codex-model-routing-team

codex-model-routing-team is a skill for Codex from zjp1997720/zhijian-skills. It costs 88 tokens per session (1,302 once invoked), scanned A, original, MIT.

A task-routing skill for splitting work among multiple coding agents. It decides when separate workers are worthwhile, assigns their tasks, and coordinates their results.

In plain words
What is it for?
Planning parallel work, selecting agent routes, assigning workers, validating task plans, and integrating their deliverables.
Why use it?
It avoids unnecessary delegation for small or tightly ordered tasks while giving larger independent tasks clear ownership and verification.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents; mentions Codex.

Good fit Planning parallel work, selecting agent routes, assigning workers, validating task plans, and integrating their deliverables.

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Install with agentmods
npx agentmods add skills/zjp1997720/zhijian-skills/codex-model-routing-team
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zjp1997720/zhijian-skills --skill codex-model-routing-team
Clone the repo
git clone --depth 1 https://github.com/zjp1997720/zhijian-skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for codex-model-routing-team

README.md
[![agentmods](https://agentmods.dev/badge/skills/zjp1997720/zhijian-skills/codex-model-routing-team/github.svg)](https://agentmods.dev/skills/zjp1997720/zhijian-skills/codex-model-routing-team)
Your own site
<a href="https://agentmods.dev/skills/zjp1997720/zhijian-skills/codex-model-routing-team"><img src="https://agentmods.dev/badge/skills/zjp1997720/zhijian-skills/codex-model-routing-team/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for codex-model-routing-team

Your own site · 80×15
<a href="https://agentmods.dev/skills/zjp1997720/zhijian-skills/codex-model-routing-team"><img src="https://agentmods.dev/badge/skills/zjp1997720/zhijian-skills/codex-model-routing-team.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,302 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00088 $0.01302
Opus 5 $0.00044 $0.00651
Sonnet 5 $0.00018 $0.00260
Haiku 4.5 $0.00009 $0.00130

Measured 5d ago against content hash 6c91cfb2f448, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

codex-model-routing-team scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/compile_route_plan.py, scripts/model_preflight.py, scripts/route_policy.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/codex-model-routing-team/SKILL.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codex 模型路由团队

主 Agent 保持当前模型,只做必要规划、所有权、集成和最终验收。独立的批量或复杂执行交给 1–3 个 Luna/Sol Worker,不重复已委派工作。两个以上 Worker 先编译 TeamPlan;registry 按风险/工作负载选路:常规 Sol Medium,复杂/高风险 Sol High,关键审查 Sol XHigh,机械批量 Luna XHigh。

不使用

简单问答、状态查询、单文件小改、强顺序和不可逆操作留在主任务;Worker 只能准备外部动作材料。

执行模式

  • native-v2(默认):按 registry 选 native_subagent Sol/Luna Worker;fresh context 使用 fork_turns="none",少量上下文写正整数。JSON 默认从 stdin 校验。
  • durable-app:仅当前 live 能力与宿主授权都通过时使用 App Thread;worktree 需求本身不授权创建用户可见 Task。
  • 上游 Skill 已定义拆分、阶段和产物时,遵守 适配协议,不重做阶段门或业务账本。
  • python3 scripts/compile_route_plan.py - 把紧凑 JSON 编译为 RoutePlan 并校验;只返回 dispatch 参数,永不派遣。

执行流程

  1. 自动派遣需 2+ 独立交付物且净收益为正;用户明确点名单 Worker 可执行,否则 lead_only
  2. 两个以上 Worker 按 TeamPlan 协议 编译 unit、依赖、所有权、交付物和集成顺序,并运行 scripts/validate_team_plan.py;上游计划只编译。
  3. registryProvider路由Surface 固定候选链;编译器降低手写成本。
  4. 每个 unit 生成 schema_version: "3.0" RoutePlan,写 surface_intent 并运行 scripts/validate_route_plan.py。原生候选须写 fork_turns、tuple-bound runtime_evidence;Fast 还须有 live service_tier=priority 证据。
  5. 任务包 写 unit、唯一 task_id、权限、验收和禁止下级派遣;简报路由、fallback 与 reserved slots。
  6. 原生路径遵守 生命周期;App 路径遵守 Thread 生命周期监督协议
  7. TeamPlan 默认 standard 6/8/3;expanded 12/16/6 需 live 容量门、2 个 reserved slots;按 child slots 切波,更严的宿主/用户限制优先。
  8. 每 unit 最多 2 次 attempt、一次 follow-up;失败只沿 预声明链。结构变化才修订 TeamPlan。
  9. 主 Agent 验证集成;原生 Worker close 或 completed-idle 后写 RELEASED,App Thread 过门后归档;运行 scripts/validate_team_ledger.py

硬门

  • registry 决定范围;live schema 只证明当前 host 接受精确组合。requested/accepted/observed 分开记录,未回显为 unknown
  • V2 父 Agent 可创建 picker 可见且未禁用的 V1 leaf model;Luna 可走原生 V2但不获协作工具,Sol/Terra 也禁止下级派遣。
  • 不加 model: luna frontmatter;编排入口留在协作父 Agent,Luna 只做 Worker。
  • Luna 最低 XHigh;Sol 最低 Medium,按工作负载与风险提升到 High/XHigh;Terra 仅显式首项;Grok 过门;Gemini blocked。禁止旧模型、Ultra 和低强度 fallback。
  • Fast 即 service_tier=priority;live schema 无字段时一律 Standard,不把 catalog 或请求值冒充 observed Fast。
  • app_thread 只用于 worktree、侧栏、跨任务恢复、耐久监督或预声明 fallback,并且必须有 live 能力与宿主授权证据。
  • Worker 不得继续派生或执行发布、发送、付款、删除、账户、生产变更;主 Agent 不切换模型。
  • TeamPlan 不创建 Planner、不调用重型计划、不落持久文件;同波写冲突、依赖环、超预算、计划外 Worker、下放验收必须拒绝。
  • 未确认返回值或 pendingWorktreeId 不得当正式身份;UNKNOWN 禁止追问、归档、fallback、重复创建、改库。

Read the full file on GitHub · 48 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago Changed · +1 lines · -35 tokens per session 6c91cfb2f448
  2. 12d ago First seen · 47 lines · 123 tokens per session scan A 9b92fbadc138

Subscribe to this mod's changes

codex-model-routing-team is a skill published in the GitHub repository zjp1997720/zhijian-skills (680 stars, last pushed 6d ago), licensed MIT. It adds 88 tokens to every session and 1,302 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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