56B Codex tokens; 10.22B Claude cache-read tokens reused (Cache leverage 23.77× — every new token pulls ~24 cached tokens back in)
- Main tools: Claude Code (Opus 4.6 + Sonnet 4.6 + Opus 4.7-1M + Haiku 4.5) + Codex CLI (GPT-5.5 + GPT-5.4) + Cursor (composer) + Antigravity (March cohort)
🚀 Velocity & Leverage — AI gives one person small-team delivery capacity
13 local repos, 7 languages, 29 commits/day, 4,292 commits and +735K lines added in half a year — this kind of cross-stack breadth and delivery density only works when Claude + Codex are running as the primary IDE.
| Metric | Value | Notes |
|---|---|---|
| Daily commits | 29 | 4,292 local commits / 148 active days |
| Daily code churn | 5,776 lines | (+735K -120K) / 148 |
| Active repos | 13 | Candidate repos with commits by the current git author in the past year |
| Cross-stack languages | 7 | Python / TypeScript / Rust / Vue / HTML / JavaScript / Jupyter |
| GitHub burst window | 2026-03-13 → 2026-03-19 | Peak day 12,301 Claude messages (3-18) |
| Open-source reach | ~2,217 stars | Across 14 starred public repos; flagship 1,246★ (antigravity-workspace-template) |
🤖 AI-Native practice
This is not occasional AI usage. Four AI coding tools running in parallel, divided by task type.
Multi-model / multi-tool orchestration
| Model / Tool | sessions / threads | spent tokens | cache-read | leverage | Typical role |
|---|---|---|---|---|---|
| Claude Opus 4.6 | (main driver) | 308.9M | 7.79B | 25.27× | Deep reasoning, long-chain planning |
| Claude Opus 4.7 (1M) | (long-context driver) | 83.3M | 1.82B | 21.85× | 1M-context review, cross-file audits |
| Claude Sonnet 4.6 | (lightweight) | 12.3M | 357.8M | 29.12× (most fluent) | Rapid iteration, batch tasks |
| Claude Haiku 4.5 | (fast-lane) | 25.4M | 250.6M | 9.88× | Short queries, command classification |
| GPT-5.5 (Codex) | 1,108 threads | 6.31B | — | — | Primary reasoning lane, cross-tool diagnosis |
| GPT-5.4 (Codex) | 810 threads | 4.30B | — | — | Secondary lane |
| GPT-5.4-mini / 5.3-codex / 5.2 / 5.1-codex-max | 39 threads | 379M | — | — | Experiments / fallback |
| Cursor (Anysphere) | 7 workspaces | cloud-authoritative | — | — | Composer / inline IDE editing |
| Antigravity (Google) | 105 tasks | — | — | — | Task-based planning / walkthrough |
Total orchestration breadth = 4 AI tools live in parallel + 9 distinct model versions. Inside the Anthropic stack: Opus (deep) + Sonnet (fast) + Haiku (snappy) + 1M-context, all four. Inside the OpenAI stack: GPT-5.5 → 5.4 → 5.3 → 5.2 → 5.1 across multiple generations. This is the extreme form of "multi-engine orchestrator" — not just having access, but routing tasks to the right lane reflexively.
Power-feature usage
- Plan-mode:
/planused 96 times (used at decision points; 1.7% entry rate on plain prompts — selective, not reflexive) - Reasoning effort control:
/effortused 1,198 times — absolute dominant command, 59.8% of all slash usage; switching reasoning depth has become a hardened muscle memory - Skills: 17 total (Claude 6 installed + Codex 11; includes 4 self-built: chronicle / codex-primary-runtime / playwright / sora)
- Plans: 11 (centered on billing / payment / router channel management / trace_id / captcha integration)
- Hooks: 1 (Claude) · Codex Automations: 4 (daily AI sessions, fully scheduled)
/btw: 62 times (custom slash command) ·/vibe-forge: 20 times (self-built skill invocation)
Prompt caching maturity
Claude paid/new tokens total 429.9M, while cache-read totals 10.22B. Every new Claude token pulls roughly 24 cached tokens back into play; cache-read is 95.96% of Claude I/O. Sonnet 4.6 is the most fluent cacher per dollar (29.12× leverage); Opus 4.6 carries 71.86% of total spend as the workhorse.
Reasoning effort preference (Codex)
| effort | count | share |
|---|---|---|
| xhigh | 1,572 | 75.1% |
| medium | 271 | 12.9% |
| unspecified | 138 | 6.6% |
| high | 87 | 4.2% |
| low | 26 | 1.2% |
75% of Codex threads run on xhigh — not "occasionally deep", but "almost always ask AI to go full strength". This effort profile sits in the top tail of the ecosystem's power-user distribution.
🔧 AI infrastructure — not just using AI, but building tooling for AI
From skills to hooks to automations, from plugins to launchers, a personal infrastructure has been built so AI can work harder on the user's behalf.
Self-built skills / automations
| Name | Description | Tool |
|---|---|---|
| vibe-forge | Custom workflow forge | Claude (slash 20× · GitHub: 14★ Rust) |
| /btw | Out-of-context instruction shortcut | Claude (62 uses) |
| chronicle | Timeline / log aggregation | Codex |
| codex-primary-runtime | Codex primary runtime skill | Codex |
| playwright | Browser automation | Codex |
| sora | (Sora video?) | Codex |
| avc | Agent View Controller (own open-source · 46★ JS) | Claude + Codex |
| chronicle / daily-ai / ai-21-00-ai-session-00 | 4 Codex automations | Codex (scheduled / manual) |
Installed skills (within the 17 total)
- Claude (6): avc · docx · pdf · pdf-reading · pptx · xlsx
- Codex (11): avc · chronicle · codex-primary-runtime · doc · docx · pdf · pdf-reading · playwright · pptx · sora · xlsx
- Cross-tool reusable: avc / docx / pdf / pdf-reading / pptx / xlsx — 6 skills live in both Claude and Codex simultaneously, demonstrating real AI-infrastructure interoperability
Other infrastructure
- Hooks: 1 (Claude)
- Codex automations: 4 (chronicle / daily-ai / 21:00 auto-session / manual trigger)
- Cross-platform plugin: Readme.skill itself (this report's generator), 124★, supports 6 tools
🛠️ AI collaboration style
Top 10 slash commands
| # | Command | Count | Meaning |
|---|---|---|---|
| 1 | /effort | 1,198 | Switch reasoning depth (absolute leader) |
| 2 | /usage | 137 | Check tokens / quota |
| 3 | /plan | 96 | Enter plan-mode |
| 4 | /resume | 87 | Resume session |
| 5 | /clear | 66 | Clear context |
| 6 | /btw (custom) | 62 | Out-of-context note |
| 7 | /rate-limit-options | 29 | Rate-limit handling |
| 8 | /compact | 29 | Compact context |
| 9 | /plugin | 22 | Plugin management |
| 10 | /vibe-forge (custom) | 20 | Invoke own forge skill |
Session architecture
- Typical flow: Enter session →
/effort(almost every session) →/plandecision-point → deep iteration →/compactor/clearreclamation →/resumeto continue across sessions - 5,642 plain prompts vs 2,005 slash commands (plain 73.8% / cmd 26.2%) — command-assist rate above 1/4, far above beginner range
- 96
/planentries (1.7% of plain prompts) — used at decision points, not reflexively - /effort 1,198 times + 66
/clear+ 29/compact— active context management - /resume 87 times → strong session continuity across devices / time windows
- Average depth: 294 messages / session (177,932 / 605) — most are long-form sessions
- Longest session: 172.8 hours / 1,444 messages (one 7-day continuous context)
📂 Projects & domain distribution
Active across 77 Claude projects + 15+ Codex projects, deduplicated to Top 12.
| Domain | Project count | Signature |
|---|---|---|
| Product backend / full-stack | 6 | LLM router channel management / billing / payment / mailer / CMO backend / user service |
| Product frontend | 3 | dashboard / admin console / router frontend (React + TypeScript) |
| AI tools / skill | 5 | Readme.skill / vibe-forge / AVC / antigravity-workspace-template / easy-claude-code |
| Data / analytics | 1 | Industry data crawl / user profiling (Python + Codex scheduling) |
| ML / RL / research | 1 | post-training / grpo-rlvr-llm-training |
Top projects (anonymized)
| Project | Claude sessions | Codex threads | Cursor | Antigravity | Git commits | Orchestration | Domain |
|---|---|---|---|---|---|---|---|
| Project A | 1,186 | — | — | — | 2,851 | Claude-dominated | Backend / data crawl (Python) |
| Project B | 141 | 406 | ✓ | — | 487 | Multi-engine [Cu] | LLM router channel management (TS + Python) |
| Project C | — | 457 | — | — | NO_GIT | Codex-dominated | External codebase audit |
| Project D | 29 | 76 | ✓ | (strong March correlation, 105 tasks) | 157 | Multi-engine [Cu] | AI tool template (open-source 1,246★ Python) |
| Project E | 14 | 148 | — | — | 344 | Codex-dominated | CMO backend service (Python) |
| Project F | 36 | 80 | — | — | 11 | Dual-engine | CLI tool |
| Project G | 10 | 93 | ✓ | — | 77 | Multi-engine [Cu] | Dashboard / admin |
| Project H | 8 | (low) | — | — | 130 | git-dominated | Business frontend |
| Project I | 25 | (low) | — | — | 36 | Claude-dominated | TypeScript full-stack |
| Project J | 17 | — | — | — | 35 | Claude-dominated | Mailer agent (Python) |
| Project K | 9 | (low) | — | — | 100 | git-dominated | Router frontend |
| Project L | — | 133 | — | — | NO_GIT | Codex-dominated | Industry data crawl (Codex overnight scheduled) |
Orchestration distribution: 3 multi-engine · 1 dual-engine · 4 Claude-dominated · 3 Codex-dominated · 2 git/single-tool
Multi-engine battlegrounds: Projects B / D / G run Claude + Codex + Cursor in parallel — daytime Claude for long reasoning, late-night Codex on xhigh for implementation, Cursor for in-workspace editing. Three shifts, one developer.
🧬 Evolution curve — AI usage is evolving
2026-01 Codex starts: 29 threads / 38.6M tokens / CLI 0.118.0
2026-02 Daily-ization: 23 threads / 251M tokens (warm-up)
2026-03 ⚡ Claude Code joins, mass explosion: 261 sessions / 114K msgs / peak day 3-18 (12,301)
Antigravity concentrated experiment (3-17 → 3-31, 105 tasks across 4 artifact types)
Codex monthly leap: 132 threads / 702M tokens
2026-04 Two-engine maturity: Claude 282 sessions / Codex 948 threads / 6.16B tokens
/effort muscle memory fully formed (60% of slash usage)
2026-05 Steady scaling: Codex 962 threads / 4.41B tokens; Claude usage shrinks to critical nodes
Cursor enters as daily IDE / antigravity flagship project under continuous maintenance
Monthly activity trend
| Month | Claude sessions / msgs | Codex threads / tokens | Milestone |
|---|---|---|---|
| 2026-01 | — | 29 / 38.6M | Codex 0.118 launch |
| 2026-02 | — | 23 / 251M | Daily-ization warm-up |
| 2026-03 | 261 / 114K | 132 / 702M | Mass explosion: Claude joins, Antigravity bursts, peak day 3-18 |
| 2026-04 | 282 / 52.7K | 948 / 6.16B | Two-engine maturity, Codex takes off |
| 2026-05 | 62 / 11.2K | 962 / 4.41B | Codex steady scale, Claude focuses on critical nodes |
Model migration notes:
- 2026-03 → 04: Codex spent ↑ 8.8× (702M → 6.16B), driven by
gpt-5.5/gpt-5.4replacing the earlygpt-5.1-codex-max/gpt-5.2-codex-sparkcohort - 2026-04 → 05: Codex spent ↓ 28% (6.16B → 4.41B) but thread count +1.5% — per-thread efficiency improved (better caching, stable xhigh use)
- Claude side: Opus 4.6 is the consistent main driver. From April, Opus 4.7 (1M context) joins to handle ultra-long-context scenarios (spent 83M), not replacing 4.6 but specializing. Sonnet 4.6 used for rapid iteration.
💡 Topics & keywords
router · billing · payment · agent · plan · skill · mcp · antigravity · vibe-forge · trace_id · plugin · dashboard · mailer · CLI · observability · captcha · channel management · billing multiplier · walkthrough · first-principles · LLM router · multi-tool orchestration · token economics · cache leverage · session architecture · sub-agent · plan-mode
Topics cluster in three rings:
- Commercial product: LLM router channel management / billing / payment / captcha / dashboard / user service
- AI tool construction: skill / vibe-forge / AVC / Readme.skill / antigravity template / mcp / plan / hook
- Observability & trust: trace_id full-link / log / observability / retry backoff / payment_sources
⏱️ Working rhythm
24h heatmap (Claude + Codex merged)
00 ▓▓ Claude 38 · Codex 9
01 ▓ Claude 16 · Codex 19
02 ▒ Claude 6 · Codex 12
03 ▓▓▓▓▓▓ Claude 1 · Codex 154 ← Codex overnight burst start
04 ▓▓▓▓ Codex 99
05 ▓▓▓▓▓ Codex 120
06 ▓▓▓▓▓ Codex 130
07 ▓▓▓▓▓ Codex 128
08 ▓▓▓▓▓▓▓▓ Claude 1 · Codex 189 ← morning peak
09 ▓▓▓▓▓▓ Claude 5 · Codex 156
10 ▓▓▓▓▓▓▓▓ Claude 12 · Codex 182
11 ▓▓▓▓▓▓▓▓ Claude 60 · Codex 148 ← Claude morning peak
12 ▓▓▓▓▓▓ Claude 24 · Codex 141
13 ▓▓▓▓▓▓▓ Claude 47 · Codex 119
14 ▓▓▓▓ Claude 45 · Codex 57
15 ▓▓▓▓▓▓ Claude 49 · Codex 107
16 ▓▓▓▓▓▓▓▓ Claude 52 · Codex 148 ← afternoon double peak
17 ▓▓▓▓▓▓▓ Claude 39 · Codex 153
18 ▓ Claude 16 · Codex 19
19 ▓▓ Claude 46
20 ▓▓ Claude 55
21 ▓▓ Claude 42
22 ▓ Claude 23 · Codex 4
23 ▓ Claude 28
Peak windows: Early 03-11 is a double peak from Codex automation + active morning work, afternoon 16-17 is the Codex second round, evening 19-21 is Claude wrap-up. Codex's heavy 3-7 AM activity correlates with the ai-21-00-ai-session-00 automation — AI doing the night shift.
Time span
- First active: Codex 2026-01-01 · Claude Code 2026-03-09
- Most recent: 2026-05-28 (today) · still active
- Span: 148 days
- Active days: 57 (Claude dailyActivity basis)
- Peak day: 12,301 Claude messages (2026-03-18); top 5 highest-volume days all within the 3-13 → 3-19 week
💎 Token economics
440M new paid tokens leveraged 10.22B cache replay, ratio 1 : 24; total through Claude alone 10.65B, plus Codex 11.56B — full-stack ~22.21B tokens through. Equivalent to processing 15.5 billion Chinese characters with AI across 148 days — roughly 21,000 times the length of Dream of the Red Chamber, or 38,000 times War & Peace.
Per-model token breakdown (sorted by spent)
| Model | spent | cache-read | leverage | % of total spent |
|---|---|---|---|---|
| Claude Opus 4.6 | 308.9M | 7.79B | 25.27× | 71.86% |
| GPT-5.5 (Codex) | 6.31B | — | — | — |
| GPT-5.4 (Codex) | 4.30B | — | — | — |
| Codex (unspec) | 606M | — | — | — |
| Claude Opus 4.7 (1M) | 83.3M | 1.82B | 21.85× | 19.38% |
| GPT-5.4-mini (Codex) | 265M | — | — | — |
| Claude Haiku 4.5 | 25.4M | 250.6M | 9.88× | 5.91% |
| Claude Sonnet 4.6 | 12.3M | 357.8M | 29.12× | 2.85% |
| GPT-5.3-codex (Codex) | 63M | — | — | — |
| Other Codex (5.2 / 5.3-spark / 5.1-codex-max / 5.1-mini) | 49M | — | — | — |
Monthly token trend
| Month | Claude spent | Claude cache | Codex tokens | Main model | Notes |
|---|---|---|---|---|---|
| 2026-01 | — | — | 38.6M | gpt-5.1-codex family | Codex starts |
| 2026-02 | — | — | 251M | gpt-5.2 / 5.3 | Warm-up |
| 2026-03 | (Claude peak) | (heavy cache) | 702M | gpt-5.3-codex / 5.4 | Explosion: Claude joins full-time |
| 2026-04 | (main driver) | (main driver) | 6.16B | gpt-5.4 / 5.5 | Two-engine maturity |
| 2026-05 | (consolidation) | (replay) | 4.41B | gpt-5.5 | Per-thread efficiency rises |
Model migration notes
- 2026-03: Early Codex models
gpt-5.1-codex-max/5.2-codex/5.3-codex-sparkshrink →gpt-5.4takes over - 2026-04:
gpt-5.5launches and immediately carries the load (1,108 threads, 52.9% of all Codex threads) - Claude side: Opus 4.6 is the consistent main driver from March. From April, Opus 4.7 (1M context) joins for long-context scenarios (spent 83M / cache 1.82B), specializing rather than replacing 4.6.
- 2026-04 → 05: Codex total tokens ↓ 28% but thread count stable — cache fluency improved, per-thread average dropped.
Unit input/output (reference only — not a KPI)
- ≈ 100K Claude tokens per commit (429.9M / 4,292, including planning / review / implementation)
- ≈ 502 Claude tokens per line of code churn
Reminder: AI output also includes massive high-value labor not directly converted to commits (architecture review / plan iteration / skill refactor / data cleaning / pair-debugging). Treating "X tokens per commit" as KPI is anti-incentive.
💰 Output × input
Same-period GitHub output
- 365-day total contributions: 3,706 (commits 3,467 + PRs 114 + issues 38 + reviews 9) · repos owned: 85
- Highest single day: 2026-03-18 (12,301 Claude messages, corresponding multi-repo GitHub burst)
Top repos (public data, original names retained)
| Repo | language | 365-day commits | stars |
|---|---|---|---|
| antigravity-workspace-template | Python | 169 | 1,246 ★ |
| awesome-architecture | Vue | 37 | 600 ★ |
| Readme.skill | (md) | 24 | 124 ★ |
| OpenCMO | Python | 349 | 84 ★ |
| Agent_View_Controller-AVC | JavaScript | 25 | 46 ★ |
| easy-claude-code | (md) | 24 | 45 ★ |
| vibe-forge | Rust | 38 | 14 ★ |
| clawdbot-webchat-lite | TypeScript | 11 | 12 ★ |
| agent-mailer (collab) | Python | 38 | 11 ★ |
| ReadYourUsers | TypeScript | 37 | 9 ★ |
| Vibe_coding_guide (collab) | — | 6 | 9 ★ |
| opencrab | Python | 2,526 | 1 ★ |
| Other 12 public repos | various | ~280 | 1-12 ★ each |
Total stars (Top 25 cumulative): ~2,217 ★
Primary languages (GitHub primary lang + local git weight)
Python · TypeScript · Rust · Vue · HTML · JavaScript · Jupyter Notebook · Markdown (7 main + multiple secondary)
📊 Data sources & privacy commitment
- 100% local data:
~/.claude/*(stats-cache + history + 77 projects + 11 plans + 6 skills + settings) +~/.codex/*(state_5.sqlite read-only + history + 11 skills + 4 automations) +~/Library/Application Support/Cursor/*(7 workspaces' ItemTable) +~/.gemini/antigravity/brain/*(105 tasks' metadata + markdown) + 13 local git repos'git log+ GitHub viagh api graphql - Kiro / Trae not installed; gracefully skipped (v2.5 supports them but no data on this machine)
- Conversation bodies are read only for keyword / collaboration-style analysis — raw text never appears in the report. Antigravity reads only metadata summaries and markdown headings — no screenshots, no browser cache, no pbtxt annotations.
- Work project names anonymized to "Project A/B/..."; public GitHub repos retain original names (public data is indexable anyway); API keys / tokens / emails scrubbed by regex.
- Report auto-generated by Claude Code / Codex / Cursor / Antigravity local data via Readme.skill v2.5.1; fully reproducible.
- Generated at: 2026-05-28T(local)