SkillAtlasSkill 详情

routing-table-updater

Essays and writing behind this toolkit live at vexjoy.com.

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项目 README

来源文件:README.md

抓取于 2026年8月31日

VexJoy Agent

VexJoy Agent

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).

What It Looks Like

$ 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.

The Pipeline

  ROUTE        PLAN         EXECUTE      VERIFY       DELIVER      RECORD
 ┌──────┐    ┌──────┐    ┌──────┐    ┌──────┐    ┌──────┐    ┌──────┐
 │ /do  │───▶│ Task │───▶│Agent │───▶│Tests │───▶│  PR  │───▶│Route │
 │Router│    │ Plan │    │+Skill│    │Gates │    │Branch│    │Result│
 └──────┘    └──────┘    └──────┘    └──────┘    └──────┘    └──────┘

Anti-Rationalization

This is the single thing that separates it from "agent with a system prompt."

Agent SaysWhat 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.

Knowledge Work Is First-Class

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.

It Proves Its Own Changes

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.

Installation

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.

CLIEntry Point
Claude Code/do
Codex$do
Factory/do
Reasonix/do

Full setup: docs/start-here.md

Codex CLI Parity

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 / Antigravity CLI Support (removed)

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
Factory CLI Support

Mirrors agents (as "droids"), skills, and all hooks into ~/.factory/. Hook config merges into ~/.factory/settings.json with paths rewritten.

Reasonix Support

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.

Token-saving mode

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.

Four Layers

LayerCountDoes
Agents44Domain knowledge: idiom tables, failure mode catalogs, error-to-fix mappings
Skills122Phased methodology with gates. Can't skip steps. Each phase has exit criteria requiring evidence.
Hooks78Fire on lifecycle events. Block incomplete work. Zero LLM cost.
Scripts136Determinism: 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)            │
└─────────────────────────────────────────────────┘

Built with the Toolkit

A game built entirely by Claude Code using these agents, skills, and pipelines:

Choose Your Path

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? 👇

Philosophy

  • Zero-expertise operation. Say what you want. The system classifies, dispatches, enforces, delivers.
  • LLMs orchestrate, programs execute. Deterministic work belongs to scripts. LLM judgment handles design decisions, diagnosis, review.
  • Density. Every word carries instruction, rule, or decision. Cut everything else.
  • Breadth over depth. Right context ensures correctness. Unfocused context adds cost.
  • Structural enforcement. Exit codes enforce what instructions can't. Quality gates are automated, not advisory.
  • Everything pipelines. Complex work decomposes into phases. Phases have gates. Gates prevent cascading failures.

Full design philosophy: PHILOSOPHY.md

Maintenance

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.

NeedUse
Run a deterministic command on a schedulescripts/agent-scheduler.py with runner: "command"
Run an agent judgment on a schedule, webhook, or file changescripts/agent-scheduler.py with the default runner: "claude"
Install or remove a user crontab entry safelyscripts/crontab-manager.py
Audit shell cron reliabilitycron-automation
Keep one interactive objective moving until criteria verifyobjective-loop

Contributing

See CONTRIBUTING.md.

License

MIT. See LICENSE.

数据与 AIAgent / MCP / Skill 创作

中风险

  • 来源需自行核对维护者身份。
  • 包含脚本或命令调用,安装前请复核。
  • 未检测到明显外部权限要求。
  • 未检测到高风险命令。
  • 扫描发现:2 条。

Codex — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/notque/vexjoy-agent.git
  3. 将 "skills/meta/routing-table-updater" 文件夹复制到 Codex 的 skills 目录中。
  4. 重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Codex 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/notque/vexjoy-agent.git
  3. 将 "skills/meta/routing-table-updater" 文件夹复制到 Claude Code 的 skills 目录中。
  4. 重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Claude Code 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/notque/vexjoy-agent.git
  3. 将 "skills/meta/routing-table-updater" 文件夹复制到 Cursor 的 skills 目录中。
  4. 重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Cursor 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/notque/vexjoy-agent.git
  3. 将 "skills/meta/routing-table-updater" 文件夹复制到 GitHub Copilot 的 skills 目录中。
  4. 重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 GitHub Copilot 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/notque/vexjoy-agent.git
  3. 将 "skills/meta/routing-table-updater" 文件夹复制到 Windsurf 的 skills 目录中。
  4. 重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: routing-table-updater
description: "Maintain /do routing tables when skills or agents change."
user-invocable: false
allowed-tools:
  - Read
  - Write
  - Bash
  - Grep
  - Glob
  - Edit
  - Task
  - Skill
routing:
  triggers:
    - "update routing tables"
    - "sync routing tables"
    - "routing maintenance"
    - "rebuild routing index"
    - "routing drift"
  not_for: "fleet-wide routing policy, trigger governance, or standards enforcement (use the toolkit-governance-engineer agent). This skill mechanically regenerates and repairs the INDEX files."
  category: meta-tooling
  pairs_with:
    - toolkit-evolution
    - generate-claudemd

Routing Table Updater Skill

Overview

This skill maintains the /do routing indices when skills or agents are added, modified, or removed. It implements a Phase-Gated Pipeline -- scan, extract, generate, update, verify -- with deterministic script execution at each phase.

The skill reads metadata from all skills and agents (never modifies them) and validates and repairs the generated routing indices skills/INDEX.json and agents/INDEX.json. PostToolUse hooks (hooks/posttooluse-sync-skill-index.py, hooks/posttooluse-sync-agent-index.py) regenerate the indices automatically on every SKILL.md or agent-file edit; this skill covers drift those hooks miss (bulk changes, deletes outside the harness, corrupted index files).


Reference Loading Table

SignalLoad These FilesWhy
batch registration of many skills (invoked by pipeline-scaffolder)batch-mode.mdLoads detailed guidance from batch-mode.md.
resolving trigger conflicts: priority rules and severity levelsconflict-resolution.mdLoads detailed guidance from conflict-resolution.md.
errors, error handlingerror-handling.mdLoads detailed guidance from error-handling.md.
worked update scenarios: new skill, conflict, manual entry, complexity changeexamples.mdLoads detailed guidance from examples.md.
extracting trigger phrases: 'use when' clauses, action verbs, domain keywords, complexity inferenceextraction-patterns.mdLoads detailed guidance from extraction-patterns.md.
routing entry format: frontmatter routing block fields, INDEX.json entry shape, regenerationrouting-format.mdLoads detailed guidance from routing-format.md.
skill-entry examples for registering a newly created skillskill-examples.mdLoads detailed guidance from skill-examples.md.

Instructions

Phase 1: SCAN -- Discover All Skills and Agents

Goal: Find every skill and agent file in the repository.

Constraints: Repository must be at agents toolkit root (requires commands/do.md); only scan skills/*/SKILL.md and agents/*.md formats; file permissions must allow reading.

Step 1: Run scan script

python3 ~/.claude/skills/meta/routing-table-updater/scripts/scan.py --repo $HOME/vexjoy-agent

Step 2: Validate scan output

Expected output is JSON with skills_found, agents_found, skills (array of paths to skills//SKILL.md), agents (array of paths to agents/.md).

Step 3: Check for gaps

Compare discovered count against expected. If missing, check directory naming, agent file naming, or file permissions.

Gate: All skill directories and agent files are discovered without permission errors. Proceed to Phase 2 only after the gate passes. See references/error-handling.md for gate failure recovery.


Phase 2: EXTRACT -- Parse Metadata

Goal: Extract YAML frontmatter, trigger patterns, complexity, and routing table targets from every discovered file.

Constraints: YAML frontmatter must be valid; required fields (name, description) must be present; trigger patterns extracted from description text; complexity inference must follow references/extraction-patterns.md.

Step 1: Run extraction script

python3 ~/.claude/skills/meta/routing-table-updater/scripts/extract_metadata.py --input scan_results.json --output metadata.json

Step 2: Verify extraction completeness

For each capability, confirm extracted fields: name, description, trigger_patterns (skills), domain_keywords (agents), complexity (Simple, Medium, Complex), routing_table (Intent Detection, Task Type, Domain-Specific, or Combination).

Step 3: Validate trigger pattern quality

Review against references/extraction-patterns.md. Patterns must be specific enough to avoid false matches, broad enough to catch common phrasings, and free of generic terms.

Description trimming: skill descriptions trim safely to ≤40 router-line tokens when the frontmatter routing.triggers array stays untouched — triggers carry routing weight independently of the description. Verify trims with scripts/skill-sprawl-audit.py plus the routing-benchmark and trigger-ambiguity CI jobs (evidence: PR #801, 11 trims, routing-benchmark 68/68).

Gate: All YAML parsed successfully, required fields are present, trigger patterns are extracted for skills, and domain keywords are extracted for agents. Proceed to Phase 3 only after the gate passes. See references/error-handling.md for gate failure recovery.


Phase 3: GENERATE -- Create Routing Table Entries

Goal: Map extracted metadata to routing entries and detect trigger conflicts before the indices are rebuilt.

Constraints: Deterministic generation (no randomness); pattern conflicts detected immediately; entries sorted alphabetically; duplicates within the same group block gate passage.

Step 1: Run generation script

python3 ~/.claude/skills/meta/routing-table-updater/scripts/generate_routes.py --input metadata.json --output routing_entries.json

Step 2: Understand the generation process

  1. Group each capability by the routing classification extracted in Phase 2
  2. Detect pattern conflicts (see references/conflict-resolution.md)
  3. Sort entries alphabetically within groups

Step 3: Review conflict detection output

Low-severity conflicts: script applies specificity rules automatically. High-severity conflicts: script blocks gate passage and requires manual resolution.

Gate: All capabilities are mapped, conflicts are documented, and no duplicates remain within the same group. Proceed to Phase 4 only after the gate passes. See references/error-handling.md for gate failure recovery.


Phase 4: UPDATE -- Repair INDEX.json

Goal: Bring skills/INDEX.json and agents/INDEX.json in line with filesystem state.

Constraints: Both indices are generated, gitignored artifacts — repair means regenerating from frontmatter via the repo scripts; hand-edits to index files are lost on the next regeneration; source SKILL.md and agent files stay untouched; run from the repo root.

Step 1: Regenerate both indices

cd $HOME/vexjoy-agent
python3 scripts/generate-skill-index.py
python3 scripts/generate-agent-index.py

Step 2: Check for phantom entries

Every entry's file path must exist on disk:

python3 - <<'EOF'
import json, os
for idx, key in (("skills/INDEX.json", "skills"), ("agents/INDEX.json", "agents")):
    entries = json.load(open(idx))[key]
    phantom = [n for n, e in entries.items() if not os.path.exists(e["file"])]
    print(idx, len(entries), "entries,", len(phantom), "phantom", phantom or "")
EOF

Gate: Both generators exit 0 and both indices contain zero phantom file paths. On generator failure, fix the offending frontmatter (the error names the file) and rerun. Proceed to Phase 5 only after the gate passes.


Phase 5: VERIFY -- Validate Routing Correctness

Goal: Final validation of the skill package and the rebuilt indices.

Constraints: No duplicate trigger phrases within an index; every index entry's file path exists; complexity values must match Simple/Medium/Complex; overlapping patterns documented with priority rules.

Step 1: Run validation script

python3 ~/.claude/skills/meta/routing-table-updater/scripts/validate.py

Validates skill package structure, SKILL.md frontmatter, and script executability. Exit 0 = pass.

Step 2: Understand verification checks

  1. Structural: Skill package complete (SKILL.md, scripts, references), frontmatter parses
  2. Content: No duplicate triggers, every index entry's file path exists (Phase 4 Step 2 check)
  3. Conflicts: Overlapping patterns documented, priority rules applied

Gate: All checks pass. Task complete ONLY if final gate passes. See references/error-handling.md for gate failure recovery.


Examples

See references/skill-examples.md for worked examples (new skill created, agent description updated, conflict detection, manual entry preserved).


Batch Mode

When invoked by pipeline-scaffolder Phase 4 (INTEGRATE), this skill operates in batch mode to register N skills and 0-1 agents in a single pass.

See references/batch-mode.md for batch input format, batch process, and the batch vs single mode comparison table.


Integration

This skill is typically invoked after other creation skills complete:

  • After skill-creator: New skill created, routing tables need updated entry
  • After skill/agent modification: Description or trigger changes require routing refresh
  • During repository maintenance: Periodic sync to catch manual drift
  • After pipeline-scaffolder Phase 3: N skills created for a domain, all need routing (batch mode)

Invocation by other skills:

skill: routing-table-updater

The skill reads metadata from all skills and agents but never modifies them. Its only write targets are the generated indices skills/INDEX.json and agents/INDEX.json, always via the repo generator scripts.


Error Handling

See references/error-handling.md for the full error matrix (YAML parse errors, routing conflicts, manual entry overwrites, markdown validation failures) and per-phase gate failure recovery.


References

Reference Files

  • ${CLAUDE_SKILL_DIR}/references/routing-format.md: routing entry format specification (frontmatter routing block fields, INDEX.json entry shape, regeneration commands)
  • ${CLAUDE_SKILL_DIR}/references/extraction-patterns.md: Trigger phrase extraction patterns (regex, keyword maps, complexity inference)
  • ${CLAUDE_SKILL_DIR}/references/conflict-resolution.md: Conflict types, priority rules, severity levels, resolution process
  • ${CLAUDE_SKILL_DIR}/references/examples.md: Real-world examples of routing table updates (new skill, updated agent, conflict detection, manual preservation)
  • ${CLAUDE_SKILL_DIR}/references/skill-examples.md: Worked examples for the 5-phase pipeline (Phase 1-5 walkthroughs)
  • ${CLAUDE_SKILL_DIR}/references/batch-mode.md: Batch mode invocation by pipeline-scaffolder (input format, process, comparison)
  • ${CLAUDE_SKILL_DIR}/references/error-handling.md: Error matrix and per-phase gate failure recovery

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