mstar-iteration

mstar-iteration is a skill for Claude Code from btspoony/mstar-harness. It costs 112 tokens per session (3,604 once invoked), scanned A, original, MIT.

A workflow for starting, running, resuming, and closing a Morning Star iteration. An iteration is a defined cycle of planning, implementation, review, and delivery.

In plain words
What is it for?
Use it to run the Morning Star phases, manage plan lifecycles, set up isolated worktrees, dispatch implementation and review work, and finish with a mergeable pull request and passing CI.
Why use it?
It coordinates the stages needed to move several plans from initial direction through implementation, quality checks, pull-request delivery, and merge readiness.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

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

Good fit Use it to run the Morning Star phases, manage plan lifecycles, set up isolated worktrees, dispatch implementation and review work, and finish with a mergeable pull request and passing CI.

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

Made for: Claude Code.

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-iteration

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/btspoony/mstar-harness/mstar-iteration"><img src="https://agentmods.dev/badge/skills/btspoony/mstar-harness/mstar-iteration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 112 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,604 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 $0.00112 $0.03604
Opus 5 $0.00056 $0.01802
Sonnet 5 $0.00022 $0.00721
Haiku 4.5 $0.00011 $0.00360

Measured 2d ago against content hash 5f20b4c1e105, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

mstar-iteration 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 2d 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.

skills/mstar-iteration/SKILL.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

mstar-iteration(迭代管理)

Load order

Read mstar-harness-core first. Path symbols → mstar-conventions. Per-plan gates → mstar-phase-gates. Knowledge crystallization → mstar-compound. Phase 2 implement 波次(进入 per-plan implement 前)→ mstar-sdd + mstar-dispatch-gates;Phase 2 QC 前 → mstar-review-qc。Git/worktree 载体(有 git 写或 lease 时)→ mstar-branch-worktreePhase 1 角色派发 preflight(每次 invoke 前的 assignment preflight;enforcement: hard fail-fast)→ references/command-shared-invariants.md(本 skill 直接触发时不依赖 command 层)。On conflict, mstar-harness-core wins.

Phase detail 不在本 skill 正文:按下方 Phase route map 只加载当前动作对应的一行 detail——禁止无条件通读全部 phase references。

设计思路

mstar 实践模式通常是:一次迭代锁定几个 spec 点(specify + clarify),产生多个 plan,每个 plan 含多个 tasks。per-plan 生命周期有完整的闭环(Prepare → Execute → QC → Done)。Compound 不是 per-plan 活动——它是迭代级收口,在迭代内所有 plan Done 后,沉淀一轮知识。

本 skill 管理迭代 Phase 1–5(command 层可聚合编排,但 不得反向引用 command 名;第三方 helper 仅由 command 按需发现):

Phase 1: start
     ↓
Phase 2: Autonomous Execute  —— [per-plan lifecycle × N]
     ↓
Phase 3: iteration-close
     ↓
Phase 4: PR delivery(开 PR)
     ↓
Phase 5: PR merge-ready loop —— 至 mergeable + CI 全绿 + reviews resolved
     ↓
迭代交付完成

关键定位

  • Phase 3 在 integration 分支收口 compound / roadmap;开 PR(Phase 4)≠ 迭代交付完成
  • Phase 5merge-ready loop(修复 → 等 CI/review 波次结束再 push → 再验证,至 §5.5 exit);Loop 理念与 push cadence SSOT 在本 skill(§2.6;push cadence 细则 §5.1a → references/phase-4-5-pr-delivery.md);宿主 command 可叠加额外 non-mstar-* helper(优先 babysit / *-babysitgreploop 可选),但不写入 mstar-* load order。
  • 一次迭代 = 一个 PR;compound 产物随 PR 合入 snapshot branch.target

Phase route map(唯一路由表 — 按当前动作加载)

当前动作 必读 detail(按需加载,勿通读)
start(启动迭代 / 重开方向锁定) references/phase-1-prepare.md(§1.1–§1.6:上下文、范围与 direction lock、compass、索引、v2 状态面、产物边界、§1.6 Review & Edit 链)
execute / resume(推进或恢复 per-plan 循环) references/phase-2-worktree-lease.md(§2.0 五道闸、§2.1–§2.5 loop/dispatch 细则、control worktree + lease 全文)
close(全部 plan Done 后收口迭代) references/phase-3-iteration-close.md(§3.0–§3.6:entry checklist、compound、roadmap、完成标记、exit checklist + commit)
PR / merge-ready(开 PR、推进合并就绪 loop) references/phase-4-5-pr-delivery.md(§4–§5.2:开 PR、§5.1a push cadence、loop、exit checklist)
Phase 5 helper discovery(仅 command 层按需) references/phase5-helper-discovery.md(babysit / greploop 发现)

Read the full file on GitHub · 123 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. 2d ago Changed · -286 lines 5f20b4c1e105
  2. 7d ago Changed ca4e1e993c2f
  3. 11d ago First seen · 409 lines · 112 tokens per session scan A 4640e20c362a

Subscribe to this mod's changes

mstar-iteration is a skill published in the GitHub repository btspoony/mstar-harness (58 stars, last pushed today), licensed MIT. It adds 112 tokens to every session and 3,604 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.