复制安装命令
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
Essays and writing behind this toolkit live at vexjoy.com.
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
Essays and writing behind this toolkit live at vexjoy.com.
AI agents skip steps.
"Looks correct" replaces running tests. "Trivial change" replaces verification. The agent confidently ships broken code because nothing structurally prevented it from skipping the work.
Harnesses have a second problem: given only a skill list, they do not route eagerly enough, or correctly enough. Good skills sit unused. So this toolkit connects the skills, agents, and workflows we want directly into the harness, automatically. You don't have to understand what is here. Say what you want in plain English and you get all the value we have put into it: the right specialist with the right methodology, behind gates that demand exit codes, not assertions.
44 domain agents, 122 workflow skills, 78 hooks, 136 scripts. Agents carry knowledge, skills enforce methodology, hooks block incomplete work, scripts handle determinism.
Works across Claude Code (/do), Codex ($do), Factory (/do), Reasonix (/do).
$ claude
> /do debug this Go test
Routing: go-engineer + systematic-debugging
Phase 1/4: Reproduce: running test, capturing failure...
Phase 2/4: Hypothesize: 3 candidates from stack trace...
Phase 3/4: Verify: isolated root cause in connection pool timeout
Phase 4/4: Fix: patch applied, test passing, PR opened
✓ Delivered: PR #847, fix connection pool timeout in health check
The router reads intent, picks a Go agent paired with a debugging skill, and runs the full lifecycle. You typed one sentence. The system did the rest.
ROUTE PLAN EXECUTE VERIFY DELIVER RECORD
┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐
│ /do │───▶│ Task │───▶│Agent │───▶│Tests │───▶│ PR │───▶│Route │
│Router│ │ Plan │ │+Skill│ │Gates │ │Branch│ │Result│
└──────┘ └──────┘ └──────┘ └──────┘ └──────┘ └──────┘
This is the single thing that separates it from "agent with a system prompt."
| Agent Says | What Happens |
|---|---|
| "Code looks correct, skip tests" | Exit gate requires test output. Blocked. |
| "Trivial change, no verification" | Hook blocks completion without evidence. |
| "Similar to before" | Skill demands case-specific proof. |
| "User is in a hurry" | Protocol overrides time pressure. |
| "I'm confident" | Gate demands exit code, not assertion. |
Hooks fire automatically. Gates block completion. Skills encode counter-arguments at every skip-worthy step. The agent verifies or it doesn't finish.
For what I do, the difference is enormous. If you're doing simple single-file edits, maybe less so.
The same routing serves knowledge work. The content engine researches, drafts in a calibrated voice, validates against 397 AI patterns, and repurposes finished pieces for each platform. /html turns any request into a single self-contained HTML file: report, slide deck, prototype, data viz, diagram. Non-engineers who try the toolkit consistently name the HTML artifacts as the thing they love. No code, no setup beyond the installer.
Changes to the toolkit itself ship with evidence. New skills get blind A/B tests against a no-skill baseline before merge. Routing and writing-standard decisions carry measured verdicts; PHILOSOPHY.md cites the numbers. Experiments that lost go into the negative-results registry, what-didnt-work.md; the registry now covers routing reversals, unvalidated A/B citations, and disabled lint rules alongside the original program refutations.
The automated nightly evolution loop (/evolve, writes to evolution-reports/) ran regularly through mid-May 2026. It is currently dormant; recent evidence has come from manual PRs instead.
git clone https://github.com/notque/vexjoy-agent.git ~/vexjoy-agent
cd ~/vexjoy-agent
./install.sh
Links into ~/.claude/ and mirrors into ~/.codex/, ~/.factory/, ~/.reasonix/ — each mirror only when that runtime is detected (its command on PATH or its home dir already exists). The installer asks symlink (live updates via git pull) or copy (stable snapshot).
Want only part of the toolkit? Run ./install.sh --configure to pick which skills, agents, and hooks install, or copy .local.example/profile.yaml to .local/profile.yaml and edit. No profile file = full install, unchanged behavior. Credit: @thomasvan. Details: .local.example/README.md.
| CLI | Entry Point |
|---|---|
| Claude Code | /do |
| Codex | $do |
| Factory | /do |
| Reasonix | /do |
Full setup: docs/start-here.md
Mirrors agents, skills, and supported hooks into ~/.codex/. The original six-hook allowlist was correct for Codex v0.114, when tool hooks only intercepted Bash. Current support requires Codex v0.144.1+ and classifies the 74 Claude hook registrations as 26 native, 35 adapter-backed, and 13 unsupported (61 supported). These are registration counts, not unique hook files. The installer also preserves explicit per-subagent model routing for GPT-5.6 Sol by setting the MultiAgent V2 compatibility keys documented in openai/codex#31814.
Codex now exposes apply_patch to tool hooks. VexJoy's adapter converts each patch operation into the Write/Edit payload expected by existing guards, but it cannot intercept writes performed through unified_exec, unmatched MCP tools, WebSearch, or other unsupported tool paths. PreCompact and Stop adapters also receive less telemetry than Claude Code: Codex does not provide Claude's conversation_history or session_data. This is expanded compatibility, not full Claude parity.
After install or any hook-definition change, run /hooks in Codex and review the new definitions before trusting them. Codex hash-trusts hook commands and skips changed, unreviewed definitions.
Gemini CLI support removed (deprecated upstream, transitioned to Antigravity CLI); Antigravity support pending CLI maturity. Per Google's transition announcement, Gemini CLI stops serving requests on 2026-06-18 for Google AI Pro / Ultra and free Gemini Code Assist for individuals. Gemini API integrations (image-gen backends, sprite pipeline, GEMINI_API_KEY) are unaffected and stay in the toolkit.
If a prior install mirrored into ~/.gemini/, remove the stale mirrors with:
rm -rf ~/.gemini/skills ~/.gemini/agents ~/.gemini/hooks ~/.gemini/scripts ~/.gemini/antigravity/plugins/vexjoy-agent
Mirrors agents (as "droids"), skills, and all hooks into ~/.factory/. Hook config merges into ~/.factory/settings.json with paths rewritten.
Mirrors skills, scripts, and the allowlisted hooks (scripts/reasonix-hooks-allowlist.txt) into ~/.reasonix/ (no agent or custom-command surface, so neither is installed; the /do router rides in as a skill). Reasonix fires only 4 events (PreToolUse, PostToolUse, UserPromptSubmit, Stop), so only hooks for those events are allowlisted. Hook config is written to the hooks key of ~/.reasonix/settings.json in Reasonix's native flat shape (one entry per hook, match regex over the tool name); the generator builds absolute python3 commands, so no path rewrite is applied. MCP/model/permissions in ~/.reasonix/config.json are user-owned and left untouched.
The toolkit supplies its own routing, domain knowledge, methodology, and enforcement. The default system prompt duplicates most of that.
claude --system-prompt "."
Strips built-in tool-use instructions. The toolkit's agents, skills, hooks, and CLAUDE.md provide equivalent coverage.
| Layer | Count | Does |
|---|---|---|
| Agents | 44 | Domain knowledge: idiom tables, failure mode catalogs, error-to-fix mappings |
| Skills | 122 | Phased methodology with gates. Can't skip steps. Each phase has exit criteria requiring evidence. |
| Hooks | 78 | Fire on lifecycle events. Block incomplete work. Zero LLM cost. |
| Scripts | 136 | Determinism: test runners, linters, validators. No LLM judgment. |
Full skill catalog: docs/skills.md.
┌─────────────────────────────────────────────────┐
│ SKILL.md │
│ ┌─ Frontmatter ─────────────────────────────┐ │
│ │ triggers, pairs_with, success-criteria │ │
│ └────────────────────────────────────────────┘ │
│ Reference Loading Table (conditional imports) │
│ Phased Instructions (numbered, with gates) │
│ Verification (evidence requirements) │
└─────────────────────────────────────────────────┘
A game built entirely by Claude Code using these agents, skills, and pipelines:
I just want to use it Install, learn /do, done.
I do knowledge work Writing, research, data analysis, moderation, HTML artifacts. No code.
I'm a developer Architecture, extension points, adding agents and skills.
I'm an AI power user Routing tables, pipelines, hooks, telemetry DB.
I'm an AI agent Machine-dense inventory. Tables, paths, schemas.
I'm on LinkedIn 🚀 Thought leadership. Agree? 👇
Full design philosophy: PHILOSOPHY.md
One report-only script surfaces upkeep work; it prints a digest and never edits, deletes, or blocks.
python3 scripts/stale-skill-scan.py --top 20 ranks stale skills and agents as pruning candidates. Run it quarterly; see docs/deprecation-template.md.Scheduled work follows the same boundary as everything else: judgment uses agents; repeatable plumbing uses scripts.
| Need | Use |
|---|---|
| Run a deterministic command on a schedule | scripts/agent-scheduler.py with runner: "command" |
| Run an agent judgment on a schedule, webhook, or file change | scripts/agent-scheduler.py with the default runner: "claude" |
| Install or remove a user crontab entry safely | scripts/crontab-manager.py |
| Audit shell cron reliability | cron-automation |
| Keep one interactive objective moving until criteria verify | objective-loop |
See CONTRIBUTING.md.
MIT. See LICENSE.
name: motion-pipeline
promoted_to: game-pipeline
user-invocable: false
description: "CPU-only motion data processing pipeline for game animation: BVH import, contact detection, root decomposition, motion blending, FABRIK IK. No GPU required."
allowed-tools:
- Read
- Bash
- Write
- Edit
- Glob
- Grep
routing:
triggers:
- "mocap"
- "motion data"
- "animation pipeline"
- "BVH import"
- "contact detection"
- "IK solve"
- "motion blend"
- "bone trajectory"
- "root extraction"
- "FABRIK"
- "skeletal animation data"
category: game-animation
pairs_with:
- game-sprite-pipeline
- phaser-gamedev
agents:
- rive-skeletal-animator
- pixijs-combat-renderer
- game-asset-generatorCPU-only motion data processing pipeline for game animation, inspired by Meta's ai4animationpy framework (CC BY-NC 4.0). All operations run on numpy and scipy with no GPU or PyTorch required.
ai4animationpy's Math/Tensor.py imports torch unconditionally at the top
level, which propagates through every module (Animation, Import, IK, Math).
This means zero ai4animationpy modules are importable without PyTorch installed.
The standalone implementations in scripts/motion-pipeline.py replicate the
key algorithms from their source code using only numpy + scipy.
# Create venv (one-time)
python3 -m venv /home/feedgen/vexjoy-agent/motion-pipeline-env/
# Install CPU-only deps
motion-pipeline-env/bin/pip install numpy scipy pygltflib Pillow
# Verify
motion-pipeline-env/bin/python -c "import numpy; import scipy; import pygltflib; print('OK')"
The venv is gitignored. The skill documents setup; it does not commit the venv.
All commands output JSON to stdout. Errors go to stderr with exit code 1.
Parse a BVH mocap file and print a motion summary.
motion-pipeline-env/bin/python scripts/motion-pipeline.py import-bvh FILE \
[--scale 0.01] # scale cm->m for CMU/Mixamo files
Output fields: name, num_frames, num_joints, framerate,
total_time_seconds, bones[], root_trajectory (x/y/z range).
Detect ground contact frames per bone (foot, hand) using height + velocity
thresholds. Replicates ContactModule.GetContacts() from ai4animationpy.
motion-pipeline-env/bin/python scripts/motion-pipeline.py extract-contacts FILE \
--bones LeftFoot RightFoot \
--height 0.1 \
--vel 0.5
Output: { "bones": { "<name>": { "contact_frames": [...] } }, "total_frames": N }.
Split motion into root trajectory (WHERE + HOW) and per-joint local Euler angles (POSE). Implements the RootModule / MotionModule decomposition pattern.
motion-pipeline-env/bin/python scripts/motion-pipeline.py decompose FILE \
--hip Hips
Output: root_trajectory.positions[], root_trajectory.velocities[],
root_trajectory.facing_directions[], per_joint_euler_zyx_degrees{}.
First 5 frames shown in stdout; full data requires piping to a file.
Blend two BVH clips at a fixed alpha using SLERP rotations and LERP positions. Clips must share the same bone hierarchy.
motion-pipeline-env/bin/python scripts/motion-pipeline.py blend FILE_A FILE_B \
--alpha 0.5
Output: summary of the blended motion.
Run FABRIK inverse kinematics on a bone chain at a single frame.
motion-pipeline-env/bin/python scripts/motion-pipeline.py solve-ik FILE \
--chain Hips:LeftFoot \
--target 0.2,0.05,0.3 \
--frame 10
Output: chain[], target[], initial_positions[], solved_positions[],
end_effector_error (metres).
Convert a BVH mocap file into a TypeScript MoveFrame function compatible with
road-to-aew's wrestlingMoves.ts interface. Outputs keyframe-interpolated
TypeScript to stdout (and optionally a file).
motion-pipeline-env/bin/python scripts/generate-move-ts.py BVH MOVE_NAME \
[--scale 0.01] \
[--contact-bones LeftToeBase RightToeBase LeftHand RightHand] \
[--num-keyframes 12] \
[--hip-bone Hips] \
[--output path/to/output.ts]
| Argument | Default | Purpose |
|---|---|---|
BVH | — | Path to .bvh mocap file |
MOVE_NAME | — | Kebab-case name (e.g. roundhouse-kick) used in TS identifiers |
--scale | 0.01 | Position scale; 0.01 converts cm→m for CMU/Mixamo files |
--contact-bones | LeftToeBase RightToeBase LeftHand RightHand | Bones used to detect the impact window |
--num-keyframes | 12 | Keyframe count in the output array (min 2) |
--hip-bone | Hips | Root bone name for trajectory extraction |
--output | stdout only | Write TS to this file path in addition to stdout |
Implementation note: The script imports motion-pipeline.py as a module
via importlib rather than calling it as a subprocess. This bypasses the 5-frame
truncation applied by the decompose CLI command, giving access to all frames.
Output structure:
// Generated from roundhouse-kick.bvh on 2026-04-13
// Keyframes: 12, Impact window: 0.45-0.55
const ROUNDHOUSE_KICK_KEYFRAMES = [...] as const;
export function getRoundhouseKick(progress: number): MoveFrame {
// keyframe lookup + linear interpolation
// isImpact based on detected contact window
return { attacker, defender, isImpact };
}
The attacker's offsetX/Y/Z are root trajectory positions normalized to
start at origin. Rotations are in radians (converted from the BVH's Euler
ZYX degrees). The defender reaction is computed procedurally: pushed backward
at impact, eases to mat post-impact.
Impact detection: The script finds the first run of 3+ consecutive contact
frames across the specified bones. For strike moves, this captures the moment
of hit. For walking/idle clips (feet always down), the window will be frame-0
and isImpact will be nearly never true — this is correct behavior.
Validation: The script prints a summary to stderr including trajectory range, impact window, and a structural syntax check. Exit code 1 if validation fails.
The decomposition from ai4animationpy becomes a design contract for all game animation work:
Animation State
root_trajectory -- WHERE (position, velocity, facing direction)
per_joint_euler -- HOW (local pose in ZYX Euler degrees)
contact_frames -- WHAT (contact states for feet, hands)
[guidance] -- WHY (intent; handled at game engine layer)
This separation enables:
| ai4animationpy module | This script equivalent | Notes |
|---|---|---|
Import/BVHImporter.BVH | load_bvh() | Same parsing logic; scipy replaces torch |
Animation/Motion | Motion dataclass | numpy-only; no torch backend |
Animation/ContactModule | extract_contacts() | Height + velocity criterion identical |
Animation/RootModule | decompose() root section | FK decomposition via matrix inverse |
Animation/MotionModule | decompose() joint section | Local Euler extraction via scipy |
IK/FABRIK | solve_ik_fabrik() | Algorithm identical; no Actor dependency |
| Downstream agent | Data consumed |
|---|---|
rive-skeletal-animator | per_joint_euler_zyx_degrees from decompose |
pixijs-combat-renderer | contact_frames from extract-contacts |
combat-effects-upgrade | contact_frames (impact timing) |
game-asset-generator | Produces source BVH files for this pipeline |
A walking cycle from ai4animationpy demos is available at:
/tmp/ai4animationpy/Demos/BVHLoading/WalkingStickLeft_BR.bvh
This is a full-body biped walking clip from the Geno character rig.
/tmp/ai4animationpy (cloned locally)Math/Tensor.py line 5.
No conditional import path exists. Standalone implementations are the correct approach.
评论 (0)
暂无评论,成为第一个评论者吧!