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.
npx skills add btspoony/mstar-harness --skill mstar-routing-evalgit clone --depth 1 https://github.com/btspoony/mstar-harnessWrote 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.
[](https://agentmods.dev/skills/btspoony/mstar-harness/mstar-routing-eval)<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.
<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>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once 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 |
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.
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 以 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-rolesskill 的project-manager角色 - 全局约束:
mstar-harness-coreskill(含 harness 不变量与 skill 索引)
评估方法
对每个场景:
- 将实际路由与
expected_route进行比对。 - 检查所需产出是否已规划并最终产出。
- 验证没有
hard_fail_if条件被违反。 - 验证
Context Loaded已声明且包含必要文件。 - 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)。
- 记录路由质量和缺失的证据。
评估执行步骤(1-2-3)
- 准备输入:加载当前
assets/routing-evals.json、project-manager.md、mstar-harness-core(含 references)。 - 逐案判定:按
expected_route/must_have_artifacts/hard_fail_if打分并记录证据。 - 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。
- 门禁顺序总体正确,但存在可修复的轻微缺项(例如
Fail- 非 hotfix 跳过
clarify或tasks。 - 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。
- 非 hotfix 跳过
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.
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.
- 11d ago First seen · 232 lines · 129 tokens per session scan A ba8858dc1e25
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.
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