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-conventionsgit 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-conventions)<a href="https://agentmods.dev/skills/btspoony/mstar-harness/mstar-conventions"><img src="https://agentmods.dev/badge/skills/btspoony/mstar-harness/mstar-conventions/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-conventions"><img src="https://agentmods.dev/badge/skills/btspoony/mstar-harness/mstar-conventions.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 | $0.00237 | $0.05082 |
| Opus 5 | $0.00118 | $0.02541 |
| Sonnet 5 | $0.00047 | $0.01016 |
| Haiku 4.5 | $0.00024 | $0.00508 |
Grade A, and why
mstar-conventions 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 — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Load order（必读顺序）
首次 Read 本 skill 前：必须先 Read mstar-harness-core（SKILL.md）。 本 skill 只约定 目录与路径；不突破状态机与门禁。冲突时 以 mstar-harness-core 为准。
| 你还可能要 Read | 何时 |
|---|---|
mstar-artifacts |
主 plan、review bundle 摘要、status.json、residual、InReview/QC 波次、knowledge |
mstar-project-governance |
projects/<id>/roadmap.md 编写约定 + residuals.json register 生命周期、_default 回退 |
mstar-branch-worktree |
Assignment 写分支 / worktree / QC 检出 |
mstar-review-qc |
派 QC（PM 同轮必读；SDD 强制 tri） |
mstar-sdd |
PM 执行 Execution mode: sdd 的 implement 波次 |
Workflow
主链：按「路径符号」+「{HARNESS_DIR} 解析顺序」确定目录（默认 .mstar/，兼容 .agents/）→ 按「初始化 Plan 目录」建 plans/ / status.json 并追加 gitignore 进程产物集（进程本地、结果共享）→ 多 Plan · 同一 Spec 时按「Spec 驱动的分支模型」登记 iteration base / spec 集成分支 / 各 Plan 实现分支 / PR target → 主 plan 写入 {PLAN_DIR}（Plan-Writing Path Gate，不引入外部默认 plan 目录）。未启用 plan 时 → 对话追踪，门禁（QC/QA）照常。
路径符号（SSOT）
| 符号 | 默认 |
|---|---|
{HARNESS_DIR} |
.mstar/ |
{PLAN_DIR} |
{HARNESS_DIR}/plans/ |
{SDD_DIR} |
{HARNESS_DIR}/sdd/<plan-id>/（SDD 运行时 scratch + review bundle；gitignored） |
{ITERATION_DIR} |
{HARNESS_DIR}/iterations/ |
{KNOWLEDGE_DIR} |
{HARNESS_DIR}/knowledge/（默认；.mstarc knowledge_dir 声明时用声明值） |
{SPECS_DIR} |
{HARNESS_DIR}/specs/（默认）；解析见下文「{SPECS_DIR} 解析」 |
{WORKFLOW_DIR} |
{HARNESS_DIR}/workflows/（默认；.mstarc workflow_dir 声明时用声明值）——v3 每 lifecycle 一个 workflows/<id>/（snapshot.json + notes.jsonl） |
{PROJECT_DIR} |
{HARNESS_DIR}/projects/（默认；.mstarc project_dir 声明时用声明值）——v3 项目层 projects/<id>/roadmap.md + residuals.json |
Engine check (when available): import
resolveHarnessDir/resolvePlanDir/resolveSddDir/resolveIterationDir/resolveKnowledgeDir/resolveSpecsDir/resolveWorkflowDir/resolveProjectDirfrom@mstar-harness/enginein a host hook — or runmstar path resolve [path](--jsonfor machine output) to print the resolved dirs — to confirm the resolution below. Onfail-> do not proceed; fix and re-run. Skill text below remains authoritative when the runtime is absent.
What ships with it
3 files 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 · 216 lines · 237 tokens per session scan A 9059db60b09d
mstar-conventions is a skill published in the GitHub repository btspoony/mstar-harness (58 stars, last pushed today), licensed MIT. It adds 237 tokens to every session and 5,082 once invoked, about $0.0012 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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