mstar-routing-eval

mstar-routing-eval is a skill for Claude Code, Cursor from btspoony/mstar-harness. It costs 129 tokens per session (3,724 once invoked), scanned A, original, MIT.

A Chinese-language evaluation skill for checking whether software tasks are routed to the right agents and project checkpoints.

In plain words
What is it for?
Use it to assess routing scenarios, expected assignments, required deliverables, context loading, and phase-gate compliance in the Morning Star harness.
Why use it?
It helps test that a development process follows its required roles, loaded context, outputs, and failure rules.

Skill for Claude CodeCursor

Written for Claude Code and Cursor: shipped in a Claude Code plugin, but also installed under .cursor/. Also seen: mentions subagents; mentions OpenCode.

Part of the morning-star-harness plugin — 23 skills, 5 commands, 14 agents, 2 hooks shipped together

Good fit Use it to assess routing scenarios, expected assignments, required deliverables, context loading, and phase-gate compliance in the Morning Star harness.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/btspoony/mstar-harness/mstar-routing-eval
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 btspoony/mstar-harness --skill mstar-routing-eval
Clone the repo
git clone --depth 1 https://github.com/btspoony/mstar-harness

Made for: Claude Code, Cursor.

Or install morning-star-harness, the plugin that ships this one along with the rest of its 23 skills, 5 commands, 14 agents, 2 hooks.

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 mstar-routing-eval

README.md
[![agentmods](https://agentmods.dev/badge/skills/btspoony/mstar-harness/mstar-routing-eval/github.svg)](https://agentmods.dev/skills/btspoony/mstar-harness/mstar-routing-eval)
Your own site
<a href="https://agentmods.dev/skills/btspoony/mstar-harness/mstar-routing-eval"><img src="https://agentmods.dev/badge/skills/btspoony/mstar-harness/mstar-routing-eval/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 mstar-routing-eval

Your own site · 80×15
<a href="https://agentmods.dev/skills/btspoony/mstar-harness/mstar-routing-eval"><img src="https://agentmods.dev/badge/skills/btspoony/mstar-harness/mstar-routing-eval.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 129 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,724 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 $0.00129 $0.03724
Opus 5 $0.00064 $0.01862
Sonnet 5 $0.00026 $0.00745
Haiku 4.5 $0.00013 $0.00372

Measured 11d ago against content hash ba8858dc1e25, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

mstar-routing-eval 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 11d ago.

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.

.cursor/skills/mstar-routing-eval/SKILL.md · 232 lines

How it starts

The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Maintainer scope(维护专用 · Cursor)

  • 不是 runtime pack:日常 specify → implement → QC 不要求 Read 本 skill;已从 skills/mstar-* 运行时包中拆出,避免与「每轮必读」混淆。
  • Canonical 位置:本仓库内 仅此目录.cursor/skills/mstar-routing-eval/)为正文 + assets/ SSOT;不再维护 skills/mstar-routing-eval/ 副本。
  • 谁在读@prompt-engineer 改规则前;维护者改 project-manager / harness 门禁后跑回归;repo-maintenance 清单涉及路由时。

Load order(必读顺序)

在同一会话或任务中首次 Read 本 skill 时:必须先 Read mstar-harness-core skill(SKILL.md,以及评估路由与门禁时需要的 mstar-harness-core/references/)。 本 skill 的 routing-evals.json 场景校验的是对 harness 的遵守情况;若未建立 harness 上下文,评估易与真实门禁脱节。冲突时 mstar-harness-core 为准

摘要mstar-harness-core — 期望路由与 phase gate;本 skill — 场景集、Routing Eval Report 模板与回归方法。

Morning Star Routing & Evaluation Harness

1. PM 路由评估

本节用于验证 @project-manager 是否将任务路由到正确的 agent 和门禁。

输入

  • 场景集:本 skill 的 assets/routing-evals.json
  • 路由策略来源mstar-roles skill 的 project-manager 角色
  • 全局约束mstar-harness-core skill(含 harness 不变量与 skill 索引)

评估方法

对每个场景:

  1. 将实际路由与 expected_route 进行比对。
  2. 检查所需产出是否已规划并最终产出。
  3. 验证没有 hard_fail_if 条件被违反。
  4. 验证 Context Loaded 已声明且包含必要文件。
  5. 验证 Assignment 的语言契约:字段名英文、任务正文可中文、执行产出/报告英文(除非用户明确要求其他语言)。
  6. 记录路由质量和缺失的证据。

评估执行步骤(1-2-3)

  1. 准备输入:加载当前 assets/routing-evals.jsonproject-manager.mdmstar-harness-core(含 references)。
  2. 逐案判定:按 expected_route / must_have_artifacts / hard_fail_if 打分并记录证据。
  3. 输出报告:按下文 Routing Eval Report 模板汇总(含 phase_gate_compliance_rate)。

评分

  • Pass:路由和产出满足预期,无硬性失败。
  • Borderline:存在轻微偏差但质量门禁得到保留。
  • Fail:触发硬性失败条件或跳过关键门禁。

Phase Gate 评分细则

用于量化 specify -> clarify -> plan -> tasks -> implement 合规度。

  • Pass
    • 非 hotfix:Prepare 与 Execute 门禁均完整通过;无跳步实现。
    • hotfix:允许压缩路径,但已明确事后 clarify/RCA 补记安排。
  • Borderline
    • 门禁顺序总体正确,但存在可修复的轻微缺项(例如 Phase Gate Checklist 字段漏写但证据可追溯)。
    • 未出现"先实现后补 gate"的行为。
  • Fail
    • 非 hotfix 跳过 clarifytasks
    • 已知 plan drift 仍继续实现,且无 plan 回写。
    • hotfix 未承诺或未记录事后 clarify/RCA

Read the full file on GitHub · 232 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 232 lines · 129 tokens per session scan A ba8858dc1e25

Subscribe to this mod's changes

mstar-routing-eval is a skill published in the GitHub repository btspoony/mstar-harness (58 stars, last pushed today), licensed MIT. It adds 129 tokens to every session and 3,724 once invoked, about $0.0006 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.