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: professional-communication
description: "Draft interpersonal and meeting messages: emails, memos, status updates, structured pushback or disagreement."
user-invocable: false
allowed-tools:
- Read
- Write
routing:
triggers:
- "business communication"
- "structured format"
- "clear writing"
- "write email"
- "draft memo"
- "executive summary"
- "summarize for management"
- "status update"
- "compose email"
- "draft response"
- "reply to my boss"
- "reply to manager"
- "help me write back"
- "work email"
- "meeting summary"
- "meeting notes"
- "write a message to"
- "pushback email"
- "disagree professionally"
- "difficult conversation"
not_for: "critiquing or stress-testing a proposal's merits — that is multi-persona-critique; deciding what to prioritize or work on next — that is productivity; writing blog posts or articles with a voice profile — that is voice-writer. This drafts interpersonal messages; it does not judge ideas, set priorities, or generate content."
category: content-creation
pairs_with:
- voice-writerThis skill transforms dense technical communication into clear, structured business formats using proposition extraction (identify all facts and relationships) and deterministic templates (apply consistent structure). It extracts every detail without loss, categorizes by business relevance, applies a standard template with professional tone, and verifies completeness before delivery.
Core principle: Transformation ≠ creation. Only restructure existing input; always extract from existing input and restructure it for executive clarity with preserved technical accuracy.
| Signal | Load These Files | Why |
|---|---|---|
| transforming raw engineer notes: stream-of-consciousness debugging, blockers, crisis updates | examples.md | Loads detailed guidance from examples.md. |
| drafting from section templates; phrase transformations | templates.md | Loads detailed guidance from templates.md. |
Goal: Extract every proposition from the input before structuring anything. This prevents information loss and ensures technical accuracy is preserved.
Step 1: Classify input type
Identify the communication type (this determines categorization strategy in Phase 2):
Step 2: Extract all propositions
Parse each sentence systematically. Extract all propositions before summarizing — summarizing skips propositions and loses facts:
Step 3: Document implicit context
Surface assumptions the author takes for granted but the audience needs stated. Non-technical audiences cannot act without this:
Step 4: Count and validate propositions
## Parsing Result
Input type: [technical update | debugging narrative | status report | dependency discussion]
Proposition count: [N distinct facts/claims]
Emotional markers: [frustration | satisfaction | urgency | neutral]
Extracted Propositions:
1. [Fact/claim 1]
2. [Fact/claim 2]
... (ALL propositions - NO information loss)
Implicit Context:
- [Assumption 1]
- [Assumption 2]
Gate: ALL propositions extracted with zero information loss. Proceed only when gate passes.
Goal: Categorize and prioritize all extracted propositions by business relevance. This prevents unsolicited sections and keeps output focused on what matters most.
Step 1: Categorize propositions
Organize by type (categorization determines template section placement):
Status: [items with current state]
Actions: [completed, in-progress, planned]
Impacts: [business and technical consequences]
Blockers: [dependencies, constraints]
Next: [required actions]
Step 2: Priority order
Rank by impact to executive decision-making, not completeness:
Only the highest-priority categories go into the output. Lower-priority items are preserved in Technical Details but not emphasized.
Step 3: Identify information gaps
Flag any propositions that need clarification before transformation. Ask for specifics only when severity classification is ambiguous:
Gate: All propositions categorized and prioritized. Proceed only when gate passes.
Goal: Apply standard template with professional tone. This ensures consistent, executive-ready formatting without speculative sections.
Step 1: Apply standard template
Include only the sections in the standard template (Risk Assessment, Historical Context, Mitigation Strategies). Use ONLY this structure:
**STATUS**: [GREEN|YELLOW|RED]
**KEY POINT**: [Single most important business takeaway]
**Summary**:
- [Primary accomplishment/issue]: [Business impact]
- [Current focus/blocker]: [Expected outcome/resolution need]
- [Secondary consideration]: [Implications]
**Technical Details**:
[2-3 sentences maximum preserving technical accuracy]
**Next Steps**:
1. [Specific action with timeline if available]
2. [Secondary action with ownership implications]
3. [Follow-up considerations]
Step 2: Tone adjustment
The transformation rules are deterministic (apply all):
Step 3: Status classification
Apply criteria consistently (inconsistency confuses stakeholders and erodes trust):
Always document reasoning: "Status: YELLOW (deployment successful but monitoring pending)" not just "Status: YELLOW"
Step 4: Action item specificity
Vague action items cannot be executed. Every next step MUST include:
Gate: Output follows template structure with professional tone and all specificity rules applied. Proceed only when gate passes.
Goal: Confirm transformation quality before delivery. All gates must pass; proceed only when complete.
Step 1: Compare output against extracted propositions — NO information loss allowed. If a fact from Phase 1 doesn't appear in output, it belongs in Technical Details.
Step 2: Verify technical accuracy — terms, metrics, causal chains preserved exactly. Preserve exact technical terms ("database issues" for "Redis cluster failover") — specificity is required.
Step 3: Confirm status indicator matches actual severity. Check reasoning against actual criteria (GREEN ≠ YELLOW vs YELLOW ≠ RED boundaries).
Step 4: Validate action items are specific — check each next step for (verb, scope, owner, timeline). "Fix the issue" fails; "Complete Redis failover testing in staging (DevOps, by EOW)" passes.
Step 5: Check appropriate detail level for target audience. If audience is non-technical, Technical Details should bridge jargon with plain explanations without losing precision.
Step 6: Document transformation summary to prove gate passage:
## Transformation Summary
Input type: [type]
Propositions extracted: [N]
Status assigned: [GREEN|YELLOW|RED] ([reasoning])
Information loss: None
Template applied: standard
Gate: All verification checks pass. Transformation is complete. Complete all 6 steps before delivering.
User says: "I fixed the database issue but then the API started failing so I had to rollback and now we're investigating the connection pool settings which might be related to the recent Kubernetes upgrade." Actions:
User says: "I can't make progress because the API team hasn't responded in 3 days and my sprint is at risk" Actions:
User says: "The latest deploy broke checkout completely, users are getting 500 errors, we rolled back but some orders might be lost" Actions:
Cause: Technical terms or acronyms critical to business impact are undefined.
Solution:
Cause: Input contains mixed signals (e.g., issue resolved but monitoring incomplete).
Solution:
Cause: Input contains multiple unrelated topics that could cross-contaminate status classifications.
Solution:
Constraint distribution in error handling:
${CLAUDE_SKILL_DIR}/references/templates.md: Status-specific templates, section formats, phrase transformations${CLAUDE_SKILL_DIR}/references/examples.md: Complete transformation examples with proposition extraction
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