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-coding-behaviorgit 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-coding-behavior)<a href="https://agentmods.dev/skills/btspoony/mstar-harness/mstar-coding-behavior"><img src="https://agentmods.dev/badge/skills/btspoony/mstar-harness/mstar-coding-behavior.svg" alt="Measured on agentmods" 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 | $0.00238 | $0.03697 |
| Opus 5 | $0.00119 | $0.01849 |
| Sonnet 5 | $0.00048 | $0.00739 |
| Haiku 4.5 | $0.00024 | $0.00370 |
Grade A, and why
mstar-coding-behavior 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 8d 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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）。 本 skill 只约束 编码与改动风格（Think / Simplicity / Surgical / Debugging / Goal-Driven / Communication）；Done 所有权、状态机 仍以 mstar-harness-core 为准；分支 / worktree / QC-QA 检出字段 → mstar-branch-worktree；调度防串扰 → mstar-dispatch-gates。冲突时 以 mstar-harness-core 为准。
摘要：mstar-harness-core — 不变量与门禁；本 skill — 实现与审查时的工程习惯，不替代 harness。
Priority remains（同 mstar-harness-core「信息源优先级」）：① 当轮用户显式指令 ② 项目 AGENTS.md / CLAUDE.md ③ mstar-harness-core ④ 其它 mstar-*（含本 skill）⑤ mstar-roles 角色正文。
Scope：适用于非平凡编码/调试/重构/审查任务；trivial one-liner 用判断、保持低开销。定义执行行为，不定义分支策略或门禁所有权。
Morning Star Coding Behavior Guidelines
Lightweight, host-agnostic coding-behavior principles that reduce common agent mistakes. Complements other Morning Star skills; does not override stage gates or role routing.
1) Think Before Coding
Do not silently choose an interpretation when ambiguity exists. State assumptions explicitly when material; if multiple plausible interpretations exist, present options and ask. Surface tradeoffs affecting scope/risk/maintainability. If critical context is missing, pause and clarify instead of guessing.
Quick check: can another reviewer see the assumptions made? If assumptions are wrong, will the user detect it before large edits happen?
Never lazy about understanding. Shorten the solution, never the reading. Read the task and every file the change touches fully first; trace the actual flow end to end. A small diff in the wrong place is not efficiency — it is a second bug shipped with confidence.
Read before you write. Before generating code in an existing project: inspect imports (which libraries the project actually uses — do not introduce a different library for the same purpose); look at nearby tests (they document expected behavior more precisely than comments); follow existing patterns (API routes, file structure, error handling — match it, do not silently introduce a different one). If no precedent exists, say so and ask. If not 100% sure a signature/parameter exists, check source/docs before using it — confidently calling a non-existent API may compile then fail at runtime.
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.
- 8d ago First seen · 168 lines · 238 tokens per session scan A 1e1f9786bbbf
mstar-coding-behavior is a skill published in the GitHub repository btspoony/mstar-harness (58 stars, last pushed today), licensed MIT. It adds 238 tokens to every session and 3,697 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.
Other skills, from other repositories
comet-verify
Comet Phase 4: Verify and Close. Invoke with /comet-verify. Verify implementation matches design, handle development branch.
comet-review
A read-only review guide for checking the current Comet change, a managed software-change workflow. It focuses on correctness, security, and boundary problems without changing files or advancing the workflow.
comet-github-pr-review
A read-only review process for pull requests in Comet's GitHub repositories. A pull request is a proposed code change; the review checks its current code, related issue, comments, merge status, and automated checks.
openspec-verify-change
Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.
requesting-code-review
Use when completing tasks, implementing major features, or before merging to verify work meets requirements.
receiving-code-review
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation.